Insights

Key Roles We Employ to Ensure Project Success

Fri, 30 May 2025 12:00:00 Z

Why Solution Architects and Functional Analysts Are Key to MES Project Success

In many MES (Manufacturing Execution System) implementations, there’s a common assumption: all you need is a solid functional and design specification, and a capable development team to build against it. In fact, we often see RFPs that state outright that the specifications are already complete, and all that's needed is an implementation team.

On paper, that might sound efficient. In practice, it's a risky oversimplification that can lead to misalignment, rework, and ultimately, project delays and underwhelming outcomes.

We have found that two roles—Functional Analyst and Solution Architect—are pivotal in accelerating execution, reducing risk, and ensuring that the MES solution delivers meaningful value from both business and technical perspectives.

The Functional Analyst: Breaking Down Barriers Between Business and Technical Teams

The Functional Analyst plays a crucial role as the bridge between the customer and the technical implementation team. This role goes well beyond gathering requirements—these resources:

Break down complex business processes into actionable, technically implementable pieces
Collaborate continuously with the customer, validating that what’s being designed and built maps back to real operational value
Act as the customer’s functional advocate, ensuring that the final system supports their workflows, compliance needs, and efficiency goals—not just in theory, but in practice

Without this role, development teams often work in a vacuum, relying on interpretations of static specs rather than an evolving understanding of customer goals. This can result in systems that technically meet the spec, but miss the mark on usability, flexibility, or business alignment.

The Solution Architect: Guarding Against Technical Missteps

Just as the Functional Analyst advocates for the business, the Solution Architect advocates for the customer’s technical landscape.

This person's role is to ensure that the solution is:

Architecturally sound and aligns with your enterprise IT strategies
Secure by design, following the customer’s authentication, authorization, and data protection policies
Performant and scalable, avoiding bottlenecks or patterns that may work now but degrade under real-world load
Built with vendor platform best practices in mind, minimizing future technical debt

Consider what happens without a Solution Architect’s oversight:

A report is built using a brute-force data query that works in dev but fails under production load
A custom interface stores sensitive data in an insecure format, exposing compliance risk
A seemingly small customization bypasses platform best practices, introducing hidden bugs and future upgrade blockers

These issues are costly—not just in time and rework, but in stakeholder trust.

The Misconception: Overhead vs. Insurance

Some organizations may view these roles as adding overhead, thereby increasing the cost of implementation. In fact, they may even explicitly seek out vendors who don’t include higher-level roles such as Functional Analysts or Solution Architects, believing that teams focused solely on execution are more cost-effective. On the surface, that can make those proposals look more attractive.

But in reality, these roles act as insurance against misalignment, technical inefficiencies, and business value gaps—all of which tend to surface much later in the project, when they’re far more expensive to fix.

We believe that every team member—developer, lead, project manager—should keep the solution’s business value and technical soundness in mind. But the Functional Analyst and Solution Architect are dedicated to ensuring exactly that. Their presence makes those goals explicit, accountable, and consistent throughout the lifecycle of the project.

We include these roles in our estimates and work breakdown structures, and we’ve developed documented best practices for how they engage across the implementation lifecycle. These practices are formalized as part of our DxOps Transformation service offerings, ensuring that their contributions are not ad hoc, but structured, repeatable, and deeply embedded in our delivery model.

By embedding these roles in our MES projects, we dramatically improve the odds that the final solution will meet the needs of both the operational and technical teams. They reduce rework, shorten decision cycles, and help us deliver a system that performs well, scales appropriately, and is embraced by users.

Conclusion: Building the Right Thing the Right Way

MES implementations are complex. They touch critical business processes, must integrate cleanly with enterprise systems, and operate in demanding manufacturing environments. That’s why we believe that delivering to spec isn’t enough—we need to deliver to purpose.

Functional Analysts and Solution Architects help us do just that. They turn specifications into real-world solutions. And their involvement is not overhead—it’s one of the smartest investments you can make toward project success.

Tips for Improving RFPs from the Integrator's Perspective

Wed, 23 Apr 2025 12:00:00 Z

One of the most challenging aspects of my job is planning our response to requests for proposal (RFPs) that we receive for digitalization initiatives. While the typical RFP process may be effective in scenarios involving procurement of tangible goods such as hardware, or execution of an engineering project with clearly defined deliverables, such as a building expansion or installation of the control system for a new production line, digitalization initiatives are different. These efforts are often inherently ill-defined in the beginning, and the situational nuances, difficult to capture in a 10 - 20 page document, can wildly impact the execution strategy, solution build, schedule, and cost. To make matters worse, a competing firm that oversimplifies specified requirements or associated project activities may present an attractive cost but has little chance of successful deployment and site acceptance. In this article I will explore the reasons for the challenges, considerations, and alternate methodologies.

Challenges:

The RFP may already target a specific software platform. As a services provider, we look to leverage best-in-class solutions across an expansive partner network based upon evaluation of the best fit for our customers, considering functionality, expandability, ease of deployment, cost, and numerous other factors. At the RFP stage, we do not know what motivations drove the customer's decision to focus on a given solution, or what criteria are most important to the customer. Is cost of utmost importance, or does the customer need a highly customizable option due to specific process nuances? Was the solution selection made by stakeholders lacking a true understanding of the software's capabilities and potential detractors? Did the customer consider an alternative option that we may feel is a better fit? All these open questions require us to make assumptions that may or may not be accurate. Alternatively In cases where the customer keeps the platform option open, we have to pick an option based on gut / assumptions, not knowing the answers to these considerations that could help us truly pick the right fit for the customer.

RFPs often present the process and required functionality at a very high level. It may list user requirements like 'production tracking', 'product sampling', or 'maintenance management'. A vendor may look at these requirements and say 'Box checked, we have that!'. However, the customer may be hoping for an extensive sample scheduling component when the software only provides the ability to input ad-hoc sample results for example. Because digitalization projects are often complex and evolving, an RFP that locks bidders into a fixed scope too early can create challenges down the road. The project may require additional features, workflow adjustments, or system refinements as real-world usage scenarios emerge. However, if these needs are not captured upfront, scope changes later can lead to contract disputes, cost overruns, and delivery delays.

Successful digital transformation is not just about technology - it requires internal process changes, stakeholder alignment, training, and careful deployment planning. However, RFPs often assume the customer’s team is fully prepared to adopt new workflows and technologies, overlooking resistance to change, training requirements, or gaps in technical expertise that can delay or derail a project. One bidder may optimistically make best-case assumptions, allowing them to present a more attractive offering, while another who makes pragmatic assumptions is not selected.

Digitalization initiatives often require integration with existing enterprise systems (ERP, SCADA, LIMS, underlying control systems, etc.), yet RFPs may not clearly outline the scope, complexity, or readiness of these integrations. The customer may underestimate the effort needed for data mapping, middleware development, or data synchronization, which can drastically affect implementation time and cost.

Often a customer has already made up their minds concerning who will be selected, but are required to seek a second bid or need to validate what the selected partner has proposed to make sure it is within reason. RFP response generation is a labor-intensive process, requiring substantial time and effort to tailor a proposed strategy based on assumption made concerning what the customer needs. While this is the cost of doing business, it is unfortunate that this effort must be expended by a services provider with little chance of securing the work.

Lastly, RFPs offer a weak feedback loop, with limited ability to truly collaborate with the customer to brainstorm, suggest options, and course correct based upon interaction. The customer is often gated behind a procurement firm or procurement team motivated primarily by finding the best cost or best hourly rate for the work. Questions can be asked but are often addressed with short, incomplete responses. Our benefits as a services provider are our ability to build relationships, solve problems, mitigate risk, and ensure flexibility to meet the customer's needs. It is difficult for these benefits to shine through in the RFP scenario, as the process is often rigid and inflexible.

Alternative Approach:

Rather than responding to an RFP with inherent gaps and assumptions, we often recommend a preliminary engagement leveraging our DxDiscovery and DxArchitecture service offerings. This approach allows us to deeply examine the customer’s current state, engage with key stakeholders to identify bottlenecks and pain points, and construct detailed business process scenarios that highlight critical "to be" workflows and corresponding decision points.

With this structured foundation, we can then evaluate various shortlisted technology options, assessing each against the customer's unique requirements, constraints, and long-term goals. Rather than being locked into a preselected platform that may or may not be the best fit, the customer receives impartial insights that empower them to make an informed, strategic decision regarding their digitalization roadmap.

From there, we provide a clear and realistic estimation of implementation and deployment efforts, ensuring alignment between expectations and execution realities. If the customer still wishes to proceed with an RFP, they can leverage our findings to construct a more precise and targeted package - one that clearly articulates requirements, mitigates ambiguity, and ultimately results in more accurate vendor proposals.

While the customer may have already engaged a consultant to create the RFP, our deep shop floor experience, structured methodologies, and extensive digitalization expertise across diverse industries and technology platforms give us an ability to uncover critical success factors that are often overlooked. This ensures that all essential aspects, including integration complexity, organizational change readiness, and scalability needs, are properly factored into the solution requirements.

Beyond just defining requirements, this collaborative assessment serves as a low-risk introduction to our organization and way of working. It allows the customer to experience our problem-solving approach firsthand, building confidence and trust before committing to a long-term engagement. It also preserves forward momentum, which is often the most critical factor in digitalization success. A lengthy RFP process can stall decision-making, diminish stakeholder engagement, and ultimately hinder project progress. In contrast, our approach enables swift alignment, informed decision-making, and an accelerated path to execution—ensuring the project delivers value as quickly and efficiently as possible.

Summary:

Responding to RFPs for digitalization initiatives is challenging because these projects are often ill-defined at the outset, with critical nuances that significantly impact execution, cost, and success. A rigid RFP process can lead to misaligned expectations, overlooked requirements, and cost-driven decisions that prioritize short-term savings over long-term viability. Where possible, I encourage my potential customers to consider alternatives that preserve momentum and minimize unexpected surprises during implementation.

MES Initiatives - Headcount Reduction or Repurpose?

Tue, 04 Mar 2025 12:00:00 Z

MES Initiatives - Headcount Reduction or Repurpose?

Many think that the role of an MES implementation is solely to aid in employee headcount reduction to cut costs. While that may be a motivation for some enterprises, more commonly, the MES aids in making the employees on staff more effective, transforming their roles. In the process, these employees become even more critical to the success of the manufacturing operation by allowing them to focus on higher-value contributions and skill development.

Enhancing Efficiency in Growth-Oriented Organizations

In an organization experiencing growth, the efficiencies enabled by the MES often lead to higher production output and operational scalability. Rather than spending time troubleshooting recurring issues, performing manual steps, or re-executing rework operations, personnel can focus on supporting increased output with precision.

As an example, in operations where diversification of the product mix is a strategic goal, the MES becomes essential in several ways:

Driving Production to Schedule: MES systems provide real-time tracking and advanced planning tools to keep production on track even with complex product portfolios.
Managing Changeovers: Automated workflows and scheduling minimize downtime during product or batch changes.
Supporting Operator Instructions: By providing clear, real-time instructions for new formulations and products, MES reduces learning curves and enhances accuracy.

These capabilities do not reduce headcount but instead ensure the operations personnel are highly effective and able to handle more challenging demands.

Knowledge Retention and Workforce Support

In mature operations focused on maintaining and optimizing production, the MES plays a critical role in mitigating knowledge loss due to employee turnover or retirement. Experienced employees often carry institutional knowledge critical to smooth operations, and the MES can act as a repository and guide for this knowledge.

For newly hired employees the MES offers the following:

Training Support: MES can provide digital instructions and process documentation, accelerating the onboarding process.
Preventative Maintenance Guidance: MES enables a shift from reactive to preventative maintenance, ensuring line stability and reducing downtime. This allows employees to focus on sustaining equipment performance and efficiency rather than reacting to unexpected failures.

Expanding Organizational Objectives Beyond Production Efficiency

MES initiatives are not limited to enhancing production efficiency; they are also instrumental in broader organizational objectives. For example:

Regulatory Compliance: MES ensures adherence to increasingly stringent government and industry regulations by maintaining detailed records and automating compliance reporting.
Product Quality Assurance: Real-time quality control measures and tracking improve product consistency and reduce defects.
Energy Management: MES provides insights into energy consumption patterns, enabling initiatives to reduce waste and promote sustainability.

These initiatives typically require a dedicated workforce to interpret data, implement strategies, and monitor outcomes, thus maintaining and sometimes even increasing headcount.

Empowering Employees Through Lean and Continuous Improvement

MES deployments eliminate tedious manual tasks, allowing employees to focus on solving operational bottlenecks and engaging in strategic improvement activities:

Lean Initiatives: Employees can implement lean manufacturing principles, such as waste reduction and process simplification.
Kaizen Events: The MES provides actionable insights and data that allow employees to take part in structured continuous improvement projects.
Root Cause Analysis: Employees can analyze data to identify underlying issues and implement corrective measures.

By redirecting efforts toward improvement and innovation, employees become active contributors to the company's growth mindset.

Fostering Innovation and Research

MES applications free up resources to enable R&D efforts and trial product runs. This fosters an environment of innovation where employees collaborate on the development of new products, test novel manufacturing methods, and refine processes to gain a competitive edge. By enabling these activities, MES shifts the enterprise’s focus from cost-cutting to growth and market leadership.

Addressing Workforce Challenges in Short-Staffed Operations

Many manufacturing operations struggle to find skilled entry-level employees, a challenge exacerbated by labor shortages. An MES can alleviate this strain by reducing the need for certain manual roles and allowing the existing workforce to focus on more strategic functions.

Examples include the following:

Supervisory Roles: Employees can transition into overseeing and optimizing automated systems rather than performing repetitive tasks.
Skill Development: MES systems provide data-driven opportunities for training and certifications, enabling workers to add value to the organization and prepare for advanced roles.
Improving Job Satisfaction: By enabling employees to take on more engaging and impactful responsibilities, MES systems can increase overall job satisfaction, reducing turnover and improving retention.

Conclusion

Implementing an MES is far more than a strategy for cost reduction or workforce downsizing. Instead, it serves as a transformative tool that empowers employees, enhances their roles, and enables them to focus on higher-value activities that directly contribute to the organization’s growth and success. By automating routine tasks, preserving critical knowledge, supporting workforce development, and aligning operations with broader organizational objectives, the MES ensures that employees become an indispensable part of the manufacturing process.

Rather than replacing workers, an MES allows companies to repurpose their talent into strategic areas like innovation, continuous improvement, compliance, and sustainability. This not only boosts productivity and operational excellence but also fosters a more engaged, skilled, and satisfied workforce. In a world where adaptability and growth are critical, MES becomes a cornerstone of a thriving, future-ready enterprise.

Why a Strong Integrator Is Essential for Digital Success

Mon, 03 Feb 2025 12:00:00 Z

Why a Strong Integrator Is Essential for Digital Success

Digital transformation is challenging. It involves carefully allocating limited budgets to maximize returns and sifting through a crowded technology market to find the right vendor fit. This process can be exhausting and intimidating, and success is not guaranteed - research from McKinsey, Harvard Business Review, Gartner, and other sources suggests that approximately 70% of digital transformation projects fall short of their goals. An increasing trend is for businesses to choose technology vendors as their primary implementation partners. It seems logical: these vendors created the technology, so they should be best equipped to implement it. However, while technology companies excel at developing products, they may not always have the expertise to navigate the complexities of your specific operations. Their strength lays in creating solutions, not necessarily in integrating them into your business.

This is where system integrators like RoviSys come in. Our expertise lays in the implementation and integration of technology solutions. Unlike technology providers, who focus on product development, we focus on delivering successful implementations. Our business depends on our ability to execute quality projects - our success is directly tied to how well we integrate and deploy technology.

We’ve invested heavily in refining our implementation approach, learning from customer experiences, and continuously improving our best practices. Our commitment includes strong Organizational Change Management practices and disciplined communication.

With over 30 years of experience in system integration, RoviSys has developed Digital Operations Transformation (DxOps) services—a comprehensive suite encompassing every stage of your transformation journey, from discovery all the way through to sustainment and continuous improvement. This portfolio reflects our accumulated knowledge and expertise, enabling us to deliver consistent, high-quality results.

When considering digital transformation of manufacturing operations, consider the benefit of partnering with a system integrator. While there are varying levels of quality, a skilled system integrator can take a strong product and significantly enhance your chances of achieving your transformation goals. At RoviSys, we are dedicated to being that partner who helps you succeed.

Agentic AI in Manufacturing: Foundations for Accelerated Adoption

Mon, 27 Jan 2025 12:00:00 Z

Agentic AI in Manufacturing: Foundations for Accelerated Adoption

A Reflective Start to 2025

I like to take time at the end of the year when customers are quiet and colleagues are away to spend some of my free time reflecting on accomplishments and working through the low-urgency but high-value tasks that I never seem to get to throughout the year. This ongoing work reflects both a professional responsibility and a personal commitment to staying informed. Similar to the end of 2023, I spent a good share of that time focused on investigating emerging technology in the generative AI landscape. This helped spur investments that I'm very excited for that are geared toward helping improve our team's workflows. During the break this year I dug deep, assessing what is real versus hype, and thinking through where we can apply the tangible advancements to improve the ways we work, optimize our methodologies, and ultimately deliver better results for our clients.

Fundamental Foundations in 2024

Over the past year, my team has refined our approach to digital transformation in manufacturing, focusing on the fundamentals that avoid risks and lead to successful results. These distill down to identifying business and process improvement opportunities, the implementation of effective solutions, and facilitating the changes that operations need to adapt to so they can realize value from their new solutions. Our team launched a comprehensive program through our DxOps Transformation framework where we clearly define what we do, the benefits our clients gain from our approach, and how the value will be realized from what we deliver. I’m also pleased to announce the launch of the RoviSys Insights blog—a space where our experts share actionable strategies and perspectives to support continued growth and improvement. As a system integrator, technology and platforms are a crucial factor to accomplishing manufacturers' goals, and our commitment to technical excellence has only expanded. Throughout 2024, our team has continued investing with our trusted vendors, gaining over 50 individual certifications across operations management solutions and MES vendor platforms.

Something Big is Coming

By now, there's a good chance you've heard the term "AI agents" or "agentic AI". Based on my own research and experimentation, the shock and awe that many experienced when LLMs and ChatGPT-type interactions were introduced was only the tip of the iceberg for what will soon be emerging. (And no, this article was not written by ChatGPT or the like... well, maybe I got a little assistance...)

Introduction to AI Agents and Agentic Frameworks

Agentic frameworks represent the next step in leveraging emerging technology to optimize and automate operational processes. Where LLMs have helped improve individual tasks and deliverables and have had a huge positive impact on people getting their work done, agentic concepts aim to coordinate and streamline the processes that even drive those tasks and deliverables. While they are gaining attention as a key innovation, their underlying principles may feel familiar to those experienced in leveraging large language models (LLMs) for decision-making and process optimization. For example, advanced prompt engineering with context chaining—where outputs are sequenced and informed by specific goals—mirrors the foundational logic of these frameworks.

What distinguishes agentic models is their ability to operate autonomously, processing complex datasets and identifying opportunities for improvement without constant human interaction. This evolution aligns with a broader trend in digital transformation, where tools are designed not just to execute tasks but to anticipate needs and deliver value proactively. For decision-makers, agentic frameworks represent a natural progression of the practices being implemented by industry innovators today.

Pesky Realities: Dependencies and Prerequisites

I can already hear it now; "Well great! Where can I buy one?" And trust me--someone will be happy to sell one to you. I hate to break the bad news--like we've learned in recent years from other technology innovations, agentic solutions are not magic beans or silver bullets that will solve all of your problems at the flip of a switch. In the context of manufacturing and industrial operations, for agentic models to succeed, a robust digital infrastructure is essential. Manufacturing Execution Systems (MES) play a pivotal role by organizing data, collecting context and data relationships, streamlining workflows, and preparing teams for digital integration. Without well-defined processes and an MES foundation, achieving seamless implementation of agentic models can be challenging.

Right Focus, Right Time

At the beginning of last year, my team's focus was squarely on, "How do we define solutions that will be useful in improving operational processes and decision making?" AI Agents and agentic frameworks were on our radars but were not the focus of our attention. Despite all of the interest around the *GPT hype, we kept our focus on defining how solutions improve operating processes. Fortunately--as it turns out--process and decision mapping is a fundamental enabler for applying agentic flows.

SIPOC Modeling and Process Structuring

The lack of well-defined processes in many manufacturing environments is a significant barrier to effective digitalization. Last year, our team adapted the SIPOC (Suppliers, Inputs, Process, Outputs, Customers) process modeling technique to help overcome this by breaking down workflows into manageable components and clarifying key decision factors. This structured approach provides a clear roadmap for implementing agentic models and maximizing their effectiveness.

Hype Versus Reality

If you are like me and have been swept up in the AI agent hype cycle, you've probably seen a few repeat examples of how these can be applied. And also like me, you're probably left wanting an example that is meaningful in a manufacturing setting--I mean there is not very much relevance between an agentic content marketing flow and a digital transformation program. Well, this is where the fun starts for me--and where the benefit of extended time out of the normal routine starts to pay back dividends. So, let's explore an example I've been thinking about.

A Common Challenge in Manufacturing

Daily/shift handoffs are critical yet often inefficient business process in manufacturing. Supervisors rely heavily on tribal knowledge and ad hoc communication, leading to gaps in information transfer. Processes are frequently undefined and managed on the fly, which can result in inconsistent decision-making and reduced operational efficiency.

Leveraging Agentic Models for Shift Handoffs

Agentic models offer a solution to these challenges by automating and streamlining several key aspects of shift handoffs:

Data Aggregation: Data processing agent models can compile and summarize key performance metrics, ensuring that the incoming team has relevant and actionable information.
Customizing Reports: Rather than rely on fixed-form reports, an agent model can adapt information based on daily performance factors, providing insights tailored to the specific needs of the shift.
Automated Alerts: In cases where typical SCADA alarming is too rigid to provide meaningful alerts, agentic models can evaluate and highlight critical issues relevant to the current operating conditions, such as aggregated equipment downtime or resource bottlenecks, reducing the chances of oversight.
Real-Time Detection: While constrained operations resources are sometimes barely able to repair what is broken, an agentic model can dynamically identify and measure emerging issues, allowing supervisors to make informed decisions without delays.
Continuous Improvement: By integrating feedback loops, agent models enable ongoing optimization of processes and communication.

Practical Example: Enhancing Shift Handoffs

Imagine a manufacturing facility where agents organize daily shift handoffs. Before each meeting, the agents aggregate operational data, identify trends such as recurring downtimes, and prioritizes critical issues. By dynamically detecting performance bottlenecks, the agent ensures that supervisors are equipped with actionable insights, enabling seamless transitions between shifts. The things no one has time for now become possible. Want to review the control room call log? Digitize the information and feed into an agent to summarize the key issues and resolutions. This real-time capability not only enhances efficiency but also fosters a proactive approach to problem-solving. Will we soon be able to say goodbye to the days of digging through data or allocating a business analyst to prepare tailored reports?

Future Outlook

Looking ahead, I believe agentic models are positioned to become increasingly mainstream in manufacturing. For companies that continue investing in robust digital infrastructure and well-structured processes, these frameworks will enable more efficient operations, deeper insights, and proactive decision-making. While there’s no silver bullet, organizations that balance foundational excellence with emerging technologies can expect measurable improvements in responsiveness and productivity. Over time, agentic frameworks will likely play a pivotal role in evolving smart factories and more adaptive manufacturing ecosystems.

Conclusion

Agentic concepts hold significant promise for manufacturing, but their success depends on well-defined processes, a solid technology foundation, thoughtful implementation, and supportive adoption. By focusing on these fundamentals, organizations can unlock the tangible benefits of agentic models to drive operational excellence, adapt to market changes, and deliver greater value to their customers. In the end, it’s a deliberate blend of proven best practices and forward-thinking technology that propels true digital transformation.

Building Lasting Value

Thu, 05 Dec 2024 12:00:00 Z

Building Lasting Value:

How RoviSys DxOps Transformation Consulting Delivers Real Results in Manufacturing

The Challenge of Consulting in Manufacturing Transformation

Consulting has a mixed reputation in manufacturing, often associated with abstract strategies that drive top-down motivations but fail to deliver meaningful results. Manufacturers frequently hear about the “why” without receiving tangible guidance on the “how.” This is especially problematic when quick wins are prioritized over sustainable growth, creating frustration for organizations seeking real value from digital transformation initiatives.

RoviSys' Relationship-Driven Approach

At RoviSys, we understand that true digital transformation is a journey, not a one-time project. Our approach centers on building long-term relationships where we serve as trusted advisors and partners to our clients. The goal is not just to implement Manufacturing Execution Systems (MES), but to support our clients’ evolving digital needs over time, providing value at every stage of their operational maturity. This focus on authentic relationships rather than quick sales is a foundational principle of RoviSys' culture and is reflected in our DxOps Transformation service model.

Defining and Building Trust in Transformation

Trust is the cornerstone of any meaningful relationship, particularly in consulting. In the context of digital transformation, trust means providing clear, unbiased insights that prioritize what is genuinely best for the client. It involves openly discussing limitations, risks, and potential outcomes, even when that means recommending steps that do not immediately generate revenue for RoviSys. We build trust through transparent communication, technology-agnostic recommendations, and consistent, quality delivery of the projects that we propose. This commitment helps create credibility, which is essential for long-term success.

How DxOps Transformation Builds Credibility

The DxOps Transformation framework is structured to support each step of a manufacturer's journey, ensuring that we deliver tangible results at every stage. It begins with DxDiscovery, where we provide an objective, detailed analysis of current operations, allowing us to identify real opportunities for improvement. This is built upon with DxArchitecture, which delivers strategic roadmaps that balance immediate needs with long-term goals. Each stage is designed to be unbiased, focused on finding and delivering value, and helping clients gain stakeholder buy-in while setting realistic expectations with wiggle room to adapt to changes that inevitably come up during the process. There is no doubt that the results of these initiatives are what ultimately matter; however our planning approach emphasizes the "way we work"--how we will collectively get there so our clients aren't left chasing the proverbial pot of gold at the end of the rainbow.

Implementation Expertise that Drives Sustainable Outcomes

When it is time to roll up our sleeves to implement solutions, our approach differs significantly from other system integrators or software vendors. We often meet new clients already working with providers who focus on resource-heavy deployments which can lack depth and fail to align with clients' strategic goals--the classic "throw people at the problem" approach. In contrast, our consulting offerings emphasize understanding the real drivers of value, whether they involve implementing new solutions or improving existing processes, and assembling a strategic project team with varied strengths to meet the business drivers. Through services like DxDeployment and DxEvolution, we ensure that any digital transformation effort maximizes ROI and minimizes disruptions, adapting to changes in the manufacturing environment while focusing on long-term improvements .

Not Every Solution is Digital

While we are strong advocates for MES as a powerful tool for operational improvement, we recognize that digitalization isn’t always the immediate answer for every manufacturer. Sometimes, operational enhancements can be achieved by optimizing existing manual processes, rethinking workflows, or simply repurposing existing tools more effectively. Our DxLean service offerings provide structured evaluation and expert guidance to mitigate operational challenges and bottlenecks throughout manufacturing operations. These outcomes may not align with our short-term sales objectives but they serve the broader mission of building lasting trust with clients. By prioritizing what is best for our clients’ operations, we position RoviSys as a long-term partner in their digital journey—ready to implement advanced solutions when the time is right.

The Technology-Independent Advantage

Our independence from specific technology vendors is a key differentiator. This allows us to offer truly agnostic guidance, evaluating technologies based on their fit for a client’s operational needs. We do have our favorites, of course. Our bias comes from our experience witnessing which platforms deliver successful projects, which means they are suited to meet the objectives of our customers. We leverage a wide range of digital tools but in a selective way to ensure they will be useful for our customers' operations teams who will use the resulting implementations. This independence not only enhances credibility but also supports long-term relationships built on delivering real value rather than meeting sales targets.

The RoviSys Difference: Trust and Transformation

Our approach to consulting is grounded in the belief that credibility is earned by delivering what’s promised—every time, not just in one project. DxOps Transformation defines a holistic approach to build upon initial transformation investments, maintaining momentum after the initial operational improvements are realized. This is the essence of DxEvolution--digitalized continuous improvement. By aligning with our manufacturing customers' strategic goals and adapting to their evolving challenges, we help clients achieve sustainable operational excellence while building the trust necessary for long-term growth.

Final Thoughts: Relationships Built on Credibility Drive Long-Term Success

In a rapidly evolving manufacturing landscape, digital transformation must be more than just a buzzword. It requires a thoughtful, disciplined approach that prioritizes lasting value alongside short-term wins. RoviSys is committed to this approach, and DxOps Transformation establishes a foundation of services that ties consulting, implementation, and value realization together in a clear and structured way to build meaningful relationships founded on trust and credibility. By focusing on real outcomes rather than immediate results, we differentiate ourselves as not just another consultant but as a strategic partner invested in our clients’ sustained success.

Road Mapping Digitalization Initiatives

Tue, 12 Nov 2024 12:00:00 Z

Road Mapping Digitalization Initiatives

One of the key aspects of our DxArchitecture services offering is formulation of a digitalization implementation and deployment roadmap, based upon definition of a body of business process scenarios detailing the manner in which digitalization will be applied to your day-to-day operations. It may seem that the ideal deployment methodology is to have all functionality in place at once, in as little time as possible. However, the reality is that due to various reasons, including budget, resource constraints, change management considerations, and risk to the business, a phased approach is typically the more pragmatic and successful approach. There is generally no 'one size fits all' path forward. The roadmap we work collaboratively with your stakeholders to formulate must consider a variety of factors specific to your situation, some of which are as follows:

Perceived ROI - Ultimately, ROI is the primary consideration. Any capability implemented and deployed must have some sort of return on investment. Certain capabilities will likely warrant a higher deployment priority due to the perceived ROI we determine as part of our DxArchitecture services offering. Based upon our analysis, various issues and opportunities may be factored into this determination, such as asset utilization, first-pass quality, accurate raw material inventory estimation, changeover time reduction, and a multitude of other factors.

A strong roadmap also considers balancing 'quick wins' with longer-term benefits. For example, if the capability with the highest ROI also requires a substantial investment of funds / resources, we may balance this with shorter-term quicker wins to foster support for the initiative as you work toward these loftier longer-term goals.

We are able to aid in ROI formulation based upon not only our rich experience working with other customers, but also direct interaction with your stakeholders, including various roles within the manufacturing facilities. This direct interaction reduces invalid assumptions, misconceptions, and hidden agendas that can often lead to the wrong priority focuses as digitalization initiatives progress, wasting both time and valuable funds.

Digitalization capability dependencies - Certain capabilities may be required to support others and thus must be implemented first. As an example, there may be a desire to establish OEE dashboarding on the shop floor to provide visibility that will improve asset utilization. However, doing so may first require establishment of schedule / product visibility so that the system knows what is being produced, how much should be manufactured, etc. in order to provide meaningful metrics. Consistent downtime fault reporting from the assets may also need to be implemented first to better quantify OEE asset utilization.

Supporting data availability - There may be a body of prerequisite data needed that must first be established. For example, there may be a desire to deploy machine learning functionality to better predict asset failure. However, such functionality will require a body of historical data that can be evaluated by the algorithms. Therefore, this may need to be deprioritized while functionality is put in place to gather the data in question and a body of representative information can be built up over the course of a longer time period.

External application dependencies - Is there a planned initiative to implement an external system, such as an ERP, that will require implementation of supporting manufacturing digitalization functionality to ensure proper execution. For example, does the ERP require real-time production and consumption information that requires tandem implementation of an MES? Is there an opportunity to establish certain MES functionality on the shop floor in advance of the ERP deployment to derisk the overall implementation, for example to give operations experience leveraging the MES before the data becomes of critical importance to ensuring proper ERP execution?

Infrastructure and IT considerations - Are there legacy applications in place that present risk to the business, due to lack of support availability, instability, security concerns, or incompatibility with planned IT/OT upgrades? Replacement or augmentation of these applications may warrant the highest priority as a result. In turn, are there legacy applications that are stable and work well, allowing their replacement to be de-prioritized?

Is there an opportunity to run the new system in parallel with legacy systems for some time period to prove out the functionality of the new system without risk to the business, both to ensure the new system is accurate and give operations experience leveraging the new system? Will this place undue burden on operations that counters these benefits?

Compliance requirements - A certain set of functions may be of highest priority to ensure compliance with regulatory requirements, regardless of perceived benefit to the business or ROI. For example, FDA or environmental reporting.

Budgetary considerations - There is likely only so much budget available in a given time period (quarter, year, etc.). We will work with your team to understand these budgetary constraints and determine the best way to apply the budget at play to ensure the most value for this budgetary spend is obtained.

The logistics in deploying the functionality to the shop floor must also be considered. It may make sense to deploy to certain lines or areas first in order to pilot the functionality, work out any kinks, and ease training & change management logistics. However, some functions may need to be deployed across the facility at one time to reduce confusion or to ensure cutover of dependent systems. For example, a capability like OEE visualization may be able to be deployed to a single area or line in a pilot capacity, but maintenance management functionality may need to be deployed across the facility as a whole so that maintenance technicians that work across the facility need not follow different procedures and utilize different applications depending on where they are working.

It may also be possible to deploy a capability in a more basic form, and then continue to add functions as the project progresses, so that initial ROI is obtained but this ROI increases as users become more comfortable. For example, perhaps initially the user is provided a few manual quality data points to input in order to apply statistical process control (SPC) to make a determination concerning process stability. At some point, it may be possible to automate this data collection and add numerous other quality data points to provide a more accurate view of plant stability, as well as introduce resolution procedures that can be followed should an out-of-control scenario be detected based upon learnings as these initial SPC non-conformances are dealt with.

Another important consideration is that roadmaps are not static in nature and must be re-evaluated over the course of the initiative. Priorities and goals will often shift throughout the course of the project for various reasons. A strategic business decision may drive shifting priorities, such as focus on a broader product portfolio, or introduction of a product with more advanced supporting digitalization requirements. Mergers and acquisitions may warrant a focus shift, either to bolster acquired business units or leverage established systems and processes they may bring to the table. Our periodic governance cadence & agenda allow these direction shifts to be discussed at a leadership level and propagated down to the project team so that priority changes can be made in a timely and efficient manner.

Deployment of a certain capability may also provide ancillary benefits that were not able to be accounted for initially, that in turn de-prioritize other capabilities or require other capabilities to be brought forward. For example, perhaps deployment of more standardized preventative maintenance procedures has led to better product quality, reducing the need for quality data capture and SPC implementation to determine product quality control root cause. However, the improved asset utilization has led to raw material inventory consumption challenges, necessitating implementation of real-time consumption reporting. Our project governance process allows these findings and results to be propagated up from the project teams to the leadership level, enabling changes in direction to be seen and acted upon as warranted, rather than continue to push forward a stale plan.

In both cases, our budgetary framework agreement approach allows for an efficient re-allocation of project dollars, enabling quick reaction to roadmap changes, ensuring that project momentum is maintained to refocus on the shifting priorities.

Formulation and execution of a large-scale digitalization initiative roadmap can be an overwhelming proposition for an organization. However, our proven DxArchitecture consulting processes help to demystify this undertaking, via application of pragmatic strategies to ensure your digitalization goals are met in an efficient, value-driven manner.

Relationships Matter

Tue, 29 Oct 2024 12:00:00 Z

Relationships Matter

Manufacturing is facing a lot of challenges—labor shortages, supply chain issues, rising costs, stricter regulations, cyber threats, and tough competition. With so many demands, it’s easy to focus only on tasks that feel essential and show tangible results. But often overlooked is how much relationships matter. When we take the time to learn more about each other—whether at a corporate or individual level—we create more collaborative workspaces. We’re more empathetic, better at giving constructive feedback, and more effective at asking questions and defining long-term paths to success.

When we connect—whether with a customer, colleague, or service provider—we foster trust and improve communication. These connections help us ask smarter questions, uncover new opportunities, and work together more effectively. Strong relationships are often the difference between just getting by and truly excelling.

In manufacturing and integration services, strong partnerships between customers and service providers are critical for success. Digital transformation projects, in particular, demand a unique level of collaboration to handle complexity, meet deadlines, and stay on budget. However, in the rush to get things done, relationship-building often takes a backseat. True partnerships go beyond checking boxes on a task list; they’re about understanding goals and finding the best way to achieve them together. Without this connection, it’s no surprise that nearly 70% of digital transformation projects fail.

Face-to-face interactions and visual engagement are essential for building strong relationships. It’s easy to misinterpret written or spoken communication when body language, tone, or context is missing. While remote work can speed up certain tasks, it often sacrifices meaningful connection. Turning on cameras during virtual meetings, scheduling regular governance updates, and having periodic in-person stakeholder reviews help maintain alignment and build trust. These touchpoints provide clarity, ensure priorities are understood, and encourage open feedback. Building trust doesn’t require elaborate gestures—just consistent, genuine engagement.

These connections are often the difference between just getting by and truly excelling.

As we start to close out 2024, ask yourself: Is your service provider helping you achieve your goals? Are they offering insights and driving innovation, or just delivering what you asked for? If you’re not sure, it might be time to rethink the relationship. Strong partnerships don’t just finish projects - they create opportunities for long-term success.

The takeaway: Don’t let busy schedules stop you from prioritizing relationships. They’re an investment in better results and a brighter future. Make the time to build them, and make sure the companies you work with are doing the same.

How Manufacturing Organizations Discover MES Solutions

Mon, 16 Sep 2024 12:00:00 Z

With a multitude of MES providers on the market, selecting the right solution can be a daunting task. The decision-making process often involves multiple stakeholders and extensive research. Manufacturers typically explore four major avenues when sourcing MES solutions: insights from research firms, peer recommendations, web searches, and usage of vendors with an existing footprint in their facilities.

Research Firms: Expert Guidance and Market Analysis

Research firms, such as Gartner, Forrester, and IDC, offer valuable insights and independent reviews on a wide range of enterprise software, including MES platforms. These organizations provide in-depth analyses of the market, highlighting key players, technological trends, and emerging solutions. Their reports and rankings play a crucial role in helping manufacturers evaluate and shortlist MES solutions that align with their strategic goals.

Gartner Magic Quadrant: One of the most well-known resources is the Gartner Magic Quadrant for MES, which positions vendors based on their ability to execute and the completeness of their vision. This enables manufacturers to quickly identify the leaders, challengers, and niche players in the MES market.
Forrester Wave: Similarly, Forrester’s Wave report offers comparative evaluations of MES platforms based on features, customer satisfaction, and potential market impact. These reports help manufacturers understand which platforms are most aligned with technological advancements like AI, IoT integration, and cloud solutions.

However, it's important to recognize that while these reports provide high-level insights, they may not account for the specific nuances of an individual manufacturing organization. For instance:

Generalized Recommendations: Research firms often rank vendors based on broad industry trends and performance criteria, which may not reflect the daily realities or unique requirements of a specific manufacturer. For example, a top-rated MES solution for the automotive industry may not perform as well in a pharmaceutical setting where regulatory compliance and batch control are paramount.
Lack of Context: These reports do not always account for unique factors such as integration with existing legacy systems, customization needs, or particular operational constraints of a manufacturer.

Thus, while research firm reports offer a valuable macro-level perspective and a good starting point, manufacturers should approach these rankings as part of a broader evaluation process that includes understanding their own operational requirements.

Peer Recommendations: Trusting the Experience of Industry Peers

Another source for discovering MES solutions is peer recommendations, where manufacturers rely on the insights and experiences of industry peers who have already implemented MES platforms. Peer recommendations can provide first-hand knowledge of the challenges and rewards of using a particular system.

Real-World Experience: Unlike vendor brochures or research reports, peers offer first-hand experiences with specific MES systems. This feedback is grounded in practical realities, such as how the system behaves under production stress, scalability, or its ease of use for shop-floor workers.
Industry-Specific Applications: Many MES platforms are tailored to specific industries—automotive, electronics, pharmaceuticals, or food & beverage. A peer in the same sector can offer insights into how a solution works in an industry-specific environment, from complying with regulations to managing specific production constraints.

However, while peer recommendations are often trusted due to their authenticity, they can also present significant challenges:

No Two Manufacturers Are Alike: A peer’s experience may not always reflect the needs of another organization. Manufacturing environments, infrastructure, and operational goals can vary significantly from one company to another. For example, a peer recommendation from a company with a highly automated, large-scale operation might not take into account the needs of a mid-sized manufacturer with more manual processes or unique regulatory requirements.
Missing Context: The advice given by a peer may not consider all the specific nuances of a manufacturer's business, such as the compatibility with existing systems, scalability, or customization needs, as well as the manufacturer's ability to support the system. What worked well for one organization may not necessarily work for another, which can lead to unintended complications if the unique situation of the manufacturer isn’t fully assessed.

Therefore, while peer recommendations provide valuable real-world insights, manufacturers must evaluate these recommendations within the context of their own environment and strategic goals. It's essential to understand that success stories from other companies may not automatically translate to success.

Web Searches: A Wealth of Information, But Also Challenges

The internet is one of the first places many manufacturers turn when beginning their search for an MES solution. Web searches can provide access to a vast array of resources, such as vendor websites, product demos, third-party reviews, and industry forums. However, web searches can also pose several challenges.

Information Overload: The sheer volume of content available online can be overwhelming. A single search query may return hundreds or thousands of results, making it difficult to sift through all the available information. Not all of these results are equally reliable, and manufacturers may find themselves buried under technical specifications, marketing materials, and user reviews that offer conflicting perspectives.
Conflicting Information: Different sources often provide contradictory information about the same MES solutions. For example, while one review may highlight an MES platform’s strength in real-time analytics, another source might report limitations in ease of use or customer service. Sorting through these conflicting opinions can be time-consuming and frustrating, making it harder to form a clear understanding of a system’s true capabilities.
Varying Quality of Sources: Not all websites provide equally credible or unbiased information. While some platforms offer in-depth and objective reviews, others may be heavily influenced by vendors themselves, promoting certain systems over others without clear justification. This lack of transparency can make it harder for manufacturers to find trustworthy data.

Vendors with an Existing Footprint: Leveraging Familiar Technology

Many manufacturers also turn to vendors who already have a footprint within their facility. For instance, a company with a specific vendor's PLCs might naturally gravitate toward that vendor's MES offerings due to familiarity and an existing relationship. This can offer some advantages:

Seamless Integration: Working with a vendor whose hardware or software is already deployed in the facility can simplify integration, as these systems may already be compatible with the manufacturer’s existing infrastructure. However, this is often not a given.
Reduced Learning Curve: Since operators and engineers may already be familiar with the vendor’s systems, there may be a reduced learning curve and faster onboarding process. But, due to acquisitions and different development teams, a vendor's MES offering may be very different from its other products.

This approach also comes with its own risks:

Sales Over Value: Vendors who are already embedded in the facility may be more focused on selling additional licenses or expanding their footprint than truly addressing the manufacturer’s specific needs. This can lead to initiatives that prioritize vendor profits over operational value, resulting in a solution that falls short of delivering the desired improvements in efficiency or flexibility.
Varying Levels of Success: Just because a vendor is a good fit for one area of a manufacturer’s operation (e.g., PLCs or SCADA) doesn’t mean their MES solution will perform equally well. Each component of a manufacturing ecosystem requires specific features and customizations, and some MES implementations that are driven by familiarity rather than functionality have had mixed levels of success.

The RoviSys Smart Manufacturing Delivery Approach

At RoviSys, we recognize the complexity and challenges manufacturers face when selecting an MES. Our Smart Manufacturing Delivery approach is designed to guide organizations toward the most effective solution by capturing the specific business intentions and process scenarios of each manufacturer.

We focus on understanding the architectural nuances of each facility, including existing infrastructure, legacy systems, and vendor relationships, to ensure that the recommended MES solution integrates seamlessly into the manufacturing environment. By analyzing the unique challenges and opportunities faced by our clients, we tailor our recommendations to meet their specific needs, avoiding a one-size-fits-all approach.

Leveraging our extensive vendor knowledge and quantitative scoring system, we provide unbiased recommendations that prioritize the manufacturer’s operational goals and long-term strategy. Unlike some vendors who may push additional licenses or focus on their own product portfolios, our goal is to deliver value-driven solutions that enhance productivity, efficiency, and scalability.

Additionally, we often introduce vendors our customers may not be familiar with. Our broad industry knowledge allows us to highlight innovative solutions that could be ideal fits for specific manufacturing challenges, which might otherwise go unnoticed.

With our deep expertise in MES systems, we ensure that our clients receive not only the most technically sound solution but also one that aligns with their broader business objectives. Our Smart Manufacturing Delivery approach ensures that manufacturers can navigate the complexities of MES selection with confidence, knowing that they are making the right choice for both the present and the future.

Conclusion

Selecting the right MES solution is a critical decision for manufacturing organizations aiming to modernize and optimize their production processes. Research firms like Gartner and Forrester offer expert analyses and market rankings but may not capture the unique needs of individual manufacturers. Peer recommendations provide real-world insights that reflect industry-specific challenges and successes, though they may not always account for the specific context of each manufacturer. Web searches provide a wealth of information but require careful navigation to avoid bias or conflicting reports. By combining these avenues with a comprehensive, tailored approach like that offered by RoviSys, manufacturers can make informed decisions that align with their operational needs and long-term business goals.

MES & DCS - Working Together to Promote Integrated Data Flow

Mon, 12 Aug 2024 12:00:00 Z

MES & DCS - Working Together to Promote Integrated Data Flow

Often, we see confusion concerning the role of the manufacturing execution system (MES) versus the role of the distributed control system (DCS) in facilitating a digitalized shop floor. Some attempt to leverage the MES as a DCS, while others try to incorporate MES functionality into the DCS. In reality, both systems are important pieces of a holistic digitalization architecture.

A distributed control system (DCS) is typically found in continuous and batch industries where real-time orchestration is required across various production units on the plant floor, and tight control of process values such as temperature, pressure, and flow throughout the facility is essential. A DCS may also introduce a degree of redundancy and fault tolerance to ensure that critical operations spanning longer time periods and multiple production units are never disrupted. Industries often leveraging a DCS include specialty chemical manufacturing, pharmaceuticals, beverage, power generation, and oil/gas production.

The DCS is an interconnected system of sensors, controllers, and associated computers distributed throughout the plant, facilitating data acquisition, process control, and feedback to the operator. A DCS can make coordinated adjustments to each of a plant's many interacting automated operations. A DCS also provides a front-end user interface alerting the operator of alarm conditions, allowing setpoint changes, and providing trending of process parameters such as temperature readings, flow readings, etc.

The purpose of the MES is to facilitate operations management on the shop floor. This includes enabling schedule execution, handling material transactions (consumption and production, genealogy, and reporting), and managing manual activities that must be done by operators, such as equipment changeovers, taking samples, weighing and kitting materials, performing manual equipment maintenance checks, etc. The MES replaces processes that were traditionally (and often haphazardly) tracked using paper processes. The MES also often provides insights concerning production, performance, and quality that can be leveraged by various stakeholders across the organization to make decisions concerning targeted improvements. While a DCS may need to react in a matter of seconds or even milliseconds to a process condition, the MES typically manages data with a granularity of minutes, hours, shifts, and days.

Given the different roles and responsibilities between the two systems, some manufacturers deploy both, but with no connectivity between the two. The DCS manages the equipment automation processes, and the MES manages the operational 'people' processes. While this is an improvement over a plant driven by isolated PLCs and paper, a far greater degree of improvement can be gained by connecting the MES and the DCS in a layered manner.

Some key examples of interaction points that can lead to more efficient execution include the following:

The MES typically possesses a view of the shop floor schedule, including products to be made, quantities, and associated bills of materials (BOMs). The MES can present a schedule view to the operator, allowing a process order to be activated and the resulting production batch to be staged to the DCS, which can associate the batch to a recipe and initiate execution.
The DCS typically possesses information concerning the amount of material transferred into a batch and the quantity of the batch produced but lacks the ability to associate transfer quantities to specific raw material lots and ERP process orders. The MES can receive raw transfer quantities over time from the DCS, associate these with the staged lots and process orders, and report consumption/production information to higher-level systems such as the ERP.
The MES can also perform broader genealogy/traceability reporting in the context of raw material/finished goods identifiers. For example, a report indicating all finished goods orders containing material from a specific raw material lot is more easily facilitated by the MES than a DCS, but the detailed raw transfer values are needed from the DCS to provide the proper quantity reporting.
The MES may be able to better calculate situational production parameters than the DCS that are reliant upon external data sources. For example, the MES may determine a blend percentage due to external data such as the CoA, quality sampling results, and finished goods tolerances that are not available to the DCS. The MES can then pass down these key parameters that are in turn leveraged by the DCS during production execution.
The MES can coordinate manual operations such as sampling but may need specific triggers from the DCS to know when to prompt a sampling operation to occur. For example, when a batch reaches the end of a certain phase, the DCS may send a signal to the MES, which the MES captures and leverages to trigger a specific sampling operation and oversees its execution, potentially interacting with lab instrumentation or an external LIMS. The result of the sampling operation may then be sent down to the DCS, permitting the batch to continue or a rework operation (such as an additional mix cycle) to occur.
The MES can allow contextualized, summarized information to be recorded based upon detailed raw data collected via sensors connected to the DCS. For example, the DCS may be connected to a temperature probe capturing the temperature of the batch over the course of its production. The MES may, in turn, leverage readings from this probe to capture the maximum or minimum temperature during the batch cycle and commit this to an electronic batch record.
While the DCS may possess specific batch procedural models for various units across the plant, the MES can facilitate the translation and abstraction of this detailed data into a standard batch reference model that allows for batch-to-batch comparison across the facility and even the enterprise, considering such aspects as batch duration, first-pass quality, key batch parameters such as concentration or yield, and other aspects.

The means of interfacing the MES to the DCS can vary greatly based upon the DCS vendor, but it is important in any scenario that standard, well-documented, consistent interface structures are leveraged across the systems to ease change management and maintenance concerns. Some DCS platforms, such as DeltaV, allow for the deployment of a batch historian layer on a SQL server that the MES can access to obtain data. Typical shop floor interface conduits using the OPC protocol are often the norm for data handshaking (trigger/response scenarios). Leveraging the concept of the universal namespace (UNS) can reduce the need for various interwoven direct connections between systems, further simplifying the data architecture and promoting data consistency.

There are some key 'red flags' that may trigger one to rethink the plant's overall systems architecture, including the following:

Relying upon the MES to facilitate real-time process alarming, such as alerting when a process parameter exceeds a certain limit, or a batch parameter such as mix time is exceeded.
Relying upon the MES to track batch production in real-time and stage setpoints across various isolated PLCs in real-time.
Relying upon the DCS to interact directly with the ERP layer to receive the schedule or report production/consumption.
Duplicating detailed batch recipe information across both the MES and DCS, making change management considerations more challenging when establishing new or editing existing formulations.
Requiring dual entry into both the MES and DCS, or requiring someone to read values off the DCS and manually record them on a paper log sheet.

All of these scenarios may warrant the establishment of both a proper DCS and MES, as well as integration between the two, to improve production efficiency, agility, and quality on the shop floor.

MES Implementation: Why the ROI Didn't Match the Hype

Mon, 22 Jul 2024 11:44:00 Z

MES Implementation: Why the ROI Didn't Match the Hype

The Critical Role of Functional Analysts in Delivering Value

Manufacturing Execution Systems (MES) have been promoted as game-changers in the manufacturing industry, promising to streamline operations, enhance productivity, and deliver significant returns on investment (ROI). However, many organizations find that their MES implementation falls short of expectations, with the anticipated ROI failing to materialize. This disconnect often leads to frustration and skepticism about the value of MES. But what’s causing this gap, and how can it be addressed? The answer lies in recognizing the pivotal role of functional analysts in the implementation process.

The Expectations vs. Reality Gap

MES implementations are complex, requiring a careful alignment of technology with business processes, organizational culture, and strategic goals. Companies often enter into MES projects with high expectations, driven by vendor promises and industry success stories. However, the reality is that MES projects are fraught with challenges, including:

Inadequate requirement gathering: Many MES implementations begin without a thorough understanding of the specific needs and pain points of the organization.
Customization challenges: The need to tailor the MES to fit unique manufacturing processes can lead to unexpected complexities and costs.
Integration issues: MES systems often need to work seamlessly with other enterprise systems like ERP, and poor integration can hamper the expected benefits.
User resistance: A lack of buy-in from employees or insufficient training can result in underutilization of the MES, further diminishing its impact.
MES solutions become stagnant post-implementation: Commissioning of MES is treated as the completion of the journey versus the starting point.

These challenges often culminate in an MES system that, while functional, doesn't deliver the promised ROI.

The Functional Analyst: A Key to Success

At the heart of a successful MES implementation is the functional analyst—a role that is often undervalued or overlooked in the rush to deploy new technology. Functional analysts are critical in bridging the gap between the business and technical teams, ensuring that the MES is not just implemented but fully embraced by the organization in a way that delivers real value.

Thorough Requirement Analysis

Functional analysts are experts in understanding business processes and translating them into technical requirements. They work closely with stakeholders to gather detailed, accurate requirements that reflect the true needs of the organization. This ensures that the MES is positioned to address specific challenges and opportunities, rather than being a one-size-fits-all solution.
Customization and Configuration

One of the common pitfalls in MES implementation is the over-customization of the system, leading to increased costs and complexity. Functional analysts play a crucial role in balancing customization with standardization. They assess where customization is necessary to meet business needs and where business process changes can be implemented to avoid complexity and drive best practices.
Effective Integration

MES systems do not operate in isolation; they must integrate with other enterprise systems to deliver their full potential. Functional analysts oversee the integration process, ensuring that data flows smoothly between systems and that the MES aligns with the broader IT landscape. This reduces the risk of integration issues that can derail the project and impact ROI.
Change Management and User Adoption

A new MES system often represents a significant change for the workforce. Functional analysts are instrumental in developing change management strategies that address user concerns, provide adequate training, and foster a culture of adoption. By ensuring that users understand the benefits of the MES and are equipped to use it effectively, functional analysts help to maximize the system’s impact.
Continuous Improvement

The work of a functional analyst doesn’t end with the go-live of an MES system. They continue to monitor the system’s performance, gather feedback from users, and identify opportunities for optimization. This ongoing involvement ensures that the MES continues to deliver value over time, adapting to the changing needs of the business.

Conclusion

The hype surrounding MES implementation is often justified—when done right, an MES can transform manufacturing operations and deliver substantial ROI. The difference between a successful implementation and a disappointing one often comes down to the involvement of skilled functional analysts. By ensuring that the MES aligns with business needs, integrates smoothly, and is embraced by users, functional analysts play a critical role in realizing the full potential of MES.

Applying Automated Unit Testing to MES

Sat, 15 Jun 2024 00:00:00 Z

Automated unit testing has long been a staple in software development, providing a reliable method for ensuring code quality and stability. However, its application to Manufacturing Execution System (MES) projects presents unique challenges. The real-time data requirements of MES systems make it difficult to structure meaningful and effective tests, as these systems often depend on live inputs that are not easily replicated in a test environment. Additionally, many MES platforms lack the built-in support or compatibility needed to host and leverage automated unit testing frameworks, further complicating efforts to implement such practices. Finally, MES configurators, who are typically more focused on system configuration and integration than on traditional software development practices, often lack the knowledge or experience necessary to design and execute automated unit tests, leading to a gap in the testing strategies employed within MES projects.

However, considering automated testing strategies in MES initiatives is crucial due to the high stakes involved in coordinating manufacturing operations. MES serves as the backbone of production environments, ensuring that processes run smoothly and efficiently. Any changes or improvements made to these systems, if not properly tested, could lead to significant disruptions in production, potentially causing costly delays, quality issues, or even complete production stoppages. Automated testing allows for the rapid verification of changes, ensuring that new configurations or updates do not negatively impact production. This ability to quickly and reliably test system modifications is essential for maintaining continuity and stability in the manufacturing process, where even minor issues can have drastic consequences on output and overall operational efficiency. By implementing automated testing, organizations can reduce the risk of unintended production impacts, ensuring that their MES continues to function optimally as the system evolves.

MES vendors are gradually beginning to embrace the importance of automated testing functionality, recognizing its value in maintaining system integrity during continuous improvement efforts. Platforms like Critical Manufacturing have taken the lead by incorporating inherent support for automated unit testing, making it easier for the team to implement and manage these testing strategies directly within the system. Other platforms, such as Parsec TrakSys, may not offer native support for automated testing, but they allow for the integration of backend software development modules that can host and run automated testing frameworks. This flexibility enables organizations to tailor their testing approach to suit their specific MES environment, ensuring that the system remains robust and reliable as it adapts to evolving production needs. As more vendors integrate such capabilities, the adoption of automated testing in MES projects is likely to increase, further safeguarding production processes from the risks associated with system changes.

In the case of TrakSys, RoviSys has implemented an automated testing harness, leveraging both the APIs exposed by TrakSys and the MSTest framework provided with Microsoft .NET to develop automated unit tests. The ability of the TrakSys platform to host native Microsoft .NET code enables this harness.

One of the key challenges of automating testing within an MES platform is ensuring consistent process data is contained within the data store. For example, a known process order, in-progress run or batch, specific machine state, quality test results, and various other entity values all may need to be established, which can be a tedious undertaking when done manually. Additionally, with traditional manual testing, once an entity is seeded and a test executed this entity can no longer be leveraged again because the system state has changed. A PO may have been completed and thus cannot be leveraged again when testing how the system handles pending PO activation for example.

The RoviSys test harness allows system state to be established at the beginning of the automated test via the usage of interface calls that wrap the entities, then the test harness 'tears down' this state at the conclusion of the automated test. An interface call can be made within the test to establish PO number '32456' with a status of 'Pending', then remove the PO at the end of the test, allowing that same PO to be re-seeded if the automated test is repeated.

The test harness further allows specific system operations to be performed using the established system state and then allows results to be verified. For example, maybe the goal of the test is to ensure that upon activation of a PO, a batch is established with an initial quantity of zero, and the target quantity is written to an output parameter. Leveraging the automated testing framework, the PO number with a specific target quantity can be established with a status of pending, calls can be made to activate the PO, and the resulting batch number and output parameter values can be queried and verified. At the end, all this data is removed, leaving the system in the same state that it was in prior to test execution.

Via the MSTest framework, unit tests can be executed in bulk and results seen at a glance. During deployment exercises (such as a CI / CD pipeline), a battery of unit tests can be quickly executed that confirms no breaking changes were introduced, streamlining manual testing processes that may take hours or even days to complete, or worse are simply not performed due to time constraints.

Usage of automated unit testing enables the technical team to create enterprise-level MES solutions that reduce the risk of undue production impacts. It is a consideration we make during every MES initiative as part of our DxExecution offering.

Embracing CI/CD in Manufacturing: Accelerating Digital Transformation on the Shop Floor

Mon, 20 May 2024 12:00:00 Z

Embracing CI/CD in Manufacturing: Accelerating Digital Transformation on the Shop Floor

Overview

CI/CD (continuous integration and continuous delivery/deployment) can significantly enhance manufacturing software deployments by speeding up implementation, testing, and deployment. Despite the benefits, adoption in manufacturing has lagged due to traditional practices and the unique challenges of the shop floor. Modernizing MES platforms with CI/CD principles and architectures like containerization and microservices can overcome these hurdles, reducing downtime and improving reliability. Continue reading for a more in depth look at CI/CD in manufacturing.

Bridging the Gap: CI/CD in Manufacturing Software Deployments

CI/CD is a concept very familiar to business software developers but still largely foreign to shop floor digitalization initiatives. Let's explore what CI/CD means, why its adoption in manufacturing software deployments has lagged, and how applying CI/CD principles has enormous potential to speed up implementation, testing, and deployment in manufacturing environments.

Understanding CI/CD

CI/CD can be divided into two aspects. CI (continuous integration) involves automatically and frequently integrating code changes into a shared source code repository. As updates are made, automated testing steps are executed to ensure the reliability of merged code changes.

Continuous delivery refers to the automation of releasing validated code as a production-ready build, allowing the operations team to quickly deploy an application to production. Continuous deployment takes this a step further, automating the release of changes to production, where the changes are immediately accessible to end users.

Adoption of CI/CD allows a team of multiple developers to work in parallel, reduces the likelihood of introducing bugs that break the production system, and streamlines the deployment of large enterprise software applications. So, why has manufacturing software lagged in adopting these benefits?

Challenges in Manufacturing Software Deployment

Traditionally, deploying a manufacturing software application involves installing a platform (such as a monolithic manufacturing execution system or MES), configuring it based on the site's physical layout and operation, performing factory and/or user acceptance testing, and then going live in production. Many companies establish one central environment per site to ease management complexity and reduce infrastructure costs but often neglect the challenges of incorporating future changes or enhancements and testing those directly in production without unforeseen impacts.

Additionally, the personnel responsible for configuring and managing the MES tend to be more process or shop floor-centric rather than software-centric. These resources are not software developers and are far removed from modern software management best practices.

MES implementations possess connectivity to a wide array of shop floor and external systems. Testing a system 'live' in production may be viewed as the only way of synchronizing all the data handoffs required.

The Limitations of Traditional MES Approaches

MES applications historically limit options for integrating CI/CD practices. Configuration and testing must be performed manually, automation of configuration or deployment tasks is often non-existent, and testing scenarios must be tediously staged and manually executed.

A move toward a development/QA/production infrastructure is a step in the right direction that many manufacturing operations have taken. Configuration is performed in a development environment or 'sandbox', migrated to a QA environment for factory/user acceptance testing and integration testing, and once confirmed, migrated to production. This architecture minimizes the risk of production impact due to bad configuration or a patch/release that introduces unforeseen issues, albeit at the expense of resource and infrastructure overhead. However, human error in duplicating manual configuration and deployment steps across environments often still leads to production issues. Companies struggle to ensure that QA and production are mirrors of each other, potentially negating testing efforts.

Modernizing MES with CI/CD

Modernizing MES software platforms with CI/CD practices greatly enhances efficiency and reliability. Many MES platforms are shifting towards containerized, microservice-based architectures, enabling independent deployment, starting, stopping, and upgrading of modules. This reduces the risk of a single bug affecting the entire system. Automation with infrastructure-as-code methods further minimizes human error in deployments across development, QA, and production environments.

Traditional deployment required significant downtime or manual fallback processes, but containerization supports zero downtime deployments by allowing seamless module swaps. Cloud-based environments support 24/7 operations, eliminating the need for physical infrastructure upgrades and streamlining deployments.

MES vendors are also improving configuration management with CI/CD principles. They offer global templates for consistent configuration across facilities, and file-based configurations allow for versioning, isolation, comparison, and merging using traditional software tools. Automated unit testing frameworks ensure configuration changes do not introduce issues, and any problems can be quickly isolated and resolved using versioned change histories.

Looking Ahead

Some may view the incorporation of these practices as introducing unnecessary complexity, which may be true for a simplistic, pilot initiative. However, as organizations continue to move toward adopting shop floor digitalization in a mission-critical, enterprise capacity, the ability of the selected technology stack to promote rather than hinder CI/CD practices is essential. This ensures quality, uptime, and the system's ability to grow to fulfill new use cases and solve new manufacturing challenges in the years to come. When evaluating platforms and associated service providers, it is crucial to ask how they promote modern enterprise software management principles as part of platform deployment, including the use of CI/CD.

In summary, embracing CI/CD in manufacturing is not just a technical upgrade; it's a strategic move towards a more agile, reliable, and future-ready operation.

MES - Why RoviSys is Different

Fri, 19 Apr 2024 12:00:00 Z

MES - Why RoviSys is Different

RoviSys has been involved in MES and digitalization initiatives since our founding in 1989. While we have had strong successes in the MES space during that time, different project teams took various approaches to MES-centric projects, leading to inconsistency and frequent reinvention. To combat this challenge, in 2019 we established a dedicated Center of Excellence (CoE) to consolidate our varied MES knowledge and expertise, ensuring that MES projects are defined, implemented, and deployed in a consistent, efficient, high-quality manner using standard tools and practices. This CoE has dedicated resources and is supported globally with RoviSys technical resources.

Since 2019, our CoE has played a role in the execution of 600+ opportunities consisting of 365K+ engineering hours across various vertical markets. RoviSys has executed large enterprise MES programs requiring thousands of hours as well as small support/enhancement projects.

As an independent integrator, RoviSys regularly evaluates MES technology trends and the various platform options, allowing us to 'right-fit' MES technology to solve our customer's pain points and provide return on investment, rather than leading with specific technology options. Vendor partnerships are based upon solution merit rather than hidden sales agendas.

Our proven Agile for Manufacturing process allows for the establishment and continuous refinement of project scope throughout the lifecycle of the digitalization initiative. It addresses key deficiencies of both purely agile and purely waterfall execution methodologies. Projects executed in a purely agile manner often lack overall goals, clear scope boundaries, and a comprehensive project roadmap. As a result, these projects often have an unclear definition of completion, exhibit cost overruns, and lead to unfulfilled customer expectations. Alternatively, projects executed in a waterfall manner have very rigid scope boundaries and have little room for course correction as the project progresses. Additionally, these projects require thorough functional requirement and detailed design definition up-front, which is often impractical and can lead to weak or incomplete design deliverables that are poorly understood by the customer at the time review is requested.

The Agile for Manufacturing process flow consists of three primary phases: Assessment, Spend Allocation, and Execution. RoviSys leverages a standardized assessment process to baseline our customer's operations and current KPIs, solicit feedback from key stakeholders, analyze potential technical solutions, and roadmap implementation logistics. With a culture based in control system engineering, RoviSys fosters MES up from the factory floor rather than down from the IT space, unlike numerous other competing technology consultants. Based on the results of the assessment, budgetary refinement is conducted and contrasted with the expected ROI of the solution.

Scope refinement occurs throughout the process as high-level goals are translated to detailed technical tasks to be executed. During execution of solution implementation, in-progress build process reviews are conducted at frequent intervals to ensure that stakeholders understand and are aligned with the functionality being implemented. This forum allows feedback to be captured and course corrections to be made while there is still room in the project budget and schedule to do so.

The most important measure of an MES initiative's success is that operations has embraced the delivered solution, and it is being leveraged to provide a positive impact to plant performance. As a result of this, we place great importance on organizational change management (OCM), ensuring that both the value statement of the solution and means of leveraging the solution are well understood across various customer stakeholder groups. We take steps early in the process and throughout the project's execution to keep OCM at top of mind. These include identification of 'expert users' who can participate in observation of the build and test of the solution and champion the solution to their peers. Proper business process scenario definition, training considerations, and project deployment planning are also considered early in the project's lifecycle rather than as an afterthought.

Additionally, RoviSys has embraced modern development tools and techniques to allow for the deployment of enterprise-wide MES architectures efficiently and with minimal quality control impact. These include usage of CI/CD (continuous integration and continuous deployment) principles such as automated unit testing, infrastructure as code, and automated development -> test -> production deployment pipelines to ensure early identification of bugs and consistent site deployments, in turn reducing opportunities for human error.

All our projects possess a strong project management component. A project manager is staffed on every project engagement who is responsible for ensuring the project's budget, schedule, and deliverables adhere to the agreed upon project plan. Our project managers utilize established RoviSys project management standards, ensuring that all projects adhere to our expected level of project delivery quality. Standard cost tracking, project organization, and project status reporting tools and templates are also leveraged. As Azure DevOps is leveraged for implementation by the internal team, RoviSys project managers are familiar with DevOps and using it to track day-to-day tasks, sprint velocity, and sprint burndown rates.

If our customer has preferred templates or tracking tools, RoviSys is willing to evaluate these to see if they can be made to fit within our Project Management approach. We are well accustomed to adapting our proven procedures to meet customer-specific practices.

Additionally, RoviSys places a strong emphasis on program governance and customer satisfaction. We lead periodic governance calls with our customers, attended by our project responsible management, the customers, and often the platform vendor's representatives as well. This call discusses key risks & issues, current project progress, and the status of future phases/initiatives. RoviSys leverages dedicated customer success personnel to serve in a customer advocate role and employ periodic feedback loops such as NPS (net promotor score) surveys to ensure we are meeting or exceeding our customer's expectations.

Rather than employ disconnected help desks or call centers, our design and development teams ultimately support the solution throughout deployment and 'Hypercare' sustainment periods, with extended support contracts available to ensure that an individual knowledgeable in the specific MES implementation is at-the-ready to quickly resolve issues, reducing downtime and further increasing the value of the solution and of RoviSys as a services partner.

At RoviSys, we distinguish ourselves in the digitalization and MES solutions space through our unique approach, extensive experience, and unwavering dedication to quality. We have continually demonstrated our commitment to improving and refining MES projects. Having successfully executed hundreds of projects, established a dedicated Center of Excellence, and nurtured a pool of highly skilled technical resources, we have a unique working ethos that sets us apart. As an independent integrator, our primary focus is on providing the right solutions to meet your specific needs and thus ensuring your success. Our Agile for Manufacturing process guarantees adaptable, efficient, and customer-centric project implementation, while our robust project management component guarantees quality and timely delivery. Unlike other technology consultants, our very business culture promotes growing MES from the factory floor upward. Given our commitment to customer satisfaction, program governance, and delivering quality service, we can assure a significant improvement in plant performance. Connect with our expert team at RoviSys to explore how we can revolutionize your manufacturing operations.

Streamlining Functional Definition - The SIPOC Approach

Wed, 20 Mar 2024 12:00:00 Z

Streamlining Functional Definition - The SIPOC Approach

Adoption of the SIPOC methodology has transformed customer engagement and driven project success while respecting time and budget constraints.

It is important to have some basis of scope when initiating a digitalization initiative so that the manner in which it will be leveraged to enact positive change and thus the value it brings is well understood by all involved. An unclear value proposition will likely lead to assumptions, unmet expectations, last-minute changes, and poor solution acceptance - in short, an unhappy customer. Projects executed in a purely agile manner often lack overall goals, clear scope boundaries, and a comprehensive project roadmap. As a result, these projects have an unclear definition of completion, exhibit cost overruns, and lead to unfulfilled customer expectations.

Historically, the common approach when starting a new implementation initiative was to create documentation up-front describing the solution to be built. This entailed creation of a user requirements specification (URS), functional requirements specification (FRS), and detailed design specification (DDS). And, it always tended to be a struggle getting these documents authored and reviewed, for the following reasons:

The delineation between the content to be put in the URS vs. FRS is often unclear, which leads to repetition and/or gaps.
It is extremely challenging to plan out all the specific functions to be provided by the solution up-front. Seeing certain functions implemented in the application will naturally spark ideas, suggestions, or corrections of misconceptions. It is hard for the customer to sign off on a screen mockup or description of an interface without sufficient understanding of what processes it enables and how it will actually be used day-to-day.
Defining a detailed design around uncertain functional requirements up front proves even more difficult. Implementations often morph to leverage new ideas and react to realizations that occur while implementations are in-flight. For example, maybe two stored procedures can be rolled into one generic one that covers multiple screens, or an additional REST API call is actually needed that was not originally anticipated.
Even worse, the team may compromise and create a functional design specification (FDS). This provides a high-level description of the functionality provided by the solution and the design of the solution to enable the functionality, poorly conveying both aspects.
Customers feel that they have one chance to get everything they need into these documents, or else the solution will be locked in and it will be a battle making further changes. As a result, the review cycles are lengthy and overall progress on the initiative is delayed.

Once this documentation is created, it tends to be lengthy and difficult to comprehend. The user cannot visualize how the solution actually looks and feels. Non-technical reviewers will not understand the technical aspects, and technical reviewers may not understand or care about the functional 'look and feel' aspects. Redlines and comments are numerous simply because clarification is needed. Or, the key customer stakeholders do not even bother to review the documentation. When it is time for go-live, even though the specifications were approved, the solution does not meet expectations because the specifications were not fully understood, were incomplete, or were not even read.

Further, the documents become stale soon after implementation commences as the implementation team often deviates from the specifications (with good intentions) but fail to revise them to reflect the as-built solution. By the end, the specifications only loosely represent what was actually delivered and are of little value to anyone.

We find that the most critical aspect of the initiative for customer stakeholders to understand up-front are the business process scenarios in which the solution will be leveraged to facilitate day-to-day operations. If stakeholders can visualize how the solution will integrate into their work processes to provide benefit, the specific details as to how exactly it will look, feel, and function can be sorted out throughout the agile sprint execution process. Well formulated business process scenarios achieve the following goals:

Be easily understood by non-technical stakeholders
Be documented in an efficient, repeatable manner
Be technology agnostic. The business process scenario should refer to various business systems at a high level (MES, ERP, LIMS, control system, etc.), but not delve into the nuances of applying a specific platform or technical solution, as this will be confusing to non-technical reviewers
Establish 'guardrails' concerning the solution to be provided, so that the intended processes to be facilitated by the solution are clear, reducing the possibility of future scope creep

Both typical (sunny day) and exception (rainy day) scenarios should be captured

Provide a basis upon which more detailed user stories can be built. User stories should be matrixed to business process scenarios so that the goal and reasoning for each user story is clear
Highlight required user-to-system and system-to-system interactions, which can be leveraged when building more detailed technical documentation (architecture diagrams, value stream maps, etc.)

The RoviSys MES center of excellence has adopted the 'SIPOC' methodology for the definition of business process scenarios. This is an industry standard methodology that has been adapted to better serve the needs of our MES project initiatives.

A SIPOC document captures the following aspects of the business process scenario:

S = Process suppliers

I = Process inputs

P = The process steps / details

O = Process outputs

C = Process consumers

It's important that SIPOCs be hierarchical in nature, and support drill-down into more specific activities. The highest-level SIPOC in a manufacturing facility represents the overall conversion of raw materials as input to finished goods as output. Various sub-processes needed to facilitate this, such as scheduling, raw material receiving, quality control, warehousing, etc. all derive from this highest-level SIPOC in some manner. SIPOCs must also be able to be chained together, as the outputs of a given SIPOC are often inputs to another. We have built standard MS PowerPoint based templates that ease initial SIPOC layout, ensuring these are defined in a consistent manner regardless of customer.

Our customers have been very receptive to the SIPOC documentation methodology. Non-technical stakeholders easily understand how the MES fits into the overall processes within the enterprise, and interactions between the MES and people / external systems, without having to review lengthy technical interface specifications. They can also easily review the documents with their wider teams. If a change or correction needs to be made, the SIPOC diagrams are more easily edited than a lengthy Word document.

Technical stakeholders have a better understanding of the various interfaces that will be required to support process input and output communication, serving as a basis for more detailed interface definitions, swim lane diagrams, architecture diagrams, and other technical collateral.

Our customers are engaged and eager to work with us to define and review these important deliverables. This eagerness up front translates to a far more successful overall project engagement, with the customer ultimately receiving a solution that better delivers upon the goals of the initiative, while also adhering to time and budgetary constraints.

Digital Transformation Is Difficult

Mon, 12 Feb 2024 12:00:00 Z

Digital transformation, especially in the manufacturing environment, is difficult.

That doesn’t mean that it's not worth the effort (jump ahead to learn more about how we overcome these challenges for our most innovative customers). Every day, organizations are realizing benefits through digital transformation that lead to faster and better decision making as well as more agile and adaptable operations.

Manufacturers face a distinctive set of challenges when compared to sectors such as finance, retail, energy, and healthcare, where substantial successes can often be observed. While these industries generally gain benefits where data drives decisions that can be made from behind a desk, the big opportunities in the manufacturing sector tend to be from people-centric process changes that involve physical manipulation of materials and goods to produce products. In terms of digital transformation, manufacturers must navigate a more challenging landscape where digital decision-making bridges hands-on, concrete operational changes.

From identifying the right business drivers to start with, to implementing solutions that work for the users, and establishing sustainment processes to drive continuous value, transformation is not as simple as many claim it to be. There are many factors to be considered to ensure your business needs are being met, followed by hard work to implement change and ensure adoption.

Steer clear of anyone peddling the notion that digitalization can be achieved through effortless shortcuts - a magic button approach, which glosses over foundational concerns. This is a far cry from reality. Sustainable transformation is an intricate process; it involves more than just buying a new tool and installing it in your facility. You simply can't buy optimization. It's up to your operations teams and your integration partner to choose, implement, and then use the right tools to affect the operations in order to see benefits. Technology innovations and theoretical constructs can help with implementation, but they will not help you identify and avoid the risks that many face when taking on these initiatives.

Tools are simply a means to facilitate process changes more effectively. They are there to be used, but they rarely "do the work for you". Take the age-old transformation analogy: the butterfly. While silk is a critical piece of the change process, it isn't the silk that's doing the work. The caterpillar has to do the work to spin the silk into their cocoon that actually enables nature's metamorphic process to work.

Fortunately for butterflies, the transformation process is encoded in their DNA. The people that operate manufacturing facilities are not so lucky. Given the choice, many would most likely not want to tackle a change, because new things surrounded by uncertainty can be scary. However, provided the right information--i.e., clear perspective to what will change, how it will affect and improve their work, and transparency in the steps and work it will take to get there, we find people are more willing, even eager, to take part in the change process.

This year, the Digital Transformation Advisors at RoviSys are introducing a comprehensive, scalable, packaged service offering to Accelerate Digital Transformation to the manufacturing market. Our advisory team has developed this offering by consolidating over 100 years of combined manufacturing digitalization experience, and all of the scars and learnings that come along with it. The offering focuses on tactical program management strategies to identify, coordinate, and mitigate risks that often interfere with successful digital operations solution implementations.

As a comprehensive offering, we’ve developed repeatable processes starting from the early stages of defining the potential value of digital transformation in manufacturing, to the complexities and challenges of solution implementation, all the way through to ensuring your operations are able to realize the potential value through effective use and continuous improvement.

As we continue to see manufacturers struggle to justify and succeed in their Digital Transformation goals, we anticipate high demand for this offering. We are looking to partner with manufacturers who are serious about change, pragmatic about the effort it will take, and are interested in improving their own metamorphic process. To secure time with our team to discuss your business objectives and learn more about our approach to addressing them, message or connect with me or my team on LinkedIn.

Digital Transformation (DTx) Advisors at RoviSys:

John Vargo – DTx Strategy & Vision - John Vargo | LinkedIn

Justin Vaught – Intelligent Manufacturing Analysis & Transformation - Justin Vaught | LinkedIn

Jeff Rericha – DTx Program Management - Jeff Rericha | LinkedIn

Keith Beaubien – Lean DTx Operations Consultancy - Keith Beaubien | LinkedIn

Jessica Buonopane – White Glove Organizational Change Management - Jessica Buonopane | LinkedIn

Josh Hilewick – Real-Time Process Control Digitalization - Joshua Hilewick | LinkedIn

Nathan Sender - Infrastructure and Industrial Digital Integration - Nathan Sender | LinkedIn

Bryan DeBois – Predictive Knowledge Digital Evolution - Bryan DeBois | LinkedIn

Importance of a Quality-Enabled MES

Mon, 15 Jan 2024 00:00:00 Z

Importance of a Quality-Enabled MES

An MES is often introduced to the shop floor to drive performance initiatives. Concepts such as OEE help provide insights that can be leveraged to reduce downtime and improve production output. However, the role of an MES in ensuring product quality may be overlooked. Manufacturers might instead look to isolated LIMS (laboratory information management systems) and/or LES (laboratory execution systems) to track product quality, or leverage more primitive means such as paper and spreadsheets. However, the MES can often be leveraged to fulfill quality-specific use cases in a more straightforward, integrated manner.

Knowing what to check and when to check it can be tribal knowledge - experienced operators know what to do to ‘fix the mix’ but checks may be overlooked or forgotten, and the results and corrections made are not documented. Expensive scrap or recall events are more likely, and continuous improvement initiatives are hindered as a result. The MES has both schedule and real-time production status visibility, including the product being produced, batch or cycle times, BOM / recipe requirements, and incoming material genealogy. This allows the MES to execute situational sample and test plans, ensuring that product is checked at the right time, the proper specifications are applied, and corrections are tracked, including additional materials added or production operations performed.
The MES is the front-line user interface on the shop floor, allowing operators to interact with a single consolidated view, reducing learning curves.
The MES can promote seamless electronic communication flows, allowing a lab to see when samples are due to be taken based upon actual production progress, and allowing operators to see testing results and specified corrections directly from their shop-floor screens. This increase in real-time communications can reduce the time taken to perform quality verifications, improving efficiency and leading to increased production output.
The MES can provide quality disposition and corrective action information to higher-level systems, such as the ERP, using interface conduits likely already established between the two layers.
Modern MES platforms can interface via a variety of conduits, often using low-code toolkits. This allows the MES to be connected directly to shop-floor or lab instrumentation.
Both shop-floor and lab quality checks can be driven by one engine, and the resulting data brought into one consistent data store, facilitating ease of data review, analytics, and other reporting aspects.
The ability to leverage a single software stack for both production and quality can reduce overall licensing costs, infrastructure requirements, and maintenance costs.
The MES is typically an enterprise application, allowing global specifications and sample plans to be configured that can be applied across all production facilities in a consistent manner. Historically, plants capture this information via a variety of means, such as PDF documents, Excel sheets, legacy systems, etc. This information may be out-of-date or inconsistent across the facilities. The MES allows this master data to be consistently configured and applied. While ERP systems can also be leveraged to define quality master data, the ERP layer may not have the granularity or flexibility to maintain nuanced sample plans required for complex manufacturing processes found in modern production facilities.

Quality is an often overlooked but extremely powerful component of a comprehensive MES rollout. When starting an MES journey or looking at where to go next, be sure that the voices of individuals responsible for quality are heard and strongly consider building sample and test functionality into your MES deployment roadmap.

Untangling the Acronyms: Understanding OEE and MES in Manufacturing

Mon, 04 Dec 2023 12:00:00 Z

Navigating the acronym matrix of our industry can be a confusing battle, but there are two that are commonly interchanged incorrectly: OEE (Overall Equipment Effectiveness) and MES (Manufacturing Execution System). Both acronyms stand for important, but distinct, concepts to boost productivity in the realm of digitalizing manufacturing operations.

Picture OEE as a tool within the larger toolbox that is your MES. OEE is a key metric for measuring how efficiently your equipment or processes are operating to produce quality products, using the formula:

OEE = Availability × Performance × Quality.

Here’s a quick overview on OEE:

Availability: Are your machines ready to go when needed? This consideration includes factoring in downtime due to maintenance, changeovers, and unexpected stops.

Performance: How does your machine’s output measure against its theoretical maximum? This takes into account factors like speed losses and minor stops.

Quality: Do your products meet set quality standards? This gauge takes defects, rework, and scrap into account.

MES, however, encompasses more than just OEE – it’s a robust software solution designed to manage, control and optimize various aspects of the manufacturing process. It acts as a bridge between your enterprise-level systems (like ERP) and the operations on your plant floor, connecting some of your most valuable equipment.

MES is about real-time monitoring, tracking and optimization of production operations. It wears many hats, such as:

Production Scheduling: MES helps manage the execution of production schedules, ensuring efficient allocation of resources to meet production targets.
Work Order Management: MES manages work orders, providing instructions to operators, tracking progress, and ensuring that operations are carried out correctly.
Inventory Management: MES keeps track of raw materials, components, and finished goods, ensuring accurate inventory levels and minimizing stockouts or excess inventory. MES also can track genealogy - what raw materials and resources were used to produce a certain finished good.
Quality Management: MES monitors and enforces quality control processes, collecting data about product quality, and ensuring that products meet quality standards.
Resource Tracking: MES tracks the utilization of resources such as equipment, labor, and materials, helping to identify bottlenecks and areas for improvement.
Additionally, some MES packages venture even farther, helping to manage maintenance operations by tracking equipment maintenance requirements, providing energy utilization metrics, tracking warehouse entry and release, as well as other aspects.

In a nutshell, OEE is a crucial measuring stick for individual equipment performance, while MES is a comprehensive software system that manages various aspects of the entire manufacturing process.

Remember, having OEE visibility helps, but it’s a starting point, not the finish. A solid strategy for interpreting and acting on OEE values is essential for true efficiency, and your MES platform is a great aid to formulate and follow through with these actions. MES as a whole provides the tools and software infrastructure to manage and optimize the entire manufacturing process, from planning to execution and quality control.

OEE and MES: two acronyms, two different roles, both essential to successful and efficient manufacturing.

How has using OEE and MES made a difference in your operations? What challenges have you faced, and how did you overcome them? Join the discussion in the comments!

Manufacturers are Refocusing on MES, and for Good Reasons

Wed, 01 Nov 2023 00:00:00 Z

Manufacturers are Refocusing on MES, and for Good Reasons

Over the last 10 years of my career, I've observed massive changes in the technologies and tactics that make up the Manufacturing Execution Systems (MES) and Manufacturing Operations Management (MOM) landscape. Of course, technology has advanced and changed rapidly. From the rise of industrial cloud computing, cyber security as a priority, secure and open-protocol communications, then edge computing and Industrial Internet of Things (IIoT), hundreds of new solutions have been developed that promise to solve manufacturing operations challenges. With the emergence of Industry 4.0 and the convergence of traditional white-space IT with shop-floor Operational Technology (OT), the changes are not only related to technology. Project owners were once mostly engineering teams but are now often the IT organizations, as they began to support the manufacturing floor. During this time, MES seemed to lose favor in the market. It would be difficult to recognize this transformed environment looking at it through a 2010 lens.

Of the organizations that evaluated the new concepts, some tested the waters with small projects or technology pilots. A few bold organizations embraced change and rolled out solutions across their manufacturing network. Teams that succeeded typically achieved visibility and control over manufacturing performance, and a few are now able to pivot to changing market demands and supply chain constraints.

While success stories are out there, there were plenty of scary stories. Trade events and conferences included sessions focused on the risks, including troubled pilots, costly and duplicated investments, scalability challenges, and poor adoption. To me, the open sharing of this real-world perspective marked the beginning of a notable shift from the preliminary hype to more realistic views of the cutting edge solutions. Catchy ads surrounding Industry 4.0 and Digital Manufacturing that held the attention of prime time viewers quickly faded away. Software vendors reinvested to refresh core platforms and legacy products, while incorporating cloud, IIoT and other technologies to enable new capabilities.

Throughout all of this, the industrial and manufacturing challenges have remained steady. Availability of assets and resources, efficiency of production, and quality of the process continue to be fundamental metrics and drivers for operational excellence. Perhaps the urgency has increased as the risks of a retiring labor force draw closer and organizations with integrated supply chain information raise competitive pressures. But the fact that goods need to be produced at the shop-floor means that manufacturing data is a key component to making better decisions on both sides of the supply chain.

So, what will happen next?  I think of it as the revival of MES.  This shift is characterized in two main ways: a realization of the new technology limitations and the recognition of the fundamental benefits of MES/MOM.

First, the factors I believe are driving the realization that the technology innovations are only a piece of digital transformation:

No silver bullets. Companies recognize that IoT and cloud are not magic. Those who still do not have reliable networking and basic electronic data collection, and many who have tried to short cut this step and stumbled are now making smart investments here first, while realizing benefits of improved manufacturing visibility.

Impractical user experiences and dependencies. Augmented reality currently relies on costly headgear or taking up an extra hand with a tablet.  Advanced analytics, ML and AI typically require large, pre-existing, and clean data sets for all but the most common of use cases.  IIoT sensors and instrumentation still need a reliable and secure network to talk to the cloud and have not yet matured to measure enough manufacturing and process variables to displace traditional shop-floor instrumentation.

Long-term platform limitations. IIoT has spawned many companies offering niche applications that address specific and complex use cases with short ROI periods. However, once the benefit is realized, what do you do next? If a solution is bespoke to a limited set of operational challenges, you risk customizing it beyond its capabilities, or searching for other solutions for your next initiative. This could lead to maintenance costs of the individual solutions outweighing the ongoing benefit.

Limited out-of-the-box capability. On the other end, platforms providing wide-open, build-your-own toolkits can lead to roadblocks. Although initial use cases can realize value quickly, scaling the platforms to the next use cases often requires more investment than the incremental enhancements that traditional platforms enable as part of standard features.

These factors have led manufacturers to refocus on the second driver of the revival of MES: the recognition of the fundamental value of managing shop floor execution, and the benefits it offers long-term.

MES is defined for Manufacturing. MES solutions have proven value propositions and are often able to extend beyond initial intention to address broader operational challenges. MES platforms have gained a stigma of being heavy and overweight. While this may be true in cases, there are increasingly more nimble offerings with broader built-in capability challenging this paradigm.

MES enables analytics. MES Solutions inherently generate context. The more integrated the solution is with shop floor machine and process data, the better the associations. Machine learning models love context, so this step is an investment toward applying ML and AI.

MES feeds the digital transformation cycle. MES records production counts and waste, detects and categorizes asset deficiencies and downtimes, captures performance against schedule, integrates quality with production records--all effectively in real-time. These are all critical data points for understanding capacity and constraints. When integrated with the appropriate business systems, digitally connected supply chain strategies can finally become a reality.

The manufacturing systems technology space has seen remarkable change. As manufacturers explored new technologies, some achieved success early, while others encountered challenges. A shift in perspective amongst manufacturers and vendors triggered a transition from hyped promise to practical value propositions. Organizations began to see cloud and IIoT as tools to increase the potential value of traditional MES and MOM software platforms rather than wholesale replace them. As manufacturers continue to pursue Industry 4.0 initiatives, there has been a refocus back to the fundamentals of shop-floor manufacturing execution systems because they not only solve operational challenges, they enable advanced analytics and supply chain management strategies. The next decade will likely bring additional changes at an even faster pace, but my bet is that MES will be there to keep manufacturers going strong.