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In my last post, I zoomed in on a preferred technical architecture for the future digital enterprise. Drawing the conclusion that it is a mission impossible to aim for a single connected environment. Instead, information will be stored in different platforms, both domain-oriented (PLM, ERP, CRM, MES, IoT) and value chain oriented (OEM, Supplier, Marketplace, Supply Chain hub).

In part 3, I posted seven statements that I will be discussing in this series. In this post, I will zoom in on point 2:

Data-driven does not mean we do not need any documents anymore. Read electronic files for documents. Likely, document sets will still be the interface to non-connected entities, suppliers, and regulatory bodies. These document sets can be considered a configuration baseline.

 

System of Record and System of Engagement

In the image below, a slide from 2016,  I show a simplified view when discussing the difference between the current, coordinated approach and the future, connected approach.  This picture might create the wrong impression that there are two different worlds – either you are document-driven, or you are data-driven.

In the follow-up of this presentation, I explained that companies need both environments in the future. The most efficient way of working for operations will be infrastructure on the right side, the platform-based approach using connected information.

For traceability and disconnected information exchanges, the left side will be there for many years to come. Systems of Record are needed for data exchange with disconnected suppliers, disconnected regulatory bodies and probably crucial for configuration management.

The System of Record will probably remain as a capability in every platform or cross-section of platform information. The Systems of Engagement will be the configured real-time environment for anyone involved in active company processes, not only ERP or MES, all execution.

Introducing SysML and SML

This summer, I received a copy of Martin Eigner’s System Lifecycle Management book, which I am reading at his moment in my spare moments. I always enjoyed Martin’s presentations. In many ways, we share similar ideas. Martin from his profession spent more time on the academic aspects of product and system lifecycle than I. But, on the other hand, I have always been in the field observing and trying to make sense of what I see and learn in a coherent approach. I am halfway through the book now, and for sure, I will come back on the book when I have finished.

A first impression: A great and interesting book for all. Martin and I share the same history of data management. Read all about this in his second chapter: Forty Years of Product Data Management

From PDM via PLM to SysLM, is a chapter that everyone should read when you haven’t lived it yourself. It helps you to understand the past (Learning for the past to understand the future). When I finish this series about the model-based and connected approach for products and systems, Martin’s book will be highly complementary given the content he describes.

There is one point for which I am looking forward to is feedback from the readers of this blog.

Should we, in our everyday language, better differentiate between Product Lifecycle Management (PLM) and System Lifecycle Management(SysLM)?

In some customer situations, I talk on purpose about System Lifecycle Management to create the awareness that the company’s offering is more than an electro/mechanical product. Or ultimately, in a more circular economy, would we use the term Solution Lifecycle Management as not only hardware and software might be part of the value proposition?

Martin uses consistently the abbreviation SysLM, where I would prefer the TLA SLM. The problem we both have is that both abbreviations are not unique or explicit enough. SysLM creates confusion with SysML (for dyslectic people or fast readers). SLM already has so many less valuable meanings: Simulation Lifecycle Management, Service Lifecycle Management or Software Lifecycle Management.

For the moment, I will use the abbreviation SLM, leaving it in the middle if it is System Lifecycle Management or Solution Lifecycle Management.

 

How to implement both approaches?

In the long term, I predict that more than 80 percent of the activities related to SLM will take place in a data-driven, model-based environment due to the changing content of the solutions offered by companies.

A solution will be based on hardware, the solid part of the solution, for which we could apply a BOM-centric approach. We can see the BOM-centric approach in most current PLM implementations. It is the logical result of optimizing the product lifecycle management processes in a coordinated manner.

However, the most dynamic part of the solution will be covered by software and services. Changing software or services related to a solution has completely different dynamics than a hardware product.

Software and services implementations are associated with a data-driven, model-based approach.

The management of solutions, therefore, needs to be done in a connected manner. Using the BOM-centric approach to manage software and services would create a Kafkaesque overhead.

Depending on your company’s value proposition to the market, the challenge will be to find the right balance. For example, when you keep on selling disconnectedhardware, there is probably no need to change your internal PLM processes that much.

However, when you are moving to a connected business model providing solutions (connected systems / Outcome-based services), you need to introduce new ways of working with a different go-to-market mindset. No longer linear, but iterative.

A McKinsey concept, I have been promoting several times, illustrates a potential path – note the article was not written with a PLM mindset but in a business mindset.

What about Configuration Management?

The different datasets defining a solution also challenge traditional configuration management processes. Configuration Management (CM) is well established in the aerospace & defense industry. In theory, proper configuration management should be the target of every industry to guarantee an appropriate performance, reduced risk and cost of fixing issues.

The challenge, however, is that configuration management processes are not designed to manage systems or solutions, where dynamic updates can be applied whether or not done by the customer.

This is a topic to solve for the modern Connected Car (system) or Connected Car Sharing (solution)

For that reason, I am inquisitive to learn more from Martijn Dullaart’s presentation at the upcoming PLM Roadmap/PDT conference. The title of his session: The next disruption please …

In his abstract for this session, Martijn writes:

From Paper to Digital Files brought many benefits but did not fundamentally impact how Configuration Management was and still is done. The process to go digital was accelerated because of the Covid-19 Pandemic. Forced to work remotely was the disruption that was needed to push everyone to go digital. But a bigger disruption to CM has already arrived. Going model-based will require us to reexamine why we need CM and how to apply it in a model-based environment. Where, from a Configuration Management perspective, a digital file still in many ways behaves like a paper document, a model is something different. What is the deliverable? How do you manage change in models? How do you manage ownership? How should CM adopt MBx, and what requirements to support CM should be considered in the successful implementation of MBx? It’s time to start unraveling these questions in search of answers.

One of the ideas I am currently exploring is that we need a new layer on top of the current configuration management processes extending the validation to software and services. For example, instead of describing every validated configuration, a company might implement the regular configuration management processes for its hardware.

Next, the systems or solutions in the field will report (or validate) their configuration against validation rules. A topic that requires a long discussion and more than this blog post, potentially a full conference.

Therefore I am looking forward to participating in the CIMdata/PDT FALL conference and pick-up the discussions towards a data-driven, model-based future with the attendees.  Besides CM, there are several other topics of great interest for the future. Have a look at the agenda here

 

Conclusion

A data-driven and model-based infrastructure still need to be combined with a coordinated, document-driven infrastructure.  Where the focus will be, depends on your company’s value proposition.

If we discuss hardware products, we should think PLM. When you deliver systems, you should perhaps talk SysML (or SLM). And maybe it is time to define Solution Lifecycle Management as the term for the future.

Please, share your thoughts in the comments.

 

My previous post introducing the concept of connected platforms created some positive feedback and some interesting questions. For example, the question from Maxime Gravel:

Thank you, Jos, for the great blog. Where do you see Change Management tool fit in this new Platform ecosystem?

is one of the questions I try to understand too. You can see my short comment in the comments here. However, while discussing with other experts in the CM-domain, we should paint the path forward. Because if we cannot solve this type of question, the value of connected platforms will be disputable.

It is essential to realize that a digital transformation in the PLM domain is challenging. No company or vendor has the perfect blueprint available to provide an end-to-end answer for a connected enterprise. In addition, I assume it will take 10 – 20 years till we will be familiar with the concepts.

It takes a generation to move from drawings to 3D CAD. It will take another generation to move from a document-driven, linear process to data-driven, real-time collaboration in an iterative manner.  Perhaps we can move faster, as the Automotive, Aerospace & Defense, and Industrial Equipment industries are not the most innovative industries at this time. Other industries or startups might lead us faster into the future.

Although I prefer discussing methodology, I believe before moving into that area, I need to clarify some more technical points before moving forward. My apologies for writing it in such a simple manner. This information should be accessible for the majority of readers.

What means data-driven?

I often mention a data-driven environment, but what do I mean precisely by that. For me, a data-driven environment means that all information is stored in a dataset that contains a single aspect of information in a standardized manner, so it becomes accessible by outside tools.

A document is not a dataset, as often it includes a collection of datasets. Most of the time, the information it is exposed to is not standardized in such a manner a tool can read and interpret the exact content. We will see that a dataset needs an identifier, a classification, and a status.

An identifier to be able to create a connection between other datasets – traceability or, in modern words, a digital thread.
A classification as the classification identifier will determine the type of information the dataset contains and potential a set of mandatory attributes

A status to understand if the dataset is stable or still in work.

Examples of a data-driven approach – the item

The most common dataset in the PLM world is probably the item (or part) in a Bill of Material. The identifier is the item number (ID + revision if revisions are used). Next, the classification will tell you the type of part it is.

Part classification can be a topic on its own, and every industry has its taxonomy.

Finally, the status is used to identify if the dataset is shareable in the context of other information (released, in work, obsolete), allowing tools to expose only relevant information.

In a data-driven manner, a part can occur in several Bill of Materials – an example of a single definition consumed in other places.

When the part information changes, the accountable person has to analyze the relations to the part, which is easy in a data-driven environment. It is normal to find this functionality in a PDM or ERP system.

When the part would change in a document-driven environment, the effort is much higher.

First, all documents need to be identified where this part occurs. Then the impact of change needs to be managed in document versions, which will lead to other related changes if you want to keep the information correct.

Examples of a data-driven approach – the requirement

Another example illustrating the benefits of a data-driven approach is implementing requirements management, where requirements become individual datasets.  Often a product specification can contain hundreds of requirements, addressing the needs of different stakeholders.

In addition, several combinations of requirements need to be handled by other disciplines, mechanical, electrical, software, quality and legal, for example.

As requirements need to be analyzed and ranked, a specification document would never be frozen. Trade-off analysis might lead to dropping or changing a single requirement. It is almost impossible to manage this all in a document, although many companies use Excel. The disadvantages of Excel are known, in particular in a dynamic environment.

The advantage of managing requirements as datasets is that they can be grouped. So, for example, they can be pushed to a supplier (as a specification).

Or requirements could be linked to test criteria and test cases, without the need to manage documents and make sure you work with them last updated document.

As you will see, also requirements need to have an Identifier (to manage digital relations), a classification (to allow grouping) and a status (in work / released /dropped)

Data-driven and Models – the 3D CAD model

3D PDF Model

When I launched my series related to the model-based approach in 2018, the first comments I got came from people who believed that model-based equals the usage of 3D CAD models – see Model-based – the confusion. 3D Models are indeed an essential part of a model-based infrastructure, as the 3D model provides an unambiguous definition of the physical product. Just look at how most vendors depict the aspects of a virtual product using 3D (wireframe) models.

Although we use a 3D representation at each product lifecycle stage, most companies do not have a digital continuity for the 3D representation. Design models are often too heavy for visualization and field services support. The connection between engineering and manufacturing is usually based on drawings instead of annotated models.

I wrote about modern PLM and Model-Based Definition, supported by Jennifer Herron from Action Engineering – read the post PLM and Model-Based Definition here.

If your company wants to master a data-driven approach, this is one of the most accessible learning areas. You will discover that connecting engineering and manufacturing requires new technology, new ways of working and much more coordination between stakeholders.

Implementing Model-Based Definition is not an easy process. However, it is probably one of the best steps to get your digital transformation moving. The benefits of connected information between engineering and manufacturing have been discussed in the blog post PLM and Model-Based Definition

Essential to realize all these exciting capabilities linked to Industry 4.0 require a data-driven, model-based connection between engineering and manufacturing.

If this is not the case, the projected game-changers will not occur as they become too costly.

Data-driven and mathematical models

To manage complexity, we have learned that we have to describe the behavior in models to make logical decisions. This can be done in an abstract model, purely based on mathematical equations and relations. For example, suppose you look at climate models, weather models or COVID infections models.

In that case, we see they all lead to discussions from so-called experts that believe a model should be 100 % correct and any exception shows the model is wrong.

It is not that the model is wrong; the expectations are false.

For less complex systems and products, we also use models in the engineering domain. For example, logical models and behavior models are all descriptive models that allow people to analyze the behavior of a product.

For example, how software code impacts the product’s behavior. Usually, we speak about systems when software is involved, as the software will interact with the outside world.

There can be many models related to a product, and if you want to get an impression, look at this page from the SEBoK wiki: Types of Models. The current challenge is to keep the relations between these models by sharing parameters.

The sharable parameters then again should be datasets in a data-driven environment. Using standardized diagrams, like SysML or UML,  enables the used objects in the diagram to become datasets.

I will not dive further into the modeling details as I want to remain at a high level.

Essential to realize digital models should connect to a data-driven infrastructure by sharing relevant datasets.

What does data-driven imply?

 

I want to conclude this time with some statements to elaborate on further in upcoming posts and discussions

  1. Data-driven does not imply there needs to be a single environment, a single database that contains all information. Like I mentioned in my previous post, it will be about managing connected datasets in a federated manner. It is not anymore about owned the data; it is about access to reliable data.
  2. Data-driven does not mean we do not need any documents anymore. Read electronic files for documents. Likely, document sets will still be the interface to non-connected entities, suppliers, and regulatory bodies. These document sets can be considered a configuration baseline.
  3. Data-driven means that we need to manage data in a much more granular manner. We have to look different at data ownership. It becomes more data accountability per role as the data can be used and consumed throughout the product lifecycle.
  4. Data-driven means that you need to have an enterprise architecture, data governance and a master data management (MDM) approach. So far, the traditional PLM vendors have not been active in the MDM domain as they believe their proprietary data model is leading. Read also this interesting McKinsey article: How enterprise architects need to evolve to survive in a digital world
  5. A model-based approach with connected datasets seems to be the way forward. Managing data in documents will become inefficient as they cannot contribute to any digital accelerator, like applying algorithms. Artificial Intelligence relies on direct access to qualified data.
  6. I don’t believe in Low-Code platforms that provide ad-hoc solutions on demand. The ultimate result after several years might be again a new type of spaghetti. On the other hand, standardized interfaces and protocols will probably deliver higher, long-term benefits. Remember: Low code: A promising trend or a Pandora’s Box?
  7. Configuration Management requires a new approach. The current methodology is very much based on hardware products with labor-intensive change management. However, the world of software products has different configuration management and change procedure. Therefore, we need to merge them in a single framework. Unfortunately, this cannot be the BOM framework due to the dynamics in software changes. An interesting starting point for discussion can be found here: Configuration management of industrial products in PDM/PLM

 

Conclusion

Again, a long post, slowly moving into the future with many questions and points to discuss. Each of the seven points above could be a topic for another blog post, a further discussion and debate.

After my summer holiday break in August, I will follow up. I hope you will join me in this journey by commenting and contributing with your experiences and knowledge.

 

 

 

 

After “The Doctor is IN,” now again a written post in the category of PLM and complementary practices/domains. In January, I discussed together with Henrik Hulgaard from Configit the complementary value of PLM and CLM (Configuration Lifecycle Management). For me, CLM is a synonym for Product Configuration Management.

PLM and Complementary Practices (feedback)

As expected, readers were asking the question:

“What is the difference between CLM (Configuration Lifecycle Management) and CM(Configuration Management)?”

Good question.

As the complementary role of CM is also a part of the topics to discuss, I am happy to share this blog today with Martijn Dullaart. You probably know Martijn if you are actively following topics on PLM and CM.

Martijn has his own blog mdux.net, and you might have seen him recently in Jenifer Moore’s PLM TV-episode: Why CM2 for Faster Change and Better Documentation. Martijn is the Lead Architect for Enterprise Configuration Management at ASML (Our Dutch national pride) and chairperson of the Industry 4.0 committee of the Integrated Process Excellence (IPX) Congress. Let us start.

Configuration Management and CM2

Martijn, first of all, can you bring some clarity in terminology. When discussing Configuration Management, what is the pure definition, what is CM2 as a practice, and what is IpX‘s role and please explain where you fit in this picture?

Classical CM focuses mainly on the product, the product definition, and actual configurations like as-built and as-maintained of the product. CM2 extends the focus to the entire enterprise, e.g., the processes and procedures (ways of working) of a company, including the IT and facilities, to support the company’s value stream.

CM2 expands the scope to all information that could impact safety, security, quality, schedule, cost, profit, the environment, corporate reputation, or brand recognition.

Basically, CM2 shifts the focus to Integrated Process Excellence and promotes continual improvement.

Next to this, CM2 provides the WHAT and the HOW, something most standards lack. My main focus is still around the product and promoting the use of CM outside the product domain.

For all CM related documentation, we are already doing this.

Configuration Management and PLM

People claim that if you implement PLM as an enterprise backbone, not as an engineering tool, you can do Configuration Management with your PLM environment.

What is your opinion?

Yes, I think that this is possible, provided that the PLM tool has the right capabilities. Though the question should be: Is this the best way to go about it. For instance, some parts of Configuration Management are more transactional oriented, e.g., registering the parts you build in or out of a product.

Other parts of CM are more iterative in nature, e.g., doing impact analysis and making an implementation plan. I am not saying this cannot be done in a PLM tool as an enterprise backbone. Still, the nature of most PLM tools is to support iterative types of work rather than a transactional type of work.

I think you need some kind of enterprise backbone that manages the configuration as an As-Planned/As-Released baseline. A baseline that shows not only the released information but also all planned changes to the configuration.

Because the source of information in such a baseline comes from different tools, you need an overarching tool to connect everything. For most companies, this means that they require an overarching system with their current state of enterprise applications.

Preferably I would like to use the data directly from the sources. Still, connectivity and performance are not yet to a level that we can do this. Cloud and modern application and database architectures are very promising to this end.

 

Configuration Management for Everybody?

I can imagine companies in the Aerospace industry need to have proper configuration management for safety reasons. Also, I can imagine that proper configuration management can be relevant for other industries. Do they need to be regulated, or are there other reasons for a company to start implementing CM processes?

I will focus the first part of my answer within the context of CM for products only.

Basically, all products are regulated to some degree. Aerospace & Defense and Medical Device and Pharma are highly regulated for obvious reasons. Other industries are also regulated, for example, through environmental regulations like REACH, RoHS, WEEE or safety-related regulations like the CE marking or FCC marking.

Customers can also be an essential driver for the need for CM. If, as a customer, you buy expensive equipment, you expect that the supplier of that equipment can deliver per commitment. The supplier can also maintain and upgrade the equipment efficiently with as few disruptions to your operations as possible.

Not just customers but also consumers are critical towards the traceability of the product and all its components.

Even if you are sitting on a rollercoaster, you presume the product is well designed and maintained. In other words, there is often a case to be made to apply proper configuration management in any company. Still, the extent to which you need to implement it may vary based on your needs.

 

The need for Enterprise Configuration Management is even more significant because one of the hardest things is to change the way an organization works and operates.

Often there are different ways of doing the same thing. There is a lot of tribal knowledge, and ways of working are not documented so that people can easily find it, let alone that it is structured and linked so that you can do an impact analysis when you want to introduce a change in your organization.

 

CM and Digital Transformation

One of the topics that we both try to understand better is how CM will evolve in the future when moving to a more model-based approach. In the CM-terminology, we still talk about documents as information objects to be managed. What is your idea of CM and a model-based future?

It is indeed a topic where probably new or changed methodology is required, and I started already describing CM topics in several posts on my enterprise MDUX blog. Some of the relevant posts in this context are:

First, let me say that model-based has the future, although, at the same time, the CM aspects are often overlooked.

When managing changes, too much detail makes estimating cost and effort for a business case more challenging, and planning information that is too granular is not desirable. Therefore, CM2 looks at datasets. Datasets should be as small as possible but not smaller. Datasets are sets of information that need to be released as a whole. Still, they can be released independently from other datasets. For example, a bill of materials, a BOM line item is not a dataset, but the complete set of BOM line items that make up the BoM of an assembly is considered a dataset. I can release a BoM independent from a test plan.

Data models need to facilitate this. However, today, in many PLM systems, a BOM and the metadata of a part are using the same revision. This means that to change the metadata, I need a revision of the BoM, while the BoM might not change. Some changes to metadata might not be relevant for a supplier. Communicating the changes to your supplier could create confusion.

I know some people think this is about document vs. model-centric, but it is not. A part is identified in the ‘physical world’ by its part ID. Even if you talk about allowing revisions in the supply chain, including the part ID’s revision, you create a new identifier. Now every new revision will end up in a different stock location. Is that what we want?

In any case, we are still in the early days, and the thinking about this topic has just begun and needs to take shape in the coming year(s).

 

CM and/or CLM?

As in my shared blog post with Henrik Hulgaard related to CLM, can you make a clear differentiation between the two domains for the readers?

 

Configuration Lifecycle Management (CLM)  is mainly positioned towards Configurable Products and the configurable level of the product.

 

Why I think this, even though Configit’s  CLM declaration states that “Configuration Lifecycle Management (CLM) is the management of all product configuration definitions and configurations across all involved business processes applied throughout the lifecycle of a product.”,
it also states:

  • “CLM differs from other Enterprise Business Disciplines because it focuses on cross-functional use of configurable products.”
  • “Provides a Single Source of Truth for Configurable Data
  • “handles the ever-increasing complexity of Configurable Products“.

I find Configuration Lifecycle Management is a core Configuration Management practice you need to have in place for configurable products. The dependencies you need to manage are enormously complex. Software parameters that depend on specific hardware, hardware to hardware dependencies, commercial variants, and options.

Want to learn more?

In this post, we just touched the surface of PLM and Configuration Management. Where can an interested reader find more information related to CM for their company?

 

For becoming trained in CM2, people can reach out to the Institute for Process Excellence, a company that focuses on consultancy and methodology for many aspects of a modern, digital enterprise, including Configuration Management.

And there is more out there, e.g.:

Conclusion

Thanks, Martijn, for your clear explanations. People working seriously in the PLM domain managing the full product lifecycle should also learn and consider Configuration Management best practices. I look forward to a future discussion on how to perform Configuration Management in a model-based environment.

PLM, CLM, and CM – mind the overlap

 

 

 

 

It Is 2021, and after two weeks’ time-out and reflection, it is time to look forward. Many people have said that 2020 was a “lost year,” and they are looking forward to a fresh restart, back to the new normal. For me, 2020 was the contrary of a lost year. It was a year where I had to change my ways of working. Communication has changed, digitization has progressed, and new trends have become apparent.

If you are interested in some of the details, watch the conversation I had with Rob Ferrone from QuickRelease, just before Christmas: Two Santas looking back to 2020.

It was an experiment with video, and you can see there is a lot to learn for me. I agree with Ilan Madjar’s comment that it is hard to watch two people talking for 20 minutes. I prefer written text that I can read at my own pace, short videos (max 5 min), or long podcasts that I can listen to, when cycling or walking around.

So let me share with you some of the plans I have for 2021, and I am eager to learn from you where we can align.

PLM understanding

I plan a series of blog posts where I want to share PLM-related topics that are not necessarily directly implemented in a PLM-system or considered in PLM-implementations as they require inputs from multiple sources.  Topics in this context are: Configuration Management, Product Configuration Management, Product Information Management, Supplier Collaboration Management, Digital Twin Management, and probably more.

For these posts, I will discuss the topic with a subject matter expert, potentially a vendor or a consultant in that specific domain, and discuss the complementary role to traditional PLM. Besides a blog post, this topic might also be more explained in-depth in a podcast.

The PLM Doctor is in

Most of you might have seen Lucy from the Charley Brown cartoon as the doctor giving advice for 5¢. As an experiment, I want to set up a similar approach, however, for free.

These are my conditions:

  • Only one question at a time.
  • The question and answer will be published in a 2- 3 minute video.
  • The question is about solving a pain.

If you have such a question related to PLM, please contact me through a personal message on LinkedIn, and I will follow-up.

PLM and Sustainability

A year ago, I started with Rich McFall, the PLM Green Global Alliance.  Our purpose to bring people together, who want to learn and share PLM-related practices, solutions,  ideas contributing to a greener and more sustainable planet.

We do not want to compete or overlap with more significant global or local organizations, like the Ellen McArthur Foundation or the European Green Deal.

We want to bring people together to dive into the niche of PLM and its related practices.  We announced the group on LinkedIn; however, to ensure a persistent referential for all information and interactions, we have launched the website plmgreenaliance.com.

Here I will moderate and focus on PLM and Sustainability topics. I am looking forward to interacting with many of you.

PLM and digitization

For the last two years, I have been speaking and writing about the gap between current PLM-practices, based on shareable documents and files and the potential future based on shareable data, the Model-Based Enterprise.

Last year I wrote a series of posts giving insights on how we reached the current PLM-practices. Discovering sometimes inconsistencies and issues due to old habits or technology changes. I grouped these posts on a single blog page with the title:  Learning from the past.

This year I will create a collection of posts focusing on the transition towards a Model-Based Enterprise. Probably the summary page will be called: Working towards the future currently in private mode.

Your feedback

I am always curious about your feedback – to understand in which kind of environment your PLM activities take place. Which topics are unclear? What am I missing in my experience?

Therefore, I created a small anonymous survey for those who want to be interacting with me. On purpose, the link is at the bottom of the post, so when you answer the survey, you get my double appreciation, first for reaching the end of this post and second for answering the survey.

Take the survey here.

Conclusion

Most of us will have a challenging year ahead of us. Sharing and discussing challenges and experiences will help us all to be better in what we are doing. I look forward to our 2021 journey.

On March 22 this year, I wrote Time to Think (and act differently) in de middle of a changing world. We were entering a lockdown in the Netherlands due to the COVID-19 virus. As it was such a disruptive change, it was an opportunity to adapt their current ways of working.

The reason for that post was my experience when discussing PLM-initiatives with companies. Often they have no time to sit down, discuss and plan their PLM targets as needed. Crucial people are too busy, leading to an implementation of a system that, in the best case, creates (some) benefits.

The well-known cartoon says it all. We are often too busy doing business as usual, making us feel comfortable. Only when it is too late, people are forced to act.  As the second COVID-19 wave seems to start in the Netherlands, I want to look back on what has happened so far in my eco-system.

Virtual Conferences

As people could not travel anymore, traditional PLM-conferences could not be organized anymore. What was going to be the new future for conferences? TECHNIA, apparently clairvoyant, organized their virtual PLM Innovation Forum as one of the first, end of April.

A more sustainable type of PLM-conference was already a part of their plans, given the carbon footprint a traditional conference induces.  The virtual conference showed that being prepared for a virtual conference pays off during a pandemic with over 1000 participants.

Being first does not always mean being the best,  as we have to learn. While preparing my session for the conference, I felt the same excitement as for a traditional conference. You can read about my initial experience here: The weekend after the PLM Innovation Forum.

Some weeks later, having attended some other virtual conferences, I realized that some points should be addressed/solved:

  • Video conferencing is a must – without seeing people talking, it becomes a podcast.
  • Do not plan long conference days. It is hard to sit behind a screen for a full day. A condensed program makes it easier to attend.
  • Virtual conferences mean that they can be attended live from almost all around the globe. Therefore, finding the right timeslots is crucial for the audience – combined with the previous point – shorter programs.
  • Playing prerecorded sessions without a Q&A session should be avoided. It does not add value.
  • A conference is about networking and discussion – I have not seen a solution for this yet. Fifty percent of the conference value for me comes from face-to-face discussions and coffee meetings. A virtual conference needs to have private chat opportunities between attendees.

In the last quarter of this year, I will present at several merely local conferences, sometimes a mix between “live” with a limited number of attendees, if it will be allowed.

And then there is the upcoming PLM Road Map & PDT Fall 2020 (virtual) conference on 17-18-19 November.

This conference has always been my favorite conference thanks to its continued focus on sharing experiences, most of the time, based on industry standards. We discuss topics and learn from each other. See my previous posts: The weekend after 2019 Day 1, 2019 Day 2, 2018 Day 1, 2018 Day2, 2017 Day 1, 2017 Day 2, etc.

The theme Digital Thread—the PLM Professionals’ Path to Delivering Innovation, Efficiency, and Quality has nothing to do with marketing. You can have a look at the full schedule here. Although there is a lot of buzz around Digital Thread, presenters discuss the reality and their plans

Later in this post, see the paragraph Digital Thread is not a BOM, I will elaborate on this theme.

Getting tired?

I discovered I am getting tired as I am missing face-to-face interaction with people. Working from home, having video calls, is probably a very sustainable way of working.  However, non-planned social interaction, meeting each other at the coffee machine, or during the breaks at a conference or workshop, is also crucial for informal interaction.

Apparently, several others in my eco-system are struggling too. I noticed a tsunami of webinars and blog posts where many of them were an attempt to be noticed. Probably the same reason: traditionally businesses have stalled. And it is all about Digital Transformation and SaaS at this moment. Meaningless if there is no interaction.

In this context, I liked Jan Bosch’s statement in his article: Does data-driven decision-making make you boring? An article not directly addressing the PLM-market; however, there is a lot of overlap related to people’s reluctance to imagine a different future.

My favorite quote:

 I still meet people that continue to express beliefs about the world, their industry, their customers or their own performance that simply aren’t true. Although some, like Steve Jobs, were known for their “reality distortion field,” for virtually all of us, just wishing for something to be true doesn’t make it so. As William Edwards Deming famously said: in God we trust; all others must bring data.

I fully concur with this statement and always get suspicious when someone claims the truth.

Still, there are some diamonds.

I enjoyed all episodes from Minerva PLM TV – Jennifer Moore started these series in the early COVID19-days (coincidence?). She was able to have a collection of interviews with known and less-known people in the PLM-domain. As most of them were vendor-independent, these episodes are a great resource to get educated.

The last episode with Angela Ippisch illustrates how often PLM in companies depends on a few enthusiastic persons, who have the energy to educate themselves. Angela mentions there is a lot of information on the internet; the challenge is to separate the useful information from marketing.

I have been publishing the past five months a series of posts under the joint theme learning from the past to understand the future. In these posts, I explained the evolution from PDM to PLM, resulting in the current item-centric approach with an EBOM, MBOM, and SBOM.

On purpose, one post per every two weeks – to avoid information overflow. Looking back, it took more posts than expected, and they are an illustration of the many different angles there are in the PLM domain – not a single truth.

Digital Thread is not a BOM

I want to address this point because I realized that in the whole blogging world there appear to be two worlds when discussing PLM terminology. Oleg Shilovitsky, CEO@OpenBOM, claims that Digital Thread and Digital Twin topics are just fancy marketing terms. I was even more surprised to read his post: 3 Reasons Why You Should Avoid Using The Word “Model” In PLM. Read the comments and discussion in these posts (if LinkedIn allows you to navigate)

Oleg’s posts have for me most of the time, always something to discuss. I would be happier if other people with different backgrounds would participate in these discussions too – A “Like” is not a discussion. The risk in a virtual world is that it becomes a person-to-person debate, and we have seen the damage such debates can do for an entire community.

In the discussion we had related to Digital Thread and BOM, I realized that when we talk about traditional products, the BOM and the Digital Thread might be the same. This is how we historically released products to the market. Once produced, there were no more changes. In these situations, you could state a PLM-backbone based on BOM-structures/views, the EBOM, MBOM, and SBOM provide a Digital Thread.

The different interpretation comes when talking about products that contain software defining its behavior. Like a computer, the operating system can be updated on the fly; meanwhile, the mechanical system remains the same. To specify and certify the behavior of the computer, we cannot rely on the BOM anymore.

Having software in the BOM and revise the BOM every time there is a software change is a mission impossible. A mistake suggested ten years ago when we started to realize the different release cycles of hardware and software. Still, it is all about the traceability of all information related to a product along its whole lifecycle.

In a connected environment, we need to manage relationships between the BOM and relations to other artifacts. Managing these relations in a connected environment is what I would call the Digital Thread – a layer above PLM. While writing this post, I saw Matthias Ahrens’ post stating the same (click on the image to see the post)

When we discuss managing all the relations, we touch the domain of Configuration Management.  Martijn Dullaart/Martin Haket’s picture shares the same mindset – here, CM is the overlapping layer.

However, in their diagram, it is not a system picture; the different systems do not need to be connected. Configuration Management is the discipline that maintains the correct definition of every product – CM maintains the Thread. When it becomes connected, it is a Digital Thread.

As I have reached my 1500 words, I will not zoom in on the PLM and Model discussion – build your opinion yourself. We have to realize that the word Model always requires a context. Perhaps many of us coming from the traditional PDM/PLM world (managing CAD data) think about CAD models. As I studied physics before even touching CAD, I grew up with a different connotation

Lars Taxén’s comment in this discussion perhaps says it all (click on the image to read it). If you want to learn and discuss more about the Digital Thread and Models, register for the PLM Roadmap & PDT2020 event as many of the sessions are in this context (and not about 3D CAD).

Conclusion

I noticed I am getting tired of all the information streams crying for my attention and look forward to real social discussions, not broadcasted. Time to think differently requires such discussion, and feel free to contact me if you want to reflect on your thoughts. My next action will be a new series named Painting the future to stay motivated. (As we understand the past).

I believe we are almost at the end of learning from the past. We have seen how, from an initial serial CAD-driven approach with PDM, we evolved to PLM-managed structures, the EBOM and the MBOM. Or to illustrate this statement, look at the image below, where I use a Tech-Clarity image from Jim Brown.

The image on the right describes perfectly the complementary roles of PLM and ERP. The image on the left shows the typical PDM-approach. PDM feeding ERP in a linear process. The image on the right, I believe it is from 2004, shows the best practice before digital transformation. PLM is supporting product innovation in an iterative approach, pushing released information to ERP for execution.

As I think in images, I like the concept of a circle for PLM and an arrow for ERP. I am always using those two images in discussions with my customers when we want to understand if a particular activity should be in the PLM or ERP-domain.

Ten years ago, the PLM-domain was conceptually further extended by introducing support for products in operations and service. Similar to the EBOM (engineering) and the MBOM (manufacturing), the SBOM (service) was introduced to support product information for products in operation. In theory a full connected cicle.

Asset Lifecycle Management

At the same time, I was promoting PLM-practices for owners/operators to enhance Asset Lifecycle Management. My first post from June 2010 was called: PLM for Asset Lifecycle Management and Asset Development introduces this approach.

Conceptually the SBOM and Asset Lifecycle Management have a lot in common. There is a design product, in this case, an asset (plant, machine) running in the field, and we need to make sure operators have the latest information about the asset. And in case of asset changes, which can be a maintenance operation, a repair or complete overall, we need to be sure the changes are based on the correct information from the as-built environment. This requires full configuration management.

Asset changes can be based on extensive projects that need to be treated like new product development projects, with a staged approach that can take weeks, months, sometimes years. These activities are typical activities performed in PLM-systems, not in MRO-systems that are designed to manage the actual operation. Again here we see the complementary roles of PLM (iterative) and MRO (execution).

Since 2008, I have worked a lot in this environment, mainly in the nuclear and process industry. If you want to learn more about this aspect of PLM, I recommend looking at the PLMpartner website, where Bjørn Fidjeland, in cooperation with SharePLM, published a course on Plant Information Management. We worked together in several projects and Bjørn has done a great effort to describe the logical model to be used instead of a function-feature story.

Ten years ago, we were not calling this concept the “Digital Twin,” as the aim was to provide end-to-end support of asset information from engineering, procurement, and construction towards operation in a coordinated manner. The breaking point in the relation between the EPCs and Owner/Operators is the data-handover – how much of your IP can/do you expose and what is needed. Nowadays, we would call striving for end-to-end data continuity the Digital Thread.

Hot from the press in this context, CIMdata just published a commentary Managing the Digital Thread in Global Value Chains describing Eurostep’s ShareAspace capabilities and experiences in managing an end-to-end information flow (Digital Thread) in a heterogeneous environment based on exchange standards like ISO 10303-239 PLCS.  Their solution is based on what I consider a more modern approach for managing digital continuity compared to the traditional approach I described before. Compare the two images in this paragraph. The first image represents the old/current way with a disconnected handover, the second represents ShareAspace connected approach based on a real digital thread.

The Service BOM

As discussed with Asset Lifecycle Management, there is a disconnect between the engineering disciplines and operations in the field, looking from the point of view of an Asset owner/operator.

Now when we look from the perspective of a manufacturing company that produces assets to be serviced, we can identify a different dataflow and a new structure, the Service BOM (SBOM).

The SBOM provides information on how a product needs to be serviced. What are the parts that require service, and what are the service kits that are possible for that product? For that reason, service engineering should be done in parallel to product engineering. When designing a product, the engineer needs to identify which the wearing parts (always require service in time) and which parts might be serviceable.

There are different ways to look at the SBOM. Conceptually, the SBOM could be created in close relation with the EBOM. At the moment you define your product, you also should specify how the product will be services. See the image below

From this example, it is clear that part standardization and modularization have a considerable benefit for services downstream. What if you have only one serviceable part that applies to many products? The number of parts to have in stock will be strongly reduced instead of having many similar parts that only fit in a single product?

Depending on the type of product, the SBOM can be generic, serving many products in the field. In that case, the company has to deal with catalogs, to be defined in PLM. Or the SBOM can be aligned with the As-Built of a capital product in the field. In that case, the concepts of Asset Lifecycle Management apply. Click on the image to see a clear picture.

The SBOM on its own,  in such an environment, will have links to specific documents, service instructions, operating manuals.

If your PLM-system allows it, extending the EBOM and MBOM with an SBOM is not a complex effort. What is crucial to understand is that the SBOM has its own lifecycle, which can even last longer than the active product sold. So sometimes, manufacturing specifications, related to service parts need to be maintained too, creating a link between the SBOM and potential MBOM(s).

ECM = Enterprise Change Management

When I discussed ECM in my previous post in the context of Engineering Change Management, I got the feedback that nowadays, everyone talks about Enterprise Change Management. Engineering Change Management is old school.

In the past, and even in a 2014 benchmark, a customer had two change management systems. One in PLM and one in ERP, and companies were looking into connecting these two processes. Like the BOM-interaction between PLM and ERP, this is technology-wise, never a real problem.

The real problem in such situations was to come to a logical flow of events. Many times the company insisted that every change should start from the ERP-system as we like to standardize. This means that even an engineering change had to be registered first in the ERP-system

Luckily the reach of PLM has grown. PLM is no longer the engineering tool (IT-system thinking). PLM has become the information backbone for product information all along the product lifecycle. Having the MBOM and SBOM available through a PLM-infrastructure allows organizations to streamline their processes.

Aras – digital thread through connected structures

And in this modern environment, enterprise change management might take place mostly in a PLM-infrastructure. The PLM-infrastructure providing a digital thread, as the Aras picture above illustrates, provides the full traceability to support configuration management.

However, we still have to remember that configuration management and engineering change management, first of all, are based on methodology and processes. Next, the combination of tools to be used will vary.

I like to conclude this topic with a quote from Lee Perrin’s comment on my previous blog post

I would add that aerospace companies implemented CM, to avoid fatal consequences to their companies, but also to their flying customers.

PLM provides the framework within which to carry out Configuration Management. CM can indeed be carried out without PLM, as was done in the old paper-based days. As you have stated, PLM makes the whole CM process much more efficient. I think more transparent too.

Conclusion

After nine posts around the theme Learning from the past to understand the future, I walked through the history of CAD, PDM and PLM in a fast mode, pointing to practices and friction points. In the blogging space, it is hard to find this information as most blog posts are coming from software vendors explaining why their tool is needed. Hopefully, these series have helped many of you to understand a broader context. Now I want to focus on the future again in my upcoming blog posts.

Still, feel free to contact me and discuss methodology topics.

Picture by Christi Wijnen – a good friend and photographer in the Netherlands

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 my last post, My four picks from PLMIF,  I ended with the remark that the discussion related to the Multiview BOM concept was not complete. The session presented by James Roche focused on the Aerospace & defense domain and touched the surface. There is a lot of confusion related to best practices associated with BOM-handling. Sometimes created to promote unique vendor capabilities or to hide system complexity.

Besides, we need to consider the past as, in particular, for PLM, the burden of legacy processes and data is significant. Some practices even come from the previous, paper-based century, later mixed with behavior from 3D CAD-systems.

Therefore, to understand the future, I will take you through the past to understand why certain practices were established. Next, in a few upcoming posts, I want to explain the evolution of BOM-practices. How each new technology step introduced new capabilities that enabled companies to improve their product delivery process.

I will describe the drawing approach (for PLM – the past), the item-centric approach (for PLM – the current), and the model-driven approach(for PLM – the future). How big this sequence will become is not clear at this stage.

Whenever I come close to 1200 – 1500 words, I will stop and conclude. Based on my To-do list and your remarks, I will continue in a follow-up post.  The target will be to have a vendor-neutral collection of information to help you identify your business and the next possible steps.

Working with drawings

MRP/ERP – the first IT-system

For this approach, I go back fifty years in time, when companies were starting to work with their first significant IT-system, the MRP-system. MRP stands for Material Requirements Planning. This system became the heart of the company, scheduling the production. The extension to ERP (Enterprise Resource Planning) quickly after, made it possible to schedule other resources and, essential for the management, to report financials. Now execution could be monitored by generating all kinds of reports.

Still, the MRP/ERP-system was wholly disconnected from the engineering world as the image shows below. Let us have a look at how this worked at that time.

The concept

Products have never been designed from scratch by jumping to drawings. In the concept phase, a product was analyzed, mainly on its mechanical behavior. Was there anything else at that time? Many companies thank their existence from a launching product which someone, most of the time, the founder of the company, invented in a workshop. The company than improved and enriched this product by starting from the core product, creating enhancements in various areas of applicability.

These new ideas were shared through sketches and prototypes.

The design

The detail design of a product is delivered by a technical documentation set, often a package of manufacturing drawings containing a list of parts on the drawing, assembly with instructions. Balloon numbers are used to indicate parts in an assembly or section view.  In addition, there are the related fabrication drawings. The challenge for this approach is that all definitions must be there uniquely and complete to avoid ambiguity, which could lead to manufacturing errors.

The parts list contains make-parts, supplier parts, and standard parts. The make-parts are specified again by manufacturing drawings, identified by a number that uniquely identifies the correct drawing version. A habit here: Part number = Drawing Number (+ revision)

As the part is identified by a drawing the part most of the time got an “intelligent” part number and a revision. Intelligent to support easy recognition and revisions as at the end we do not want to generate a new part number when there is an evolution of the part. Read more about this in What the FFF is happening and “Intelligent” part numbers?

The standardized parts can be either company standard parts or external standard parts. There is a difference between them.

A company standard part could be a certain bracket, a frame. Anything that the company decided to standardize on for its own products Company standard parts are treated like make parts; they have an identifier related to their manufacturing drawings.  Again, here the habit: Part Number = Drawing Number (+ revision)

The supplier part is coming from a supplier that manufactures this part based on the supplier or market specifications. You can specify this part by using the supplier’s catalog number or refer to the standard.

For example, the part that has been specified under a certain ISO/ANSI/DIN-standard. For example, a stainless-steel bolt M8 x 1,25 x 20, meaning a metric bolt with a head diameter of 8 mm, a speed of 1,25 mm, and a length of 20 mm. You specify the standard part according to the standard. Purchasing will decide where to buy this part

Manufacturing Preparation

This is the most inefficient stage when working in a traditional drawing approach. At this stage, the information provided in drawings needs to be entered into the MRP/ERP-system to start production. This is the place where information is thrown over the wall as some might say.

This means a person needs to create process steps in the ERP-system based on the drawing information. For each manufacturing step, there needs to be a reference to the right drawing. Most ERP-systems have a placeholder where you can type the drawing number(s). Later, when companies were using CAD, there could be a reference to a file.

The part number in the ERP-system might be the same as the drawing number; however, the ERP-system requires unique numbers. In the beginning, ERP-systems were the number-generator for new parts. The unique number was often 6 to 7 digits in size, because it fits in our human short-term memory.

The parts list on the drawings had to be entered in the ERP-system too. A manual operation that often required additional research from the manufacturing engineer. As the designer might have specified the SS Bolt M8 x 1,25 x 20 as such, manufacturing preparation has to search in the ERP-system for the company’s part number.

Suppliers have to be sourced for outside manufactured make-parts. In case you do not want to depend on a single supplier, you have to send drawings and specifications to the supplier before the product is released. The supplier will receive a drawing number with revision and status warning.

If everything worked well the first time, there would be no iterations between engineering and manufacturing preparation. However, this is a utopia: prototype changes, potential manufacturing issues will require changes in the drawings. These changes require updates in the drawings, which will lead to new versions. How do you keep consistency between all identifiers?

Manufacturing

During manufacturing, orders are processed based on information from the ERP-system. The shop floor gets the drawing provided to the link in ERP. Sometimes there are issues during manufacturing. In coordination with engineering, some adaptations will be made to the manufacturing process. e.g., a changed fit or tolerance. Instead of going back to engineering to provide a new documentation set, the relevant drawings are redlined. Engineering will update these drawings whenever they touch them in the future (yeah, yeah).

Configuration Management

But will they update them? Perhaps already a new version existed due to the product’s evolution. Everything needs to be coordinated manually. Smaller companies heavily rely on people knowing things and talking together.

Larger companies cannot work in the same manner; therefore, they introduce procedures to guarantee that the information flow is consistent and accurate. Here the practices from configuration management come in.

There are many flavors of configuration management. Formal CM was first used in the 1950s to control the technical documentation for complex space and weapons systems. (Source ESA CM initiative for SME’s – © 2000) We will see it come back in future posts dealing with more complex products and the usage of computer systems.

Last year I wrote a few times about PLM and configuration management (PLM and CM – a happy marriage?) not relevant at this moment as there is no PLM yet.

Where is the BOM

As you might have noticed, there was no mentioning of a BOM so far. At this stage, there is only one Bill of Materials managed in the ERP-system. The source from the BOM comes from the various parts lists on the drawings, completed with manual additions.

Nobody talks in this stage about an EBOM or MBOM as there is only one BOM, a kind of hybrid BOM, where manufacturing steps were driving the way parts are grouped. Because the information was processed step by step, why would you like to have a multilevel BOM or a BOM tree?
Note: The image on the left was one of my first images in 2008 when I started my blog.

Summary

Working with drawings introduced “intelligent” part numbers as the documents have to be identified by manual interpretations. The intelligence of the part number was there to prevent people from making mistakes as the number already was a kind of functional identifier. Combined with a revision and versioning in the number, nothing could go wrong if handled consistently.

The disadvantage was that new employees had to master a numbering system. Next, the risk for all employees that a released drawing will not change its status. Only manual actions (retract/replace) will avoid making mistakes. And then, there are the disconnected redline drawings.

The “drawing number equals part number”  relation created a constraint that will be hard to maintain in the future.  Therefore you should worry if you still work according the above principles.

Conclusion

I reached the 1500 words – a long story – probably far from complete. I encourage readers to provide enhancements that might be relevant in the comments. This post might look like a post for dummies. However, to understand what is applicable to the future, we first need to understand why certain practices have been defined in the past.
I am looking forward to your comments and enhancements to make this a relevant stream of public information for all.

One week ago, Yoann Maingon wrote an innocent post with the question: Has FFF killed?  The question was raised related to a 2014 problem at GM, where a changed part was causing fatal accidents.

The discussion started by Yoann and here my short extract. Assuming this problem was a configuration management issue and Yoann somehow indicated that the problem might be related to the fact that ERP-systems do not carry a revision on the part number – leading to an unnoticed change.  Therefore, he assumes there is a disconnect between the PLM-side (where we have parts with multiple lifecycle states and revisions) and ERP (where we have an industrial lifecycle – prototype/production).

He posted his thoughts, and then LinkedIn exploded (currently 116 comments), which means it is a topic that is of significant concern in our community. Next, if you read the comments, there are different viewpoints:

  • What does FFF really imply?
  • What about revisions of parts?
  • What are the best practices?

Let’s investigate these viewpoints with some comments

What does FFF really imply?

When we talk about FFF in engineering, we mean Form, Fit and Function – the three primary characteristics to describe a part  (source Wikipedia)

  • Form refers to such characteristics as external dimensions, weight, size, and visual appearance of a part or assembly. This is the element of FFF that is most affected by an engineer’s aesthetic choices, including enclosure, chassis, and control panel, that become the outward “face” of the product.
  • Fit refers to the ability of the part or feature to connect to, mate with, or join to another feature or part within an assembly. The “fit” allows the part to meet the required assembly tolerances to be useful.
  • Function is a criterion that is met when the part performs its stated purpose effectively and reliably. In an electronics product, for example, a function can depend on the solid-state components used, the software or firmware, and quite often on the features of the electronics enclosure selected.

One of the comments in Yoann’s post referred to Safe/Unsafe as a potential functional characteristic. I think this addition is not needed. Safety should be a requirement for the part, not a characteristic.

FFF was and still is an approach for engineers to decide if a new, improved version of the part would get a revision or needs a new part number.

I think before we dive deeper into the other viewpoints, it is crucial to define the part number a little more.

In a correct PLM data model, there are two types of part numbers. First, the internal part number that your company uses inside its engineering Bill of Materials to identify a part. This part number can be a meaningless part only to provide uniqueness inside the company.

In 2015 I wrote several posts related to best practices and data modeling for PLM. The most relevant posts to this discussion are here:

The part number can specify a part that needs to be manufactured according to specification, or it can be a part that needs to be purchased from an available supplier/manufacturer. The manufacturer part number is, most of the time, a meaningful number (6 – 7 characters) as these parts need to be ordered by your company. The manufacturer part number is the SKU for the manufacturer. As you can imagine in the manufacturer’s catalog, there isn’t a revision mentioned. In graphics, see the image below:

Your company might sell Product MP-323121 (note: the ID is meaningful to help the customer to order the product).

Internally there is a related EBOM that specifies the product. The EBOM top part is O122 (note: here, we can use a meaningless identifier as all is digitally connected).

For the manufacturing of O122, we need to resolve the EBOM according to its specifications. Therefore, for Part O124, the company needs to decide to purchase from their approved manufacturers either part ABC-21231 or XYZ-88818 (note: again, a meaningful ID as these companies are not digitally connected).

Now coming back to the FFF-discussion. For the orange parts, with a meaningful ID, no revision exists. However, if Assembly O122 is 100% FFF compatible, the Product ID MP-323121 will not change. It allows your company to optimize the EBOM and/or MBOM, meanwhile keeping 100% compatibility to the outside world. (note: the same principle applies to the two manufacturers for Part O124.)

In case Top Assembly O122 has new or changed parts – what should happen there?

At that moment, the definition has changed. The definitions, most of the time described in documents/drawings/models, are related information to the BOM. Therefore the Top Assembly O122 should get a new identifier. There is no need to name it a revision, it is a new data set in the PLM-system, again with a meaningless identifier as we are connected digitally,

What about revisions of parts?

Of course, the management of changes existed long before PLM-systems were introduced.

The specifications of a part were defined in drawings. The drawing contained all the information, not only the geometry definitions, but also specifications on how to manufacture the part.

For complex products, a considerable set of consistently related drawings would be released to manufacturing.  A release process with physical signatures on it.

At the same time, there was no discussion: the drawing represents the part. And as there was no digital connection, part numbers/drawing numbers were meaningful, often with the format of the drawing as part of the identifier.

In case changes were needed, for example, fixing a dimension or tolerance as discovered during manufacturing, the drawing had to be revised to remain consistent. First, in the original drawing, the issue or change was marked in red (redlining). Then engineering had to create a new version of the drawing.

Depending on the impact of change (here comes also the FFF-principle), people decided if a new part number was needed (FFF-change) or that the change only required an update of the drawing(s), meaning a revision.  If the difference was small (for example, adding a missing annotation), it could be called a minor change, all to be reflected in the drawing number, which equals the part number in this approach. So, when we talk about revisions of parts, we are talking about a document change.

A lousy practice from that approach is also that often manufacturing just redlines a drawing and keeps the redlined drawing as their source. It is too time-consuming or difficult to update the source drawing(s) through a change process. Engineering is not aware of this change, and when a later change comes through from engineering, these “fixes” might be missed as there is no traceability.

Generic example of a PLM data model and its relationsWhen PLM-systems were introduced, of course, companies did not want to disrupt their existing ways of working. Therefore, they were asking the PLM-editors to enable revisions on parts and so the PLM-editors did (or do).

Decoupling of parts and documents in a PLM data model

However, if you want to use the PLM-system in the best manner, you need to “decouple” the concept:  part number equals drawing number, combined with the possibility to start using meaningless identifiers, as relations between parts and drawings are managed in the PLM-system through relational links.

Relevant post related to the PLM data model are:

What are the best practices?

As some people mentioned in their comments to Yoann’s post, why do we have to answer this question as all is already well understood and described in best practices? I agree with that statement: Best Practices exist – so how to obtain them?

First, there is the whole framework of Configuration Management, which existed long before PLM-systems were introduced. If you follow their methodology, you can be (almost) guaranteed your information is consistent and correct. Configuration Management is crucial in areas where the impact of an error is enormous, like the GM-example Yoann referred to. Also, companies in the Aerospace and Defense industry are the ones that have strict configuration management in place.

Configuration management does not come for free. It requires an investment in skills, potentially a change in ways of working, and requires an overhead. Manufacturing companies that are creating less “risky” products often focus more on optimizing (= reducing) the cost of their internal processes instead of investing in proper methodologies to manage consistency.

If you want to learn more about CM, investigate the Institute of Process Excellence (IPX), the founders of the CM2 framework for Enterprise Configuration Management, and much more. Note: Their knowledge does not come for free, which I can understand. However, it also creates a barrier for the company’s further investment in CM as this kind of strategic investments are hard to sell at the management level by individuals in a company.

In the context of CM, I advise you to follow Martijn Dullaart, who is quite active in our social community. His latest blog post related to this thread is: It’s about Interchangeability and Traceability

With the introduction of PLM-system, these companies and the PLM-editors created the opportunity to implement configuration management in their system.

The data inside the system would be the “single version of the truth.” Unfortunately, this was most of the time, just a sales strategy, falsely giving the impression that information is under control now. Last year I wrote several posts related to the relation between PLM and CM, starting from PLM and Configuration Management – a happy marriage?

If you are interested in another resource for information related to these topics, have a look at the website from Jörg Eisenträger who also collected his best practices for PLM and CM for sharing (thanks Paul van der Ree for the link)

Don’t expect best practices from your PLM-vendors as their role is to sell software. It is the continuous discussion between:

  • A PLM-system that forces companies to work according to embedded methodology (hard to sell/implement but idealistically correct)

And

  • A flexible PLM-system that allows you to build and configure anything (easy to sell/challenging to implement correctly, depending on “wise” decisions)

The Future

Even though most companies are working drawing-centric, with or without a linked PLM-backbone for BOM-management, the next upcoming challenge is to evolve to model-based practices. The current CM-practices still talk about documents, although documents are already electronic datasets in that context. The future, however, in a model-based enterprise evolves related to connected models, 3D Models, but also simulation and software models, with different lifecycles and pace of change. For the model-based enterprise, we need to develop digital best practices that guarantee the same level of quality, however, executed and/or supported by (AI) Artificial Intelligence. AI is needed as human beings cannot physically analyze and understand all the impact of a change in such an environment.

Conclusion

The FFF-discussion illustrates that building a consistent framework within PLM is not an easy goal to achieve. My blog buddy Oleg Shilovitsky would claim that we consultants create the complexity. PLM-editors will never solve this complexity, it is up to your company’s mission to invest in knowledge to understand why and how to reduce the complexity. With this post and the related links and discussions, I hope more clarity will help you to make “wise” decisions.

This time a post that has been on the table already for a long time – the importance of having established processes, in particular with implementing PLM.  By nature, most people hate processes as it might give the idea that their personal creativity is limited, where large organizations love processes as for them this is the way to guarantee a confident performance.  So let’s have a more in-depth look.

Where processes shine

In a transactional world, processes can be implemented like algorithms, assuming the data to be processed has the right quality. That is why MRP (Material Requirement Planning) and ERP (Enterprise Resource Planning) don’t have the mindset of personal creativity. It is about optimized execution driven by financial and quality goals.

When I started my career in the early days of data management, before it was called PDM/PLM, I learned that there is a need for communication-related to product data. Terms are revisions, and versions started to pop-up combined with change processes. Some companies began to talk about configuration management.

Companies were not thinking PLM along the whole lifecycle. It was more PDM for engineering and ERP for manufacturing. Where PDM was ultimate a document-control environment, ERP was the execution engine relying on documented content, but not necessarily connected. Unfortunate this is still the case at many companies, and it has to do with the mindset. Traditionally a company’s performance has been measured based on financial reporting coming from the ERP system. Engineering was an unmanageable cost in the eyes of the manufacturing company’s management and ERP-software vendors.

In de middle of the nineties (previous century now ! ), I had a meeting with an ERP-country manager to discuss a potential partnership. The challenge was that he had no clue about the value and complementary need for PLM. Even after discussing with him the differences between iterative product development (with revisioning) and linear execution (on the released product), his statement was:

“Engineers are just resources that do not want to be managed, but we will get them”

Meanwhile, I can say this company has changed its strategy, giving PLM a space in their portfolio combined with excellent slides about what could be possible.

To conclude, for linear execution the meaning of processes is more or less close to algorithms and when there is no algorithm, the individual steps in place are predictable with their own KPIs.

Process certification

As I mentioned in the introduction, processes were established to guarantee a predictable outcome, in particular when it comes to quality. For that reason, in the previous century when globalization started companies were somehow forced to get ISO 900x certified. The idea behind these certifications was that a company had processes in place to guarantee an expected outcome and for when they failed, they would have procedures in place to fix these gaps. The reason companies were doing this because no social internet could name and shame bad companies. Having ISO 900x certification would be the guarantee to deliver quality.  In the same perspective, we could see, configuration management, a system of best practices to guarantee that product information was always correct.

Certification was and is heaven for specialized external auditors and consultants.  To get certification you needed to invest in people and time to describe your processes, and once these processes were defined, there were regular external audits to ensure the quality system has been followed.  The beauty of this system – the described procedures were more or less “best intentions” not enforced. When the auditor would come the company had to play some theater that processes were followed., the auditor would find some improvements for next year and the management was happy certification was passed.

This has changed early this century. In particular, mid-market companies were no longer motivated to keep up this charade. The quality process manual remained as a source of inspiration, but external audits were no longer needed. Companies were globally connected and reviewed, so reputation could be sourced easily.

The result: there are documented quality procedures, and there is a reality. The more disconnected employees became in a company due to mergers or growth, the more individual best-practices became the way to deliver the right product and quality, combined with accepted errors and fixes downstream or later. The hidden cost of poor quality is still a secret within many companies.  Talking with employees they all have examples where their company lost a lot of money due to quality mistakes. Yet in less regulated industries, there is no standard approach, like CAPA (Corrective And Preventive Actions), APQP or 8D to solve it.

Configuration Management and Change Management processes

When it comes to managing the exact definition of a product, either an already manufactured product or products that are currently made, there is a need for Configuration Management.  Before there were PLM systems configuration management was done through procedures defining configurations based on references to documents with revisions and versions. In the aerospace industry, separate systems for configuration management were developed, to ensure the exact configuration of an aircraft could be retrieved at any time. Less regulated industries used a more document-based procedural approach as strict as possible. You can read about the history of configuration management and PLM in an earlier blog post: PLM and Configuration Management – a happy marriage?

With the introduction of PDM and PLM-systems, more and more companies wanted to implement their configuration management and in particular their change management inside the system, as the changes are always related to product information that can reside in a PLM-system. The change of part can be proposed (ECR), analyzed and approved, leading to and implementation of the change (ECO) which is based on changed specifications, designs (3D Models / Drawings) and more. You can read the basics here: The Issue and ECR/ECO for Dummies (Reprise)

The Challenge (= Problem) of Digital Processes

More and more companies are implementing change processes fully in PLM, and this is the point that creates the most friction for a PLM implementation. The beauty of digital change processes is that they can be full-proof. No change gets unnoticed as everyone is forced to follow the predefined procedures, either a type of fast track in case of lightweight (= low risk) changes or the full change process when the product is already in a mature state.

Like the ISO-900x processes, the PLM-implementer is often playing the role of the consultancy firm that needs to recommend the company how to implement configuration management and change processes. The challenge here is that the company most of the time does not have a standard view for their change processes and for sure the standard change management inside PLM s not identical to their processes.

Here the battle starts….

Management believes that digital change processes, preferable out-of-the-box, a crucial to implement, where users feel their job becomes more an administrative job than a creative job. Users that create information don’t want to be bothered with the decisions for numbering and revisioning.

They expect the system to do that easily for them – which does not happen as old procedures, responsibilities, and methodologies do not align with the system. Users are not measured or challenged for data quality, they are measured on the work they deliver that is needed now. Let’s first get the work done before we make sure all is consisted defined in the PLM-system.

Digital Transformation allows companies to redefine the responsibilities for users related to the data they produce. It is no longer a 3D Model or a drawing, but a complete data set with properties/attributes that can be shared and used for analysis and automation.

Conclusion

Implementing digital processes for PLM is the most painful, but required step for a successful implementation. As long as data and processes are not consistent, we can keep on dreaming about automation in PLM. Therefore, digital transformation inside PLM should focus on new methods and responsibilities to create a foundation for the future. Without an agreement on the digital processes there will be a growing inefficiency for the future.

 

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