Monday, December 20, 2010
It is no wonder that MES solutions are typically the last ones to be implemented in the typical manufacturing solution landscape. It is simply too hard to provide a clear and concise return or benefit from an MES alone or at least to justify the investment – and MESs do not come cheap. On the other hand it is obviously much easier when there is a specific and typically catastrophic event that needs to be remedied, such as a recall, 483 (FDA warning letter), regulatory compliance, detrimental quality issues, etc.
MES need to be thought of as enablers for operational excellence where the ROI and benefit come from the “Whole” solution and not the system. For example more efficient process, better quality, effective material management, etc. The ROI and/or benefits have to then be attributed to The Whole Solution – focus on the solution rather than the System (i.e. MES).
Tuesday, December 7, 2010
Tuesday, November 23, 2010
My colleague Carsten Holm Pedersen held a talk on the synergies between systems and operational excellence. The main theme of his talk was what he called “The 4 Myths” about manufacturing information systems or as I refer to them as “The 4 Misunderstanding” about Manufacturing System implementations. I really liked his message so I wanted to share it here.
Sole focus on ROI ensures success because it defines qualitative business goals and sets a defined scope. However this also means that focus is diverted to “easy wins” rather than usable solutions and enhancement that have obvious value are ignored or rejected as “scope creep”. Furthermore there is risk that synergies from process improvement and other OpEx initiatives are not incorporated or supported by the system.
Use of Standard Systems
Application of standard systems is more effective and guarantees use of “Best Practices”. They reduce risk and provide superior maintainability. The reality is that these so-called “Best Practices” are not necessarily a good fit to your process and sometimes they are not “best” at all, but simply a result of “that is the way we have always done it” thinking. As such they sometimes do not provide the flexibility or adaptability to specific processes and force unnecessary constraints. Focus is diverted to “What we can buy” rather than “What we need”.
Competitive approaches increase productivity
Employing a competitive approach where different projects are competing for the same funds motivates and steers project teams to achieve better results. In fact just the contrary is true, this approach only ensures sub-optimization. It inhibits collaboration and does not leverage the inherent need for systems to be built to support the process. Systems are built to provide specific point solutions and not enable a streamlined lean manufacturing process or superior process understanding.
Integration should be avoided.
Interoperability between systems is not that important and if it is implemented has to be in real time. On the contrary one of the inherent attributes of Manufacturing Systems is interoperability with all levels in the manufacturing process. Not including interoperability with other system may seriously inhibit the usability of a solution and some obvious benefits to process visibility may be ignored. Also each interface may have different “real-time” requirements that have to be evaluated by needs and value.
There is obviously much more to these than what I can put in this post so let me know what you think and make sure to follow Carsten for more discussion on these topics.
Tuesday, November 2, 2010
Most definitions of Manufacturing System are focused on describing a solution, or more precisely the functionality and architecture of a Manufacturing System solution. For example the MESA model presents number of functional categories from a business perspective, where as the ISA-95 (S-95) model provides a solution architecture based on functional decomposition. All these are of course relevant and useful yet it seems that the problem only interesting to academia – try to Google it. It is assumed that we in industry all know what it is – a dangerous proposition to have.
We all agree that the key to a successful deployment of a Manufacturing System is the understanding of the problem that it is designed to solve. This obviously not a novel approach – it is what everybody attempts to do with the system’s requirement or URS. Yet my experience shows that even in the requirement phase many resort to using the existing models, thus reverting to describe the problem with the solution itself. Quite confusing isn’t it?
So here is my take on what a Manufacturing System is, or in other words the Shop Floor Management Problem. I like to describe it as the problem of integrating 3 important flows in a manufacturing organization. The 2 vertical flows provide Product and Logistical information while the horizontal flow is the physical flow of material, equipment and people.
The Shop Floor Management problem is therefore: How to make use of the information provided by the Product and Logistical flow to efficiently and effectively manage the physical flow of Resources and Materials (also known as the production process). Simple isn’t it - that is what a Manufacturing System is designed to do. Try to imagine a seasoned and effective production supervisor or plant manager – the Shop Floor Management problem is very close to his real life job duties.
It is obviously not that simple and there is of course much more detail that is yet to be discussed. I plan to provide some of this in upcoming posts (hence this post is named Part I). Also this is not meant to take away from the importance and complexity of product development, process engineering, operations, and planning. It is a model that is focused on explaining the particulars of managing a shop floor (yes this is my disclaimer).
More detail to come in future posts…
Friday, October 15, 2010
Medical Devices is one of our core markets at NNE Pharmaplan and hence we are hoping to leverage this event to make ourselves better known in the industry. Kind of old school marketing but I am hoping that there is value there? I look forward to an interesting week and getting to meet some interesting companies and people. Also last time I have been to DC is in 1995 so I am long due. If you are around give me a shout.
Monday, September 27, 2010
Friday, September 17, 2010
Thursday, September 16, 2010
Next week I will be at the CBI MES conference in
I also look forward to the conference because I have never been to
Friday, September 10, 2010
- Value stream: We all know that value is identified by the specific needs of the customer hence the Manufacturing System should be usable and implementable to support only these specific processes that add value. In other words the system once implemented should not require or be constrained to use extra processes or involves extra steps if they are not directly part of the value flow.
- Implement flow: The Manufacturing System should employ a value centric process model that is easily managed and accessible to all the relevant people. This will allow a transparent view of the value flow and thus allow engineers and operators to ensure production flow, be it a one-piece flow, supermarkets, or other relevant Lean solutions.
- Execute Pull: This is kind of the obvious requirement that involves the enablement of pull execution and dispatching of WIP. This may include features and functionality to enable or enforce flow and managing kanbans, supermarkets, balancing, etc.
- Enable Perfection: Enable perfection by providing the production and process visibility needed for the continuous improvement efforts. This is the part of the system that provides Intelligence (a topic that I have written a few relevant posts about). In addition the Manufacturing System should provide adequate configurability, extendibility and customizability that support continuous improvement.
Wednesday, September 1, 2010
I help people and companies in the pharmaceutical and biotechnology industry that produce medicine, drugs and tools for doctors with their computer systems. The use computers to make sure that their products have no defects, as wells as to make sure that they produce their products exactly the way the recipes instruct. The computer systems save and maintain all the information during the production so that it can be used to analyze what happened if there is a defect, or how to improve the production process. The computers also help automate some of the steps in the process.
Friday, August 20, 2010
Monday, August 16, 2010
Tuesday, May 11, 2010
The presentation shares our experiences from the current global MES rollout project at Novo Nordisk. This is an ongoing long term multi faceted project that involves a staggered deployment of a commercial MES software package to all of Novo Nordisk’s manufacturing sites.
Deploying a new manufacturing system is a complex and risky proposition for any company, rolling out such a system to multiple sites on a global scale may be even considered scary. In order to mitigate the risks and manage the complexity of this immense undertaking Novo Nordisk makes the best use of people and technology to evolve a best practice approach that is continually improved upon. This approach includes technical and organizational aspects that cover the complete life cycle of the manufacturing system’s deployment. In addition the “out-of-the-box” feature set of the software obviously did not suffice and navigating this predicament, coined as "Customize or Compromise", is another interesting topic.
Novo Nordisk is a global healthcare company with 87 years of innovation and leadership in diabetes care, haemophilia care, growth hormone therapy, and hormone replacement therapy. It has international production facilities and employs more than 29,300 employees in 76 countries.
Thursday, March 25, 2010
- For specific scenarios there may exists one or more solution approaches using available OOTB features. This is the postive scenario - in such cases we are good to go.
- For specific scenarios the OOTB feature set may not provide a solution approach. In other words an OOB solution does not exist and hence a customization may be required. the question here becomes: "Can we live with out this?"
- For specific scenarios the OOTB feature set may be able to provide a solution approach but it is constrained or lacking. In such cases a decision has to be made to compromise or customize.
Tuesday, February 23, 2010
Henri Poincare once noted in a related topic that “Science is facts; just as houses are made of stones, so is science made of facts; but a pile of stones is not a house and a collection of facts is not necessarily science.”
Wednesday, February 17, 2010
“…contrary to popular belief, companies that announce layoffs do not enjoy higher stock prices than peers—either immediately or over time.”It is an interesting read for everybody, obviously for them that have been laid-off but also for the people doing the lay offs.
I think that the story behind the story is once again the topic of management and leadership. I strongly believe that in any situation it is always about people. That means that it is the people (managers) and their way of running a company that is the root-cause here. I have said before that you manage processes but you have to lead people. When you just manage people then they become an assets and when hard times are upon us, cutting costs by reducing your capital makes sense – right? Well no – isn’t that obvious - Apparently not?
“In the face of management actions that signal that companies don't value employees, virtually every human-resource consulting firm reports high levels of employee disengagement and distrust of management.”
“Layoffs are more like bloodletting, weakening the entire organism. That's because of the vicious cycle that typically unfolds. A company cuts people. Customer service, innovation, and productivity fall in the face of a smaller and demoralized workforce. The company loses more ground, does more layoffs, and the cycle continues.”This reminds me of one of Dr. Demmings most commonly used quotes:
"Running a company on visible figures alone is one of the seven deadly diseases of management."In this case it is financial metrics. It seems that in a recession most management executives are thinking of short term financial metrics rather than the long term health of their company? I am sure that these managers do not intend to do this and that they probably believe that they are doing the right thing. However it is this focus on managing rather than leading that is the problem. Managing the company’s business (The process) is more important than leading the people (organization). The end of the quarter's bottom line is more important than long term viability. Although this seem to be common practice, there is ample proof of companies that thrive by doing differently. Yes, by simply motivating and empowering their people. That is what makes them great companies, and also immensely profitable I may add
We are driven by this need to satisfy investors, whom I may add are also typically about short term gain. It seems that everything revolves around the need to make money now - the typical sales man approach, which is to pick up the closest shiniest pennies rather than to look ahead and possibly see a pot of gold on the horizon. Even if there is not one there at least you looked, and people appreciate that – do not underestimate what that means?
Monday, February 15, 2010
I think the best way to frame this up is to tell the story of a persona in a simple scenario. Let’s consider Patrick Process Engineer who is trying to understand yield fluctuations specifically and maybe the yield’s behaviour in general. He is perplexed about why he cannot accurately predict yield given that most of the processes are “in control” (yes, another one of these myths about processes). What he really is striving for is an understanding the process and the best way to investigate it – in other words analyze the process.
Obviously Patrick will be looking at the Yield metric(s) and once he sees some fluctuation he will embark on an analysis. Typically he will perform what I call a high-level analysis, which is kind of a “look-around” in the data and maybe other related metrics to determine patterns. But wait, why patterns. Well whether we like it or not when we analyze processes we naturally look for patterns since that is what complex processes really exhibit. I guess I need to write a bit more about the complex adaptive behavior of manufacturing systems, but let me leave that for a future post. For now let’s just say that the patterns really tell us about the dependencies between the different metrics and parameters in the system.
OK, once Patrick has performed is “high-level” analysis he may then start digging a bit deeper in to some of the areas that may lead him to the root-cause of the fluctuation. He may perform some more detailed analysis, maybe choose to monitor some specific metrics, define some additional more detail or focused metrics. If he really is trying some advanced analysis he may try and observe dependencies between metrics for a period of time. That means monitor maybe a few metrics and how they change in relation to each other.
What is described here is really a simple scenario of human behavior exhibited when we perform troubleshooting. Although this as simple behavior for us, when we think about the data and data structures that we need to support what Patrick is trying to do, we may quickly realize that the complexity abounds. Modern business intelligence concepts such as multidimensional analysis, OLAP, and practices for data aggregation provide the tools. However it takes a lot of work and process knowledge to transform the base process data to such information structures.
This I believe is the main challenge in modern manufacturing systems. Compounding this problem is that effective analysis needs to use information from all the host of system that may reside in a manufacturing business, i.e. ERP, MES, Automation, Historians, LIMS and others. Most manufacturing intelligence tools that are in the market today simply do not address this simple scenario. If we do our inbound marketing work correctly and draw up the scenarios above, with Patrick our main persona, the problem definition is straightforward; however the engineering task required to solve it is not.
Friday, February 12, 2010
What makes a house sell? I have been pondering this question, obviously since I am trying to sell my home. How do you get into the minds of the people that may be potential buyers? There are of course the standard things that the real estate agent tells you to do such as the de-cluttering, remove personal objects, make it clean and tidy, price, the signs, etc. But when you walk into a home what is it that makes one like or dislike this home?
I wish I could get into the minds of these buyers, but as a seller you get no exposure to the real people that visit your home when it is cleaner than it has ever been. They leave no trace, no scent, and no feedback. Maybe I should consider some hidden cameras? Maybe ask them to fill out a questionnaire before they leave – right!
My only method of understanding my potential buyers is by asking others within my network; what is it that made them buy the house they currently own? So this is it, my plea to all - please let me know who my buyer persona is?
Monday, February 8, 2010
I was reading an article in National Geographic Blog about counting jelly beans that in a way boiled down what my general belief about metrics (see also another relevant post about metrics). Also, I have lately been involved in MESA’s metrics working group and all of this had me thinking…
The current practice in regards to metrics in operational environments especially in manufacturing is the typical engineering tactic - we need to break down the complexity of the system and figure out what metrics we need. Well one approach is to take a look at what other companies are doing – as in MESA paper we try to figure out if there are any best practices. But is this the right approach for any company or for you? I say no! Metrics are a way to represent patterns in the complex systems that enhance our understanding of its dynamics. We can look at one metric and say we are doing good or bad, which works well if you are a computer since we can take a decision based on this metric. Yet unlike computers, we humans are much better at using our knowledge and understanding to detect patterns and react to them. So if you give us a set of metrics that help us interpret what the system is doing then we do much better. That is exactly what the term "Actionable Intelligence" means.
There are a few important factors that I believe are important:
- A few metrics used independently are never going to give you the true picture of what is going on.
- Simply copying what other companies are doing will not work either, since metrics should be driven by what you are trying to achieve – and that changes with time.
- The Accuracy of the metrics are not necessarily important. What! Yes, I just said it; accuracy is not that important. Let’s think about a jelly bean counting competition, you really don’t needs to know the exact number but be the one that is closest to the precise number, in order to win. Michael Schumacher (if you do not know, he was a 7 time Formula 1 GP winner) once said “… you don’t have to drive your fastest to win, but faster than the guy behind you”.
In a blog post Stephen Few states “most poor decisions are caused by lack of understanding, not lack of data”. This is exactly my point, we spend so much time working on detail. For example, how much the ocean water level will rise over the next period of time. Some say a few meters some say 30 meters in the next 100 years. But the point here is that even in a moderate scenario calculation; Venice, New Orleans and the SF Bay Area delta, among other places, will be under water. So if you live there – guess what? You are in trouble, regardless of accuracy.
Friday, February 5, 2010
It has been a very long while since I have posted anything on this blog. Hopefully this will change – starting right now.
I have just started a new job with NNE Pharmaplan and it looks like a very exciting opportunity. If you did not know NNE Pharmaplan is an engineering consultancy firm focusing on the Life Science industry. The company is quite large and also well known in Europe. With renewed focus on North America I will be responsible for helping Life Science customers with their Manufacturing Systems efforts.
This new opportunity is taking me back to my core expertise – Manufacturing Systems (I don’t like to call it MES – Manufacturing Execution Systems because of narrow and misleading perceptions, but more on this in a later post). That being said I still plan to spend time on new media marketing and hopefully help with some new ideas at NNE Pharmaplan.
So watch this space for some interesting discussions and opinions…