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I am writing this post because one of my PLM peers recently asked me this question: “Is the BOM losing its position? He was in discussion with another colleague who told him:
“If you own the BOM, you own the Product Lifecycle”.
This statement made me think of ä recent post from Jan Bosch recent post: Product Development fallacy #8: the bill of materials has the highest priority.
Software becomes increasingly an essential part of the final product, and combined with Jan’s expertise in software development, he wrote this article. I recommend reading the full post (4 min read) and next browse through the comments.
If you cannot afford these 10 minutes, here is my favorite quote from the article:
An excessive focus on the bill of materials leads to significant challenges for companies that are undergoing a digital transformation and adopting continuous value delivery. The lack of headroom, high coupling and versioning hell may easily cause an explosion of R&D expenditure over time.
Where did the BOM focus come from? A historical overview related to the rise (and fall) of the BOM.
In the beginning, there was the drawing.
Before the era of computers, there was “THE drawing”, describing assemblies, subassemblies or parts. And on the drawing, you can find the parts list if relevant. This parts list was the first Bill of Material, describing the parts/materials shown on the drawing.
Next came MRP/ERP
With the introduction of the MRP system (Material Requirement Planning), it was the first step that by using computers, people could collect the material requirements for one system as data and process. Entering new materials/parts described on drawings was still a manual process, as well as referring to existing parts on the drawing. Reuse of parts was a manual process based on individual knowledge.
In the nineties, MRP evolved into ERP (Enterprise Resource Planning), which included the MRP part and added resource and manufacturing planning and financial reporting.
The ERP system became the most significant IT system, the execution system of the company. As it was the first enterprise system implemented, it was the first moment we learned about implementation challenges – people change and budget overruns. However, as the ERP system brought visibility to the company’s execution, it became a “must-have” system for management.
The introduction of mainstream 2D CAD did not affect the company’s culture so much. Drawings became electronic drawings, and the methodology of the parts list on the drawing remained.
Sometimes the interaction with the MRP/ERP system was enhanced by an interface – sending the drawing BOM to ERP. The advantage of the interface: no manual transfer of data reducing typos and BOM errors. The disadvantages at that time: relatively expensive (connectivity between systems was a challenge) and mostly one direction.
And then there was PDM.
In parallel with the introduction of ERP systems, mainstream 3D CAD systems became affordable, particularly SolidWorks, Solid Edge and Inventor. These 3D CAD systems allow sharing of parts and assemblies in different products, and the PDM database was the first aid to support part reuse, versioning and standardization.
By extracting the parts from the assemblies and subassemblies, it was possible to generate a BOM structure in the PDM system to be transferred or typed into the ERP system. We did not talk about EBOM or MBOM then, as there was only one BOM in the ERP system, and the PDM system was a tool to feed the ERP system.
Many companies still have based their processes on this approach. ERP (read SAP nowadays) is the central execution system, and PDM is an external system. You might remember the story and image from my previous post about people, processes and tools. The bad practice example: Asking the ERP system to provide a part number when starting to design a part.
And then products started to change.
In the early 2000s, I worked with SmarTeam to define the E&E (Electronics and Electrical) template. One of the new concepts was to synchronize all design data coming from different disciplines to a single BOM structure.
It was the time we started to talk about the EBOM. A type of BOM, as the structure to consolidate all the design data, was based on parts.
The EBOM, most of the time, reflects the design intent in logical groups and sending the relevant parts in the correct order to the ERP system was a favorite expensive customization for service providers. How to transfer an engineering BOM view to an ERP system that only understands the manufacturing view?
Note: not all ERP systems have the data model to differentiate between engineering parts and manufacturing parts
The image below illustrates the challenge and the customer’s perception. 
The automated link between the design side (EBOM) and manufacturing side (MBOM) was a mission impossible – too many exceptions for the (spaghetti) code.
And then came the MBOM.
The identified issues connecting PDM and ERP led to the concept of implementing the MBOM in the PLM system. The MBOM in PLM is one of the characteristics of a PLM implementation compared to a PDM implementation. In a traditional PLM system, there is an interaction and connection between the EBOM and MBOM. EBOM parts should end up as MBOM parts. This interaction can be supported by automation, however, as it is in the same system, still leaving manual changes possible.
The MBOM structure in PLM could then be the information structure to transfer to the ERP system; however, there is more, as Jörg W. Fischer wrote in his provoking post-Die MBOM muss weg (The MBOM must go). He rightly points out (in German) that the MBOM is not a structure on its own but a combination of different views based on Assembly Drawings, Process Planning and Material Requirements.
His conclusion:
Calling these structures, MBOM is trying to squeeze all three structures into one. That usually doesn’t work and then leads to much more emotional discussions in the project. It also costs a lot of money. It is, therefore, better not to use the term MBOM at all.
And indeed, just having an MBOM in your PLM system might help you to prepare some of the manufacturing steps, the needed resources and parts. The MBOM result still has to be localized at the local plant where the manufacturing takes place. And here, the systems used are the ERP system and the MES system.
The main advantage of having the MBOM in the PLM system is the direct relation between specification and manufacturing intent, allowing manufacturing engineering to work collaboratively with engineering in the same environment.
- The first benefit is fewer iterations and a shorter time to production, thanks to early interaction and manufacturing involvement in the engineering process.
- The second benefit is: product knowledge is centralized in a single system. Consolidating your Product Knowledge in ERP does not make sense due to global localization and the missing capabilities to manage the iterative engineering processes on non-existing parts.
And then came the SBOM, the xBOM
Traditional PLM vendors and implementations kept using xBOM structures as placeholders for related specification data (mechanical designs, electrical, software deliverables, serialized products). Most of the time, related files.
And with this approach, talking about digital thread, PLM systems also touch on the concepts of Configuration Management.
I will not go into the details here but look at the two images by clicking on them and see a similar mindset.
It is about the traceability of information in structures and systems. These structures work well in a relatively static and linear product development and delivery environment, as illustrated below:
Engineering change and release processes are based on managing the changes in different structures from the left to the right.
And then came software!
Modern connected products are no longer mechanical products. The product’s functionality no longer depends on the mechanical properties but mainly on embedded electronics and software used. For example, look at the mechanical design of a telecom transmission tower – its behavior merely comes from non-mechanical components, and they can change over time. Still, the Bill of Material contains a lot of concrete and steel parts.
The ultimate example is comparing a Tesla (software on wheels) with a traditional car. For modern connected products, electronics and software need to be part of the solution. Software and electronics allow the product to be upgraded over time. Managing these products in the same manner as mechanical products is impossible, inefficient and therefore threatening your company’s future business.
I requote Jan Bosch:
An excessive focus on the bill of materials leads to significant challenges for companies that are undergoing a digital transformation and adopting continuous value delivery. The lack of headroom, high coupling and versioning hell may easily cause an explosion of R&D expenditure over time.
The model-based, connected enterprise
I will not solve the puzzle of the future in this post. You can read my observations in my series: The road to model-based and connected PLM. We need a new infrastructure with at least two modes. One that still serves as a System of Record, storing information in a traditional manner, like a Bill of Materials for the static parts, as not everyone and everything can be connected.
In addition, we need various Systems of Engagement that enable close to real-time interaction between products (systems) and relevant stakeholders for the engagement scope(multidisciplinary / consumers).
Digital twins are examples of such environments. Currently, these Systems of Engagement often work disconnected from the System of Record due to the lack of understanding of how to connect. (standard connectors? / OSLC?)
Our mission is to explore, as I wrote in my post Time to split PLM and drop our mechanical mindset.
And while I was finalizing this post, I read a motivating post from Jan Bosch again for all of you working on understanding and pushing the digital transformation in your eco-system.
The title: Be the protagonist of your life: 15 rules A starting point for more to come.
Conclusion
The BOM is no longer the master of the product lifecycle when it comes to managing connected products, where functionality mainly depends on software. BOM structures with related documents are just one of the extracted baselines from a data-driven, connected enterprise. This traditional PLM infrastructure requires other, non-BOM-driven structures to represent the actual status of a virtual or physical product.
The BOM is not dead, but there is more ………
Your thoughts?
Those who have read my blog posts over the years will have seen the image to the left.
The people, processes and tools slogan points to the best practice of implementing (PLM and CM) systems.
Theoretically, a PLM implementation will move smoothly if the company first agrees on the desired processes and people involved before a system implementation using the right tools.
Too often, companies start from their historical landscape (the tools – starting with a vendor selection) and then try to figure out the optimal usage of their systems. The best example of this approach is the interaction between PDM(PLM) and ERP.
PDM and ERP
Historically ERP was the first enterprise system that most companies implemented. For product development, there was the PDM system, an engineering tool, and for execution, there was the ERP system. Since ERP focuses on the company’s execution, the system became the management’s favorite.
The ERP system and its information were needed to run and control the company. Unfortunately, this approach has introduced the idea that the ERP system should also be the source of the part information, as it was often the first enterprise system for a company. The PDM system was often considered an engineering tool only. And when we talk about a PLM system, who really implements PLM as an enterprise system or was it still an engineering tool?
This is an example of Tools, Processes, and People – A BAD PRACTICE.
Imagine an engineer who wants to introduce a new part needed for a product to deliver. In many companies at the beginning of this century, even before starting the exercise, the engineer had to request a part number from the ERP system. This is implementation complexity #1.
Next, the engineer starts developing versions of the part based on the requirements. Ultimately the engineer might come to the conclusion this part will never be implemented. The reserved part number in ERP has been wasted – what to do?
It sounds weird, but this was a reality in discussions on this topic until ten years ago.
Next, as the ERP system could only deal with 7 digits, what about part number reuse? In conclusion, it is a considerable risk that reused part numbers can lead to errors. With the introduction of the PLM systems, there was the opportunity to bridge the gap between engineering and manufacturing. Now it is clear for most companies that the engineer should create the initial part number.
Only when the conceptual part becomes approved to be used for the realization of the product, an exchange with the ERP system will be needed. Using the same part number or not, we do not care if we can map both identifiers between these environments and have traceability.
It took almost 10 years from PDM to PLM until companies agreed on this approach, and I am curious about your company’s status.
Meanwhile, in the PLM world, we have evolved on this topic. The part and the BOM are no longer simple entities. Instead, we often differentiate between EBOM and MBOM, and the parts in those BOMs are not necessarily the same.
In this context, I like Prof. Dr. Jörg W. Fischer‘s framing:
EBOM is the specification, and MBOM is the realization.
(Leider schreibt Er viel auf Deutsch).
An interesting discussion initiated by Jörg last week was again about the interaction between PLM and ERP. The article is an excellent example of how potentially mainstream enterprises are thinking. PLM = Siemens, ERP = SAP – an illustration of the “tools first” mindset before the ideal process is defined.
There was nothing wrong with that in the early days, as connectivity between different systems was difficult and expensive. Therefore people with a 20 year of experience might still rely on their systems infrastructure instead of data flow.
But enough about the bad practice – let’s go to people, processes, (data), and Tools
People, Processes, Data and Tools?
I got inspired by this topic, seeing this post two weeks ago from Juha Korpela, claiming:
Okay, so maybe a hot take, maybe not, but: the old “People, Process, Technology” trinity is one of the most harmful thinking patterns you can have. It leaves out a key element: Data.
His full post was quite focused on data, and I liked the ” wrapping post” from Dr. Nicolas Figay here, putting things more in perspective from his point of view. The reply made me think about how this discussion fits into the PLM digital transformation discussion. How would it work in the two major themes I use to explain the digital transformation in the PLM landscape?
For incidental readers of my blog, these are the two major themes I am using:
- From Coordinated to Connected, based on the famous diagram from Marc Halpern (image below). The coordinated approach based on documents (files) requires a particular timing (processes) and context (Bills of Information) – it is the traditional and current PLM approach for most companies. On the other hand, the Connected approach is based on connected datasets (here, we talk about data – not files). These connected datasets are available in different contexts, in real-time, to be used by all kinds of applications, particularly modeling applications. Read about it in the series: The road to model-based and connected PLM.
. - The need to split PLM, thinking in System(s) of Record and Systems of Engagement. (example below) The idea behind this split is driven by the observation that companies need various Systems of Record for configuration management, change management, compliance and realization. These activities sound like traditional PLM targets and could still be done in these systems. New in the discussion is the System of Engagement which focuses on a specific value stream in a digitally connected manner. Here data is essential.I discussed the coexistence of these two approaches in my post Time to Split PLM. A post on LinkedIn with many discussions and reshares illustrating the topic is hot. And I am happy to discuss “split PLM architectures” with all of you.
These two concepts discuss the processes and the tools, but what about the people? Here I came to a conclusion to complete the story, we have to imagine three kinds of people. And this will not be new. We have the creators of data, the controllers of data and the consumers of data. Let’s zoom in on their specifics.
A new representation?
I am looking for a new simplifaction of the people, processes, and tools trinity combined with data; I got inspired by the work Don Farr did at Boeing, where he worked on a new visual representation for the model-based enterprise. You might have seen the image on the left before – click on it to see it in detail.
I wrote the first time about this new representation in my post: The weekend after CIMdata Roadmap / PDT Europe 2018
Related to Configuration Management, Martijn Dullaart and Martin Haket have also worked on a diagram with their peers to depict the scope of CM and Impact Analysis. The image leads to the post with my favorite quote: Communication is merely an exchange of information, but connections tell the story.
Below I share my first attempt to combine the people, process and tools trinity with the concepts of document and data, system(s) of record and system(s) of engagement. Trying to build the story. Look if you recognize the aspects of the discussion above, and feel free to develop enhancements.
I look forward to your suggestions. Like the understanding that we have to split PLM thinking, as it impacts how we look at implementations.
Conclusion
Digital transformation in the PLM domain is forcing us to think differently. There will still be processes based on people collecting, interpreting and combining information. However, there will also be a new domain of connected data interpreted by models and algorithms, not necessarily depending on processes.
Therefore we need to work on new representations that can be used to tell this combined story. What do you think? How can we improve?
Yes, it is not a typo. Clayton Christensen famous book written in 1995 discussed the Innovator’s Dilemma when new technologies cause great firms to fail. This was the challenge two decades ago. Existing prominent companies could become obsolete quickly as they were bypassed by new technologies.
The examples are well known. To mention a few: DEC (Digital Equipment Corporation), Kodak, and Nokia.
Why the innovation dilemma?
This decade the challenge has become different. All companies are forced to become more sustainable in the next ten years. Either pushed by global regulations or because of their customer demands. The challenge is this time different. Besides the priority of reducing greenhouse gas emissions, there is also the need to transform our society from a linear, continuous growth economy into a circular doughnut economy.
The circular economy makes the creation, the usage and the reuse of our products more complex as the challenge is to reduce the need for raw materials and avoid landfills.
The circular economy concept – the regular product lifecycle in the middle
The doughnut economy makes the values of an economy more complex as it is not only about money and growth, human and environmental factors should also be considered.
Doughnut Economics: Trying to stay within the green boundaries
To manage this complexity, I wrote SYSTEMS THINKING – a must-have skill in the 21st century, focusing on the logical part of the brain. In my follow-up post, Systems Thinking: a second thought, I looked at the human challenge. Our brain is not rational and wants to think fast to solve direct threats. Therefore, we have to overcome our old brains to make progress.
An interesting and thought-provoking was shared by Nina Dar in this discussion, sharing the video below. The 17 Sustainability Development Goals (SDGs) describe what needs to be done. However, we also need the Inner Development Goals (IDGs) and the human side to connect. Watch the movie:
Our society needs to change and innovate; however, we cannot. The Innovation Dilemma.The future is data-driven and digital.
What is clear to me is that companies developing products and services have only one way to move forward: becoming data-driven and digital.
Why data-driven and digital?
Let’s look at something companies might already practice, REACH (Registration, Evaluation, Authorization and Restriction of Chemicals). This European directive, introduced in 2007, had the aim to protect human health and protect the environment by communicating information on chemicals up and down the supply chain. This would ensure that manufacturers, importers, and their customers are aware of information relating to the health and safety of the products supplied.
The regulation is currently still suffering in execution as most of the reporting and evaluation of chemicals is done manually. Suppliers report their chemicals in documents, and companies report the total of chemicals in their summary reports. Then, finally, authorities have to go through these reports.
Where the scale of REACH is limited, the manual effort to have end-to-end reporting is relatively high. In addition, skilled workers are needed to do the job because reporting is done in a document-based manner.
Life Cycle Assessments (LCA)
Where you might think REACH is relatively simple, the real new challenges for companies are the need to perform Life Cycle Assessments for their products. In a Life Cycle Assessment. The Wiki definition of LCA says:
Life cycle assessment or LCA (also known as life cycle analysis) is a methodology for assessing environmental impacts associated with all the stages of the life cycle of a commercial product, process, or service. For instance, in the case of a manufactured product, environmental impacts are assessed from raw material extraction and processing (cradle), through the product’s manufacture, distribution and use, to the recycling or final disposal of the materials composing it (grave)
This will be a shift in the way companies need to define products. Much more thinking and analysis are required in the early design phases. Before committing to a physical solution, engineers and manufacturing engineers need to simulate and calculate the impact of their design decisions in the virtual world.
This is where the digital twin of the design and the digital twin of the manufacturing process becomes relevant. And remember: Digital Twins do not run on documents – you need connected data and various types of models to calculate and estimate the environmental impact.
LCA done in a document-based manner will make your company too slow and expensive.
I described this needed transformation in my series from last year: The road to model-based and connected PLM – nine posts exploring the technology and concept of a model-based, data-driven PLM infrastructure.
Digital Product Passport (DPP)
The European Commission has published an action plan for the circular economy, one of the most important building blocks of the European Green Deal. One of the defined measures is the gradual introduction of a Digital Product Passport (DPP). As the quality of an LCA depends on the quality and trustworthy information about products and materials, the DPP is targeting to ensure circular economy metrics become reliable.
This will be a long journey. If you want to catch a glimpse of the complexity, read this Medium article: The digital product passport and its technical implementation related to the DPP for batteries.
The innovation dilemma
Suppose you agree with my conclusion that companies need to change their current product or service development into a data-driven and model-based manner. In that case, the question will come up: where to start?
Becoming data-driven and model-based, of course, is not the business driver. However, this change is needed to be able to perform Life Cycle Assessments and comply with current and future regulations by remaining competitive.
A document-driven approach is a dead-end.
Now let’s look at the real dilemmas by comparing a startup (clean sheet / no legacy) and an existing enterprise (experience with the past/legacy). Is there a winning approach?
The Startup
Having lived in Israel – the nation where almost everyone is a startup – and working with startups afterward in the past 10 years, I always get inspired by these people’s energy in startup companies. They have a unique value proposition most of the time, and they want to be visible on the market as soon as possible.
This approach is the opposite of systems thinking. It is often a very linear process to deliver this value proposition without exploring the side effects of such an approach.
For example, the new “green” transportation hype. Many cities now have been flooded with “green” scooters and electric bikes to promote transportation as a service. The idea behind this concept is that citizens do not require to own polluting motorbikes or cars anymore, and transportation means will be shared. Therefore, the city will be cleaner and greener.
However, these “green” vehicles are often designed in the traditional linear way. Is there a repair plan or a plan to recycle the batteries? Reuse of materials used.? Most of the time, not. Please, if you have examples contradicting my observations, let me know. I like to hear good news.
When startup companies start to scale, they need experts to help them grow the company. Often these experts are seasoned people, perhaps close to retirement. They will share their experience and what they know best from the past: traditional linear thinking.
As a result, even though startup companies can start with a clean sheet, their focus on delivering the product or service blocks further thinking. Instead, the seasoned experts will drive the company towards ways of working they know from the past.
Out of curiosity: Do you know or work in a startup that has started with a data-driven and model-based vision from scratch? Please add the name of this company in the comments, and let’s learn how they did it.
The Existing company
Working in an established company is like being on board a big tanker. Changing its direction takes a clear eye on the target and navigation skills to come there. Unfortunately, most of the time, these changes take years as it is impossible to switch the PLM infrastructure and the people skills within a short time.
From the bimodal approach in 2015 to the hybrid approach for companies, inspired by this 2017 McKinsey article: Toward an integrated technology operating model, I discovered that this is probably the best approach to ensure a change will happen. In this approach – see image – the organization keeps running on its document-driven PLM infrastructure. This type of infrastructure becomes the system of record. Nothing different from what PLM currently is in most companies.
In parallel, you have to start with small groups of people who independently focus on a new product, a new service. Using the model-based approach, they work completely independently from the big enterprise in a data-driven approach. Their environment can be considered the future system of engagement.
The data-driven approach allows all disciplines to work in a connected, real-time manner. Mastering the new ways of working is usually the task of younger employees that are digital natives. These teams can be completed by experienced workers who behave as coaches. However, they will not work in the new environment; these coaches bring business knowledge to the team.
People cannot work in two modes, but organizations can. As you can see from the McKinsey chart, the digital teams will get bigger and more important for the core business over time. In parallel, when their data usage grows, more and more data integration will occur between the two operation modes. Therefore, the old PLM infrastructure can remain a System of Record and serve as a support backbone for the new systems of engagement.
The Innovation Dilemma conclusion
The upcoming ten years will push organizations to innovate their ways of working to become sustainable and competitive. As discussed before, they must learn to work in a data-driven, connected manner. Both startups and existing enterprises have challenges – they need to overcome the “thinking fast and acting slow” mindset. Do you see the change in your company?
Note: Before publishing this post, I read this interesting and complementary post from Jan Bosch Boost your digitalization: instrumentation.
It is in the air – grab it.
Image http://www.mdux.net
As promised in my early November post – The road to model-based and connected PLM (part 9 – CM), I come back with more thoughts and ideas related to the future of configuration management. Moving from document-driven ways of working to a data-driven and model-based approach fundamentally changes how you can communicate and work efficiently.
Let’s be clear: configuration management’s target is first of all about risk management. Ensuring your company’s business remains sustainable, efficient, and profitable.
By providing the appropriate change processes and guidance, configuration management either avoids costly mistakes and iterations during all phases of a product lifecycle or guarantees the quality of the product and information to ensure safety.
Companies that have not implemented CM practices probably have not observed these issues. Or they have not realized that the root cause of these issues is a lack of CM.
Similar to what is said in smaller companies related to PLM, CM is often seen as an overhead, as employees believe they thoroughly understand their products. In addition, CM is seen as a hurdle to innovation because of the standardization of practices. So yes, they think it is normal that there are sometimes problems. That’s life.
I already wrote about this topic in 2010 PLM, CM and ALM – not sexy 😦 – where ALM means Asset Lifecycle Management – my focus at that time.
Hear it from the experts
To shape the discussion related to the future of Configuration Management, I had a vivid discussion with three thought leaders in this field: Lisa Fenwick, Martijn Dullaart and Maxime Gravel. A short introduction of the three of them:
Lisa Fenwick, VP Product Development at CMstat, a leading company in Configuration Management and Data Management software solutions and consulting services for aviation, aerospace & defense, marine, and other high-tech industries. She has over 25 years of experience with CM and Deliverables Management, including both government and commercial environments.
Ms. Fenwick has achieved CMPIC SME, CMPIC CM Assessor, and CMII-C certifications. Her experience includes implementing CM software products, CM-related consulting and training, and participation in the SAE and IEEE standards development groups
Martijn Dullaart is the Lead Architect for Enterprise Configuration Management at ASML (Our Dutch national pride) and chairperson of the Industry 4.0 committee of the Institute Process Excellence (IPX) Congress. Martijn has his own blog mdux.net, and you might have seen him recently during the PLM Roadmap & PDT Fall conference in November – his thoughts about the CM future can be found on his blog here
Maxime Gravel, Manager Model-Based Engineering at Moog Inc., a worldwide designer, manufacturer, and integrator of advanced motion control products. Max has been the director of the model-based enterprise at the Institute for Process Excellence (IPX) and Head of Configuration and Change Management at Gulfstream Aerospace which certified the first aircraft in a 3D Model-Based Environment.
What we discussed:
We had an almost one-hour discussion related to the following points:
- The need for Enterprise Configuration Management – why and how
- The needed change from document-driven to model-based – the impact on methodology and tools
- The “neural network” of data – connecting CM to all other business domains, a similar view as from the PLM domain,
I kept from our discussion the importance of planning – as seen in the CMstat image on the left.
To plan which data you need to manage and how you will manage the data. How often are you doing this in your company’s projects?
Next, all participants stressed the importance of education and training on this topic – get educated. Configuration Management is not a topic that is taught at schools. Early next year, I will come back on education as the benefits of education are often underestimated. Not everything can be learned by “googling.”
Conclusion
The journey towards a model-based and data-driven future is not a quick one to be realized by new technologies. However, it is interesting to learn that the future of connected data (the “neural network”) allows organizations to implement both CM and PLM in a similar manner, using graph databases and automation. When executed at the enterprise level, the result will be that CM and PLM become natural practices instead of other siloed system-related disciplines.
Most of the methodology is there; the implementation to make it smooth and embedded in organizations will be the topics to learn. Join us in discussing and learning!
In March 2018, I started a series of blog posts related to model-based approaches. The first post was: Model-Based – an introduction. The reactions to these series of posts can be summarized in two bullets:
- Readers believed that the term model-based was focusing on the 3D CAD model. A logical association as PLM is often associated with 3D CAD-model data management (actually PDM), and in many companies, the 3D CAD model is (yet) not a major information carrier/
- Readers were telling me that a model-based approach is too far from their day-to-day life. I have to agree here. I was active in some advanced projects where the product’s behavior depends on a combination of hardware and software. However, most companies still work in a document-driven, siloed discipline manner merging all deliverables in a BOM.
More than 3 years later, I feel that model-based approaches have become more and more visible for companies. One of the primary reasons is that companies start to collaborate in the cloud and realize the differences between a coordinated and a connected manner.
Initiatives as Industry 4.0 or concepts like the Digital Twin demand a model-based approach. This post is a follow-up to my recent post, The Future of PLM.
History has shown that it is difficult for companies to change engineering concepts. So let’s first look back at how concepts slowly changed.
The age of paper drawings
In the sixties of the previous century, the drawing board was the primary “tool” to specify a mechanical product. The drawing on its own was often a masterpiece drawn on special paper, with perspectives, details, cross-sections.
All these details were needed to transfer the part or assembly information to manufacturing. The drawing set should contain all information as there were no computers.
Making a prototype was, depending on the complexity of the product, the interpretation of the drawings and manufacturability of a product, not always that easy. After a first release, further modifications to the product definition were often marked on the manufacturing drawings using a red pencil. Terms like blueprint and redlining come from the age of paper drawings.
There are still people talking nostalgically about these days as creating and interpreting drawings was an important skill. However, the inefficiencies with this approach were significant.
- First, updating drawings because there was redlining in manufacturing was often not done – too much work.
- Second, drawing reuse was almost impossible; you had to start from scratch.
- Third, and most importantly, you needed to be very skilled in interpreting a drawing set. In particular, when dealing with suppliers that might not have the same skillset and the knowledge of which drawing version was actual.
However, paper was and still is the cheapest neutral format to distribute designs. The last time I saw companies still working with paper drawings was at the end of the previous century.
Curious to learn if they are now extinct?
The age of electronic drawings (CAD)
With the introduction of AutoCAD and personal computers around 1982, more companies started to look into drafting with the computer. There was already the IBM drafting system in 1965, but it was Autodesk that pushed the 2D drafting business with their slogan:
“80 percent of the functionality for 20 percent of the price (Autodesk 1982)”
A little later, I started to work for an Autodesk distributor/reseller. People would come to the showroom to see how a computer drawing could be plotted in the finest quality at the end. But, of course, the original draftsman did not like the computer as the screen was too small.
However, the enormous value came from making changes, the easy way of sharing drawings and the ease of reuse. The picture on the left is me in 1989, demonstrating AutoCAD with a custom-defined tablet and PS/2 computer.
The introduction of electronic drawings was not a disruption, more optimization of the previous ways of working.
The exchange with suppliers and manufacturing could still be based on plotted drawings – the most neutral format. And thanks to the filename, there was better control of versions between all stakeholders.
Aren’t we all happy?
The introduction of mainstream 3D CAD
In 1995, 3D CAD became available for the mid-market, thanks to SolidWorks, Solid Edge and a little later Inventor. Before that working with 3D CAD was only possible for companies that could afford expensive graphic stations, provided by IBM, Silicon Graphics, DEC and SUN. Where are they nowadays? The PC is an example of disruptive innovation, purely based on technology. See Clayton Christensen’s famous book: The Innovator’s Dilemma.
The introduction of 3D CAD on PCs in the mid-market did not lead directly to new ways of working. Designing a product in 3D was much more efficient if you mastered the skills. 3D brought a better understanding of the product dimensions and shape, reducing the number of interpretation errors.
Still, (electronic) drawings were the contractual deliverable when interacting with suppliers and manufacturing. As students were more and more trained with the 3D CAD tools, the traditional art of the draftsman disappeared.
3D CAD introduced some new topics to solve.
- First of all, a 3D CAD Assembly in the system was a collection of separate files, subassemblies, parts, and drawings that relate to each other with a specific version. So how to ensure the final assembly drawings were based on the correct part revisions? Companies were solving this by either using intelligent filenames (with revisions) or by using a PDM system where the database of the PDM system managed all the relations and their status.
- The second point was that the 3D CAD assembly also introduced a new feature, the product structure, or the “Bill of Materials”. This logical structure of the assembly up resembled a lot of the Bill of Material of the product. You could even browse deeper levels, which was not the case in the traditional Bill of Material on a drawing.
Note: The concept of EBOM and MBOM was not known in most companies. People were talking about the BOM as a one-level definition of parts or subassemblies in the assembly. See my Where is the MBOM? Post from July 2008 when this topic was still under discussion.
- The third point that would have a more significant impact later is that parts and assemblies could be reused in other products. This introduced the complexity of configuration management. For example, a 3D CAD part or assembly file could contain several configurations where only one configuration would be valid for the given product. Managing this in the 3D CAD system lead to higher productivity of the designer, however downstream when it came to data management with PDM systems, it became a nightmare.
I experienced these issues a lot when discussing with companies and implementers, mainly the implementation of SmarTeam combined with SolidWorks and Inventor. Where to manage the configuration constraints? In the PDM system or inside the 3D CAD system.
These environments were not friends (image above), and even if they came from the same vendor, it felt like discussing with tribes.
The third point also covered another topic. So far, CAD had been the first step for the detailed design of a product. However, companies now had an existing Bill of Material in the system thanks to the PDM systems. It could be a Bill of Material of a sub-assembly that is used in many other products.
Configuring a product no longer started from CAD; it started from a Product or Bill of Material structure. Sales and Engineers identified the changes needed on the BoM, keeping as much as possible released information untouched. This led to a new best practice.
The item-centric approach
Around 2005, five years after introducing the term Product Lifecycle Management, slowly, a new approach became the standard. Product Lifecycle Management was initially introduced to connect engineering and manufacturing, driven by the automotive and aerospace industry.
It was with PLM that concepts as EBOM and MBOM became visible.
In particular, the EBOM was closely linked to engineering practices, i.e., modularity and reuse. The EBOM and its related information represented the product as it was specified. It is essential to realize that the parts in the EBOM could be generic specified purchase parts to be resolved when producing the product or that the EBOM contained Make-parts specified by drawings.
At that time, the EBOM was often used as the foundation for the ERP system – see image above. The BOM was restructured and organized according to the manufacturing process specifying materials and resources needed in the ERP system. Therefore, although it was an item-like structure, this BOM (the MBOM) always had a close relation to the Bill of Process.
For companies with a single manufacturing site, the notion of EBOM and MBOM was not that big, as the ERP system would be the source of the MBOM. However, the complexity came when companies have several manufacturing sites. That was when a generic MBOM in the PLM system made more sense to centralize all product information in a single system.
The EBOM-MBOM approach has become more and more a standard practice since 2010. As a result, even small and medium-sized enterprises realized a need to manage the EBOM and the MBOM.
There were two disadvantages introduced with this EBOM-MBOM approach.
- First, the EBOM and the MBOM as information structures require a lot of administrative maintenance if information needs to be always correct (and that is the CM target). Some try to simplify this by keeping the EBOM part the same as the MBOM part, meaning the EBOM specification already targets a single supplier or manufacturer.
- The second disadvantage of making every item in the BOM behave like a part creates inefficiencies in modern environments. Products are a mix of hardware(parts) and software(models/behavior). This BOM-centric view does not provide the proper infrastructure for a data-driven approach as part specifications are still done in drawings. We need 3D annotated models related to all kinds of other behavior and physical models to specify a product that contains hard-and software.
A new paradigm is needed to manage this mix efficiently, the enabling foundation for Industry 4.0 and efficient Digital Twins; there is a need for a model-based approach based on connected data elements.
More next week.
Conclusion
| The age of paper drawings | 1960 – now dead |
| The age of electronic drawings | 1982 – potentially dead in 2030 |
| The mainstream 3D CAD | 1995 – to be evolving through MBD and MBSE to the future – not dead shortly |
| Item-centric approach | 2005 – to be evolving to a connected model-based approach – not dead shortly |
Last summer, I wrote a series of blog posts grouped by the theme “Learning from the past to understand the future”. These posts took you through the early days of drawings and numbering practices towards what we currently consider the best practice: PLM BOM-centric backbone for product lifecycle information.
You can find an overview and links to these posts on the page Learning from the past.
If you have read these posts, or if you have gone yourself through this journey, you will realize that all steps were more or less done evolutionarily. There were no disruptions. Affordable 3D CAD systems, new internet paradigms (interactive internet), global connectivity and mobile devices all introduced new capabilities for the mainstream. As described in these posts, the new capabilities sometimes created friction with old practices. Probably the most popular topics are the whole Form-Fit-Function interpretation and the discussion related to meaningful part numbers.
What is changing?
In the last five to ten years, a lot of new technology has come into our lives. The majority of these technologies are related to dealing with data. Digital transformation in the PLM domain means moving from a file-based/document-centric approach to a data-driven approach.
A Bill of Material on the drawing has become an Excel-like table in a PLM system. However, an Excel file is still used to represent a Bill of Material in companies that have not implemented PLM.
Another example, the specification document has become a collection of individual requirements in a system. Each requirement is a data object with its own status and content. The specification becomes a report combining all valid requirement objects.
Related to CAD, the 2D drawing is no longer the deliverable as a document; the 3D CAD model with its annotated views becomes the information carrier for engineering and manufacturing.
And most important of all, traditional PLM methodologies have been based on a mechanical design and release process. Meanwhile, modern products are systems where the majority of capabilities are defined by software. Software has an entirely different configuration and lifecycle approach conflicting with a mechanical approach, which is too rigid for software.
The last two aspects, from 2D drawings to 3D Models and Mechanical products towards Systems (hardware and software), require new data management methods. In this environment, we need to learn to manage simulation models, behavior models, physics models and 3D models as connected as possible.
I wrote about these changes three years ago: Model-Based – an introduction, which led to a lot of misunderstanding (too advanced – too hypothetical).
I plan to revisit these topics in the upcoming months again to see what has changed over the past three years.
What will I discuss in the upcoming weeks?
My first focus is on participating and contributing to the upcoming PLM Roadmap & PDS spring 2021 conference. Here speakers will discuss the need for reshaping the PLM Value Equation due to new emerging technologies. A topic that contributes perfectly to the future of PLM series.
My contribution will focus on the fact that technology alone cannot disrupt the PLM domain. We also have to deal with legacy data and legacy ways of working.
Another post will focus on the difference between the digital thread and the digital thread. Yes, it looks like I am writing twice the same words. However, you will see based on its interpretation, one definition is hanging on the past, the other is targeting the future. Again here, the differentiation is crucial if the need for a maintainable Digital Twin is required.
Model-Based Systems Engineering (MBSE) in all its aspects needs to be discussed too. MBSE is crucial for defining complex products. Model-Based Systems Engineering is seen as a discipline to design products. Understanding data management related to MBSE will be the foundation for understanding data management in a Model-Based Enterprise. For example, how to deal with configuration management in the future?
Writing Learning from the past was an easy job as explaining with hindsight is so much easier if you have lived it through. I am curious and excited about the outcome of “The Future of PLM”. Writing about the future means you have digested the information coming to you, knowing that nobody has a clear blueprint for the future of PLM.
There are people and organizations are working on this topic more academically, for example read this post from Lionel Grealou related to the Place of PLM in the Digital Future. The challenge is that an academic future might be disrupted by unpredictable events, like COVID, or disruptive technologies combined with an opportunity to succeed. Therefore I believe, it will be a learning journey for all of us where we need to learn to give technology a business purpose. Business first – then technology.
No Conclusion
Normally I close my post with a conclusion. At this moment. there is no conclusion as the journey has just started. I look forward to debating and learning with practitioners in the field. Work together on methodology and concepts that work in a digital enterprise. Join me on this journey. I will start sharing my thoughts in the upcoming months
In the last two weeks, three events were leading to this post.
First, I read John Stark’s recent book Products2019. A must-read for anyone who wants to understand the full reach of product lifecycle related activities. See my recent post: Products2019, a must-read if you are new to PLM
Afterwards, I talked with John, discussing the lack of knowledge and teaching of PLM, not to be confused by PLM capabilities and features.
Second, I participated in an exciting PI DX USA 2020 event. Some of the sessions and most of the roundtables provided insights to me and, hopefully, many other participants. You can get an impression in the post: The Weekend after PI DX 2020 USA.
A small disappointment in that event was the closing session with six vendors, as I wrote. I know it is evident when you put a group of vendors in the arena, it will be about scoring points instead of finding alignment. Still, having criticism does not mean blaming, and I am always open to having a dialogue. For that reason, I am grateful for their sponsorship and contribution.
Oleg Shilovitsky mentioned cleverly that this statement is a contradiction.
“How can you accuse PLM vendors of having a limited view on PLM and thanking them for their contribution?”
I hope the above explanation says it all, combined with the fact that I grew up in a Dutch culture of not hiding friction, meanwhile being respectful to others.
We cannot simplify PLM by just a better tool or technology or by 3D for everybody. There are so many more people and processes related to product lifecycle management involved in this domain if you want a real conference, however many of them will not sponsor events.
It is well illustrated in John Stark’s book. Many disciplines are involved in the product lifecycle. Therefore, if you only focus on what you can do with your tool, it will lead to an incomplete understanding.
If your tool is a hammer, you hope to see nails everywhere around you to demonstrate your value
The thirds event was a LinkedIn post from John Stark – 16 groups needing Product Lifecycle Knowledge, which for me was a logical follow-up on the previous two events. I promised John to go through these 16 groups and provide my thoughts.
Please read his post first as I will not rewrite what has been said by John already.
CEOs and CTOs
John suggested that they should read his book, which might take more than eight hours. CEOs and CTOs, most of the time, do not read this type of book with so many details, so probably mission impossible.
They want to keep up with the significant trends and need to think about future business (model).
New digital and technical capabilities allow companies to move from a linear, coordinated business towards a resilient, connected business. This requires exploring future business models and working methods by experimenting in real-life, not Proof of Concept. Creating a learning culture and allowing experiments to fail is crucial, as you only learn by failing.
CDO, CIOs and Digital Transformation Executives
They are the crucial people to help the business to imagine what digital technologies can do. They should educate the board and the business teams about the power of having reliable, real-time data available for everyone connected. Instead of standardizing on systems and optimizing the siloes, they should assist and lead in new infrastructure for connected services, end-to-end flows delivered on connected platforms.
These concepts won’t be realized soon. However, doing nothing is a big risk, as the traditional business will decline in a competitive environment. Time to act.
Departmental Managers
These are the people that should worry about their job in the long term. Their current mission might be to optimize their department within its own Profit & Loss budget. The future is about optimizing the information flow for the whole value chain, including suppliers and customers.
I wrote about it in “The Middle Management Dilemma.” Departmental Managers should become more team leaders inspiring and supporting the team members instead of controlling the numbers.
Products Managers
This is a crucial role for the future, assuming a product manager is not only responsible for the marketing or development side of the product but also gets responsibility for understanding what happens with the product during production and sales performance. Understanding the full lifecycle performance and cost should be their mission, supported by a digital infrastructure.
Product Developers
They should read the book Products2019 to be aware there is so much related to their work. From this understanding, a product developer should ask the question:
“What can I do better to serve my internal and external customers ?”
This question will no arise in a hierarchical organization where people are controlled by managers that have a mission to optimize their silo. Product Developers should be trained and coached to operate in a broader context, which should be part of your company’s mission. Too many people complain about usability in their authoring and data management systems without having a holistic understanding of why you need change processes and configuration management.
Product Lifecycle Management (PLM) deployers
Here I have a little bit of the challenge that this might be read as PLM-system users. However, it should be clear that we mean here people using product data at any moment along the product lifecycle, not necessarily in a single system.
This is again related to your company’s management culture. In the ideal world, people work with a purpose and get informed on how their contribution fits the company’s strategy and execution.
Unfortunately, in most hierarchical organizations, the strategy and total overview get lost, and people become measured resources.
New Hires and others
John continues with five other groups within the organization. I will not comment on them, as the answers are similar to the ones above – it is about organization and culture.
Educators and Students
This topic is very close to my heart, and one of the reasons I continue blogging about PLM practices. There is not enough attention to product development methodology or processes. Engineers can get many years of education in specific domains, like product design principles, available tools and technologies, performing physical and logical simulations.
Not so much time is spent on educating current best practices, business models for product lifecycle management.
Check in your country how many vendor-independent methodology-oriented training you can find. Perhaps the only consistent organization I know is CIMdata, where the challenge is that they deliver training to companies after students have graduated. It would be great if education institutes would embed serious time for product lifecycle management topics in their curriculum. The challenge, of course, the time and budget needed to create materials and, coming next, prioritizing this topic on the overall agenda.
I am happy to participate to a Specialized Master education program aiming at the Products and Buildings Digital Engineering Manager (INGENUM). This program organized by Arts Et Metiers in France helps create the overview for understanding PLM and BIM – in the French language as before COVID-19 this was an on-site training course in Paris.
Hopefully, there are more institutes offering PLM eductation – feel free to add them in the comments of this post.
Consultants, Integrators and Software Company Employees
Of course, it would be nice if everyone in these groups understands the total flow and processes within an organization and how they relate to each other. Too often, I have seen experts in a specific domain, for example, a 3D CAD-system having no clue about revisioning, the relation of CAD to the BOM, or the fundamentals of configuration management.
Consultants, Integrators and Software Company Employees have their own challenges as their business model is often looking for specialized skills they can sell to their clients, where a broader and general knowledge will come from experience on-the-job.
And if you are three years working full-time on a single project or perhaps work in three projects, your broader knowledge does not grow fast. You might become the hammer that sees nails everywhere.
For that reason, I recommend everyone in my ecosystem to invest your personal time to read related topics of interest. Read LinkedIn-posts from others and learn to differentiate between marketing messages and people willing to share experiences. Don’t waste your time on the marketing messages and react and participate in the other discussions. A “Like” is not enough. Ask questions or add your insights.
In the context of my personal learning, I mentioned that I participated in the DigitalTwin-conference in the Netherlands this week. Unfortunately, due to the partial lockdown, mainly a virtual event.
I got several new insights that I will share with you soon. An event that illustrated Digital Twin as a buzzword might be hype, however several of the participants illustrated examples of where they applied or plan to apply Digital Twin concepts. A great touch with reality.
Another upcoming conference that will start next week in the PLM Roadmap 2020 – PDT conference. The theme: Digital Thread—the PLM Professionals’ Path to Delivering Innovation, Efficiency, and Quality is not a marketing theme as you can learn from the agenda. Step by step we are learning here from each other.
Conclusion
John Stark started with the question of who should need Product Lifecycle Knowledge. In general, Knowledge is power, and it does not come for free. Either by consultancy, reading or training. Related to Product Lifecycle Management, everyone must understand the bigger picture. For executives as they will need to steer the company in the right direction. For everyone else to streamline the company and enjoy working in a profitable environment where you contribute and can even inspire others.
An organization is like a human body; you cannot have individual cells or organs that optimize themselves only – we have a name for that disease. Want to learn more? Read this poem: Who should be the boss?
In the previous seven posts, learning from the past to understand the future, we have seen the evolution from manual 2D drawing handling. Next, the emerge of ERP and CAD followed by data management systems (PDM/PLM) and methodology (EBOM/MBOM) to create an infrastructure for product data from concept towards manufacturing.
Before discussing the extension to the SBOM-concept, I first want to discuss Engineering Change Management and Configuration Management.
ECM and CM – are they the same?
Often when you talk with people in my PLM bubble, the terms Change Management and Configuration Management are mixed or not well understood.
When talking about Change Management, we should clearly distinguish between OCM (Organizational Change Management) and ECM (Engineering Change Management). In this post, I will focus on Engineering Change Management (ECM).
When talking about Configuration Management also here we find two interpretations of it.
The first one is a methodology describing technically how, in your PLM/CAD-environment, you can build the most efficient way connected data structures, representing all product variations. This technology varies per PLM/CAD-vendor, and therefore I will not discuss it here. The other interpretation of Configuration Management is described on Wiki as follows:
Configuration management (CM) is a systems engineering process for establishing and maintaining consistency of a product’s performance, functional, and physical attributes with its requirements, design, and operational information throughout its life.
This is also the area where I will focus on this time.
And as-if great minds think alike and are synchronized, I was happy to see Martijn Dullaart’s recent blog post, referring to a poll and follow-up article on CM.
Here Martijn precisely touches the topic I address in this post. I recommend you to read his post: Configuration Management done right = Product-Centric first and then follow with the rest of this article.
Engineering Change Management
Initially, engineering change management was a departmental activity performed by engineering to manage the changes in a product’s definition. Other stakeholders are often consulted when preparing a change, which can be minor (affecting, for example, only engineering) or major (affecting engineering and manufacturing).
The way engineering change management has been implemented varies a lot. Over time companies all around the world have defined their change methodology, and there is a lot of commonality between these approaches. However, terminology as revision, version, major change, minor change all might vary.
I described the generic approach for engineering change processes in my blog post: ECR / ECO for Dummies from 2010.
The fact that companies have defined their own engineering change processes is not an issue when it works and is done manually. The real challenge came with PDM/PLM-systems that need to provide support for engineering change management.
Do you leave the methodology 100 % open, or do you provide business logic?
I have seen implementations where an engineer with a right-click could release an assembly without any constraints. Related drawings might not exist, parts in the assembly are not released, and more. To obtain a reliable engineering change management process, the company had to customize the PLM-system to its desired behavior.
An exercise excellent for a system integrator as there was always a discussion with end-users that do not want to be restricted in case of an emergency (“we will complete the definition later” / “too many clicks” / “do I have to approve 100 parts ?”). In many cases, the system integrator kept on customizing the system to adapt to all wishes. Often the engineering change methodology on paper was not complete or contained contradictions when trying to digitize the processes.
For that reason, the PLM-vendors that aim to provide Out-Of-The-Box solutions have been trying to predefine certain behaviors in their system. For example, you cannot release a part, when its specifications (drawings/documents) are not released. Or, you cannot update a released assembly without creating a new revision.
These rules speed-up the implementation; however, they require more OCM (Organizational Change Management) as probably naming and methodology has to change within the company. This is the continuous battle in PLM-implementations. In particular where the company has a strong legacy or lack of business understanding, when implementing PLM.
There is an excellent webcast in this context on Minerva PLM TV – How to Increase IT Project Success with Organizational Change Management.
Click on the image or link to watch this recording.
Configuration Management
When we talk about configuration management, we have to think about managing the consistency of product data along the whole product lifecycle, as we have seen from the Wiki-definition before.
Wiki – the configuration Activity Model
Configuration management existed long before we had IT-systems. Therefore, configuration management is more a collection of activities (see diagram above) to ensure the consistency of information is correct for any given product. Consistent during design, where requirements match product capabilities. Consistent with manufacturing, where the manufacturing process is based on the correct engineering specifications. And consistent with operations, meaning that we have the full definition of product in the field, the As-Built, in correct relation to its engineering and manufacturing definition.
Source: Configuration management in aerospace industry
This consistency is crucial for products where the cost of an error can have a massive impact on the manufacturer. The first industries that invested heavily in configuration management were the Aerospace and Defense industries. Configuration management is needed in these industries as the products are usually complex, and failure can have a fatal impact on the company. Combined with many regulatory constraints, managing the configuration of a product and the impact of changes is a discipline on its own.
Other industries have also introduced configuration management nowadays. The nuclear power industry and the pharmaceutical industry use configuration management as part of their regulatory compliance. The automotive industry requires configuration management partly for compliance, mainly driven by quality targets. An accident or a recall can be costly for a car manufacturer. Other manufacturing companies all have their own configuration management strategies, mainly depending on their own risk assessment. Configuration management is a pro-active discipline – it costs money – time, people and potential tools to implement it. In my experience, many of these companies try to do “some” configuration management, always hoping that a real disaster will not happen (or can happen). Proper configuration management allows you to perform reliable impact analysis for any change (image above)
What happens in the field?
When introducing PLM in mid-market companies, often, the dream was that with the new PLM-system configuration, management would be there too.
Management believes the tools will fix the issue.
Partly because configuration management deals with a structured approach on how to manage changes, there was always confusion with engineering change management. Modern PLM-systems all have an impact analysis capability. However, most of the time, this impact analysis only reaches the content that is in the PLM-system. Configuration Management goes further.
If you think that configuration management is crucial for your company, start educating yourselves first before implementing anything in a tool. There are several places where you can learn all about configuration management.
- Probably the best-known organization is IpX (Institute for Process Excellence), teaching the CM2 methodology. Have a look here: CM2 certification and courses
- Closely related to IpX, Martijn Dullaart shares his thoughts coming from the field as Lead Architect for Enterprise Configuration Management at ASML (one of the Dutch crown jewels) in his blog: MDUX
- CMstat, a configuration and data management solution provider, provides educational posts from their perspective. Have a look at their posts, for example, PLM or PDM or CM
- If you want to have a quick overview of Configuration Management in general, targeted for the mid-market, have a look at this (outdated) course: Training for Small and Medium Enterprises on CONFIGURATION MANAGEMENT. Good for self-study to get an understanding of the domain.
To summarize
In regulated industries, Configuration Management and PLM are a must to ensure compliance and quality. Configuration management and (engineering) change management are, first of all, required methodologies that guarantee the quality of your products. The more complex your products are, the higher the need for change and configuration management.
PLM-systems require embedded engineering change management – part of the PDM domain. Performing Engineering Change Management in a system is something many users do not like, as it feels like overhead. Too much administration or too many mouse clicks.
So far, there is no golden egg that performs engineering change management automatically. Perhaps in a data-driven environment, algorithms can speed-up change management processes. Still, there is a need for human decisions.
Similar to configuration management. If you have a PLM-system that connects all the data from concept, design, and manufacturing in a single environment, it does not mean you are performing configuration management. You need to have processes in place, and depending on your product and industry, the importance will vary.
Conclusion
In the first seven posts, we discussed the design and engineering practices, from CAD to EBOM, ending with the MBOM. Engineering Change Management and, in particular, Configuration Management are methodologies to ensure the consistency of data along the product lifecycle. These methodologies are connected and need to be fit for the future – more on this when we move to modern model-based approaches.
Closing note:
While finishing this blog post today I read Jan Bosch’s post: Why you should not align. Jan touches the same topic that I try to describe in my series Learning from the Past ….., as my intention is to make us aware that by holding on to practices from the past we are blocking our future. Highly recommended to read his post – a quote:
The problem is, of course, that every time you resist change, you get a bit behind. You accumulate some business, process and technical debt. You become a little less “fitting” to the environment in which you’re operating
In this post in the series Learning from the past to understand the future, I want to leave the 3D CAD structures behind. But before doing so, I want to mention some of the lessons learned:
In Part 1: “Intelligent” drawing numbers were the source for “intelligent” part numbers as often there was a one-to-one relationship between the drawing and the part(s) on a drawing.
In Part 2: 3D CAD has been introduced in the automotive and aerospace industry due to process optimization, where a 3D CAD environment created better collaboration possibilities (DMU). The introduction of 3D CAD in the mid-market was different. Here 3D CAD is used as an engineering tool, not changing any processes.
The complexity grew because also file names needed to be managed, introducing the need for PDM-systems.
In Part 3: we discussed the challenges of working with file-based 3D CAD structures. The versioning problem with check-in/check-out of structure in particular in the case of data reuse. Here the best practice was introduced to have physical parts with a different lifecycle than 3D CAD parts and assemblies.
Now engineers need to create valid configurations based on links between the physical part and the 3D/2D object. This requires a PDM-system with BOM and CAD-files as standard information objects.
In Part 4: we discussed the relations between the BOM and 3D CAD structures without neglecting the fact the 2D Drawing is still the primary legal information carrier for manufacturing/suppliers. The point discussed in this post was the fact that most companies used a kind of ETO-approach. Starting from the 3D CAD-system, adding sometimes manufacturing parts in this structure, to generate a BOM that can be served as input for the ERP-system.
I want to follow up from the last conclusion:
Changing from ETO to CTO requires modularity and a BOM-driven approach. Starting from a 3D CAD-structure can still be done for the lowest levels – the modules, the options. In a configure to order process, it might not be relevant anymore to create a full 3D-representation of the product.
Starting from a conceptual structure
Most companies that deliver products to the market do not start from scratch, as we discussed. They will start from either copying an existing product definition (not recommend) or trying to manage the differences between them, meanwhile keeping shared components under revision control.
This cannot be done based on 3D CAD-structures anymore. At that time (we are in the early 2000s) in the mid-market, the PDM-system was used to manage these structures, in particular, they used the BOM-capabilities.
The BOM-structure was often called the EBOM, as engineers were defining the EBOM. But is it really an EBOM? Let us have a look wat defines an EBOM.
What characterizes an EBOM?
There are many personal definitions of what is considered as an EBOM. Also, the Wiki-definition here does not help us a lot. So here is my personal 2004 definition:
- The EBOM reflects the engineering view of a product and, therefore, can have a logical structure of assemblies and subassemblies based on functionality, modularity, and standardization.
- The EBOM is a part structure specifying a product from its design intent, specifying parts, materials, tolerances, finishing.
- The EBOM-structure is allowing multidisciplinary teams to work together on a joint definition of the product
The picture below illustrates the above definition.
In this EBOM-structure, we see that the first two levels actually are more a logical division of functional groups, either as units, product/discipline-specific definitions (cabling/software). These components should not be in the EBOM if you have support for logical structures in your PLM-environment. However, in 2004 – PLM was not that mature in the mid-market, and this approach was often chosen.
If we look at the Line Feed module, which could also be used in other products, there is the typical mechanical definition and in parallel the electrical definition. Having them inside a single EBOM gives the advantage of being able to do a “where-used” and status/impact-analysis.
1 – Purchased parts
Motor P280 is an interesting EBOM-part to consider. This motor is required; however, in an EBOM, you should not specify the supplier part number directly. As supplier part availability and preference will change over time, you do not want to revise the EBOM every time a supplier part gets changed.
Therefore, the Motor P280 should have an internal part number in the EBOM. Next, it will be engineering that specifies which motors fulfill the need for Motor P280. Preferably they will create an Approved Manufacturing List for this motor to give manufacturing/purchasing the flexibility to decide per order where to purchase the motor and from which supplier.
The relation between the Approved Manufacturing List and the Approved Vendor List is shown in the diagram above.
Or follow the link to this image to read more in Arena’s glossary. In particular, for electronic components, this concept is needed as high-level specifications for electronic parts might be the same.
However, the details (tolerances/environment) can be decisive, which component is allowed. Besides, due to the relatively short lifecycle of electronic components, the EBOM needs to be designed in such a manner to anticipate changes in suppliers.
You can only benefit from this approach if, from the beginning of your designs, there are no supplier-specific parts in your EBOM. For Engineering, to Order companies that want to become more Build to Order, this is a challenging but critical point to consider.
Note: The functional characteristics for the motor will come from the electrical definition, and through a reference designator, we create the link between the functional definition and the physical implementation in the product.
2 – Make Parts
Secondly, if we look to the conveyor block D1020 rev A, this block is a make part, with probable a whole assembly of parts below it. As it is a make part, there is at least an assembly drawing and, more likely, a related technical data package linked to D1020 rev A. Make parts still carry a revision as here the Form-Fit-Function discussion can be used when implementing a change of the part.
Note: I used for the final assembly drawing the same number scheme as this is how most companies work. However, in my previous post, I described that if you have a PDM-system in place, the numbering can be different. Maintaining the relations between a part and the related drawing is, in this case, crucial.
The Configured EBOM
The image on the left, we used to illustrate the typical mid-market EBOM in a PDM-system, will become more complicated if we also add options and variants to the EBOM. I assume you know the difference between a variant and an option.
In this case, the EBOM the definition for the full product range. Actually, the top part of the EBOM does not exist as an instance. It is the placeholder to select a resolved EBOM for a specific product configuration. For the ease of use, I have simplified the initial diagram, now zooming in on variants and options, apologizing for my artistic capabilities as the purpose of a blog is different from a book.
If we look at the diagram, this configured structure contains variants and options.
First, on the logical definition, we see a new grouping. There are two types of Line Feed available, one specific for the X-123 and a later, more generic designed LF100, suitable for all X-1nn variants.
As the LF100 is more generic designed, the customer can select between two motors, the standard P280 and the more advanced version P360, with better service capabilities.
For the Line Feed LF200, there is an option to order a Noise Reduction Cover. It was sold once to an existing customer, and as the cover fits all X-123, it has been linked here as an option to the X-123 definition. So, the customer solution with the Noise Reduction Cover does not have an isolated, copied structure in the EBOM.
Also, in the Logical Structure, we see there is a cabling definition for the X-123 or the default cabling set for all other products.
The diagram illustrates what many mid-market companies have been doing more or less in their PDM-system to avoid copying of EBOM structures per customer order.
It is an example of where a tool (the PDM-system) is slowly abused for administrative reasons. Let me explain why.
The link between Products and (E)BOMs
If we look at the upper part of the configured EBOM structure, this is a logical product definition. Or to say it in different words, it is a portfolio definition, which products and modules a company can sell to the market. Some of the grouping of the portfolio is purely based on business reasons, which products and options do we want to sell.
In most companies, the product portfolio is managed in (marketing) documents without a direct connection to the engineering world. However, we will see in an upcoming post, this relation is crucial for a digital enterprise. Meanwhile, look at on old blog post: Products, BOMs and Parts if you want to be faster
The Engineering definition below the red dashed line is a real EBOM, representing the engineering definition of a system, a module, or a component. When these systems and modules are defined in a single structure that can be filtered based on selection criteria, we talk about a Configured EBOM or sometimes a 150 % EBOM.
Each of the components in the configured EBOM can have a related 3D CAD structure or specification that can be developed traditionally.
The result of a resolved EBOM is a variant that can be delivered to the customer. In this EBOM-driven approach, there is not always a full 3D-representation of the customer product.
Again, size (1500+) words make me stop this story, where next time we will go from product to EBOM and introduce the need for an MBOM in specific industries.
Conclusion
A pure EBOM only specifies a product and contains all relevant information in context – designs & specifications. The EBOM should not be mixed or confused with a logical grouping, belonging to a portfolio definition (even if the system allows you to do it)
On my previous post shared on LinkedIn Ilan Madjar, a long-time PLM colleague reacted with the following point (full thread here)
Ilan is pointing to the right challenge in many companies. Changing the way you work is though exercise and requires a good understanding, vision, and execution to move forward. Do not trust the tool to work for you – it is about human understanding and process re-engineering to be more efficient. And if you do not practice this on the basic PDM-level as discussed so far, imagine the impossibility of going through a digital transformation.
Meanwhile, two weeks of a partial lockdown have passed here in the Netherlands, and we have at least another 3 weeks to go according to the Dutch government. The good thing in our country, decisions, and measures are made based on the advice of experts as we cannot rely on politicians as experts.
I realize that despite the discomfort for me, for many other people in other countries, it is a tragedy. My mental support to all of you, wherever you are.
So what has happened since Time to Think (and act differently)?
All Hands On Deck
In the past two weeks, it has become clear that a global pandemic as this one requires an “All Hands On Deck” mentality to support the need for medical supplies and in particular respiration devices, so-called ventilators. Devices needed to save the lives of profoundly affected people. I have great respect for the “hands” that are doing the work in infectious environments.
Due to time pressure, innovative thinking is required to reach quick results in many countries. Companies and governmental organizations have created consortia to address the urgent need for ventilators. You will not see so much PR from these consortia as they are too busy doing the real work.
Still, you see from many of the commercial participants their marketing messages, why, and how they contribute to these activities.
One of the most promoted capabilities is PLM collaboration on the cloud as there is a need for real-time collaboration between people that are under lockdown. They have no time setting-up environments and learning new tools to use for collaboration.
For me, these are grand experiments, can a group of almost untrained people corporate fast in a new environment.
For sure, offering free cloud software, PLM, online CAD or 3D Printing, seems like a positive and compassionate gesture from these vendors. However, this is precisely the wrong perception in our PLM-world – the difficulty with PLM does not lie necessary in the tools.
It is about learning to collaborate outside your silo.
Instead of “wait till I am done” it should become “this is what I have so far – use it for your progress”. This is a behavior change.
Do we have time for behavioral changes at this moment? Time will tell if the myth will become a reality so fast.
A lot of thinking
The past two weeks were weeks of thinking and talking a lot with PLM-interested persons along the globe using virtual meetings.
As long as the lockdowns will be there I keep on offering free of charge PLM coaching for individuals who want to understand the future of PLM.
Through all these calls, I really became THE VirtualDutchman in many of these meetings (thanks Jagan for the awareness).
I realized that there is a lot of value in virtual meetings, in particular with the video option on. Although I believe video works well when you had met before as most of my current meetings were with people, I have met before face-to-face. Hence, you know each other facial expressions already.
I am a big fan of face-to-face meetings as I learned in the past 20 years that despite all the technology and methodology issues, the human factor is essential. We are not rational people; we live and decide by emotions.
Still, I conclude that in the future, I could do with less travel, as I see the benefits from current virtual meetings.
Less face-to-face meetings will help me to work on a more sustainable future as I am aware of the impact flying has on the environment. Also, talking with other people, there is the notion that after the lockdowns, virtual conferencing might become more and more a best practice. Good for the climate, the environment, and time savings – bad for traditional industries like aircraft carriers, taxis, and hotels. I will not say 100 % goodbye but reduce.
A Virtual PLM conference!
I was extremely excited to participate in the upcoming PLM Innovation Forum (PLMIF) starting on April 28th, organized by TECHNIA. I have been visiting the event in the past a few times in Stockholm. It was a great place to meet many of the people from my network.
This time I am even more excited as the upcoming PLMIF will be a VIRTUAL conference with all the aspects of a real conference – read more about the conference here.
There will be an auditorium where lectures will be given, there are virtual booths, and it will be a place to network virtually. In my next post, I hope to zoom in on the conference.
Sustainability, a circular economy, and modern PLM should go together. Since 2014, these topics have been on the agenda of the joint CIMdata Roadmap/PDT conferences. Speakers like Amir Rashid KTH Sweden, Ken Webster Ellen MacArthur Foundation, and many others have been talking about the circular economy.
The Scandinavian mindset for an inclusive society for people and the environment for sure, has influenced the agenda. The links above lead to some better understanding of what is meant by a circular economy and a sustainable future, as also the short YouTube movie below:
The circular economy is crucial for a sustainable future. Therefore, I am looking forward to participating in the upcoming PLM Innovation Forum on April 28th, where it will be all about digitalization for sustainable product development and manufacturing. Hopefully, with the right balance towards the WHY-side of our brain, not so much about WHAT.
You are welcomed to register for free here: the virtual PLM Innovation Forum – we might meet there (virtually).
The PLM Green Alliance
The PLM Green Alliance had been announced some months ago, started by Rich McFall and supported by Bjorn Fidjeland, Oleg Shilovitsky, and me.
It was the first step to proactively bringing people together to discuss topics like reducing our carbon footprint, sharing and brainstorming about innovations that will lead to a sustainable future for ourselves and our children, grand-grand-children. The idea behind the PLM Green Alliance is that a proactive approach is much cheaper in the long term as we can still evaluate and discuss options.
This brings me back to the All hands On Deck approach we currently use for fighting the COVID-19 virus.
In a crisis mode, the damage to the people and the economy is severe. Besides, in a crisis mode, a lot of errors will be made, but don’t blame or joke about these people that are trying. Without failure, there is no learning.
We are in a potential time of disruption as the image shows below, but we do not have the complete answers for the future
Think about how you could pro-actively work on a sustainable future for all of us. This will be my personal target, combined with explaining and coaching companies related to topics of modern PLM, during the current lockdown and hopefully long after. The PLM Green Alliance is eager to learn from you and your companies where they are contributing to a more sustainable and greener future.
Do not feel your contribution is not needed, as according to research done by the Carr Center’s Erica Chenoweth: The ‘3.5% rule’: How a small minority can change the world. It could be an encouragement to act instead of watching who will determine your future.
Conclusion
While learning to live in a virtual world, we might be realizing that the current crisis is an opportunity to switch faster to a more sustainable and inclusive society. For PLM moving to data-driven, cloud-based environments, using a Model-Based approach along the whole lifecycle, is a path to reduce friction when delivering innovations. From years to weeks? Something we wished to have today already. Stay safe!
Jos Voskuil's Weblog 
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