So far, I have been discussing PLM experiences and best practices that have changed due to introducing electronic drawings and affordable 3D CAD systems for the mainstream. From vellum to PDM to item-centric PLM to manage product designs and manufacturing specifications.

Although the technology has improved, the overall processes haven’t changed so much. As a result, disciplines could continue to work in their own comfort zone, most of the time hidden and disconnected from the outside world.

Now, thanks to digitalization, we can connect and format information in real-time. Now we can provide every stakeholder in the company’s business to have almost real-time visibility on what is happening (if allowed). We have seen the benefits of platformization, where the benefits come from real-time connectivity within an ecosystem.

Apple, Amazon, Uber, Airbnb are the non-manufacturing related examples. Companies are trying to replicate these models for other businesses, connecting the concept owner (OEM ?), with design and manufacturing (services), with suppliers and customers. All connected through information, managed in data elements instead of documents – I call it connected PLM

Vendors have already shared their PowerPoints, movies, and demos from how the future would be in the ideal world using their software. The reality, however, is that implementing such solutions requires new business models, a new type of organization and probably new skills.

The last point is vital, as in schools and organizations, we tend to teach what we know from the past as this gives some (fake) feeling of security.

The reality is that most of us will have to go through a learning path, where skills from the past might become obsolete; however, knowledge of the past might be fundamental.

In the upcoming posts, I will share with you what I see, what I deduct from that and what I think would be the next step to learn.

I firmly believe connected PLM requires the usage of various models. Not only the 3D CAD model, as there are so many other models needed to describe and analyze the behavior of a product.

I hope that some of my readers can help us all further on the path of connected PLM (with a model-based approach). This series of posts will be based on the max size per post (avg 1500 words) and the ideas and contributes coming from you and me.

What is platformization?

In our day-to-day life, we are more and more used to direct interaction between resellers and services providers on one side and consumers on the other side. We have a question, and within 24 hours, there is an answer. We want to purchase something, and potentially the next day the goods are delivered. These are examples of a society where all stakeholders are connected in a data-driven manner.

We don’t have to create documents or specialized forms. An app or a digital interface allows us to connect. To enable this type of connectivity, there is a need for an underlying platform that connects all stakeholders. Amazon and Salesforce are examples for commercial activities, Facebook for social activities and, in theory, LinkedIn for professional job activities.

The platform is responsible for direct communication between all stakeholders.

The same applies to businesses. Depending on the products or services they deliver, they could benefit from one or more platforms. The image below shows five potential platforms that I identified in my customer engagements. Of course, they have a PLM focus (in the middle), and the grouping can be made differently.

Five potential business platforms

The 5 potential platforms

The ERP platform
is mainly dedicated to the company’s execution processes – Human Resources, Purchasing, Finance, Production scheduling, and potentially many more services. As platforms try to connect as much as possible all stakeholders. The ERP platform might contain CRM capabilities, which might be sufficient for several companies. However, when the CRM activities become more advanced, it would be better to connect the ERP platform to a CRM platform. The same logic is valid for a Product Innovation Platform and an ERP platform.  Examples of ERP platforms are SAP and Oracle (and they will claim they are more than ERP)

Note: Historically, most companies started with an ERP system, which is not the same as an ERP platform.  A platform is scalable; you can add more apps without having to install a new system. In a platform, all stored data is connected and has a shared data model.

The CRM platform

a platform that is mainly focusing on customer-related activities, and as you can see from the diagram, there is an overlap with capabilities from the other platforms. So again, depending on your core business and products, you might use these capabilities or connect to other platforms. Examples of CRM platforms are Salesforce and Pega, providing a platform to further extend capabilities related to core CRM.

The MES platform
In the past, we had PDM and ERP and what happened in detail on the shop floor was a black box for these systems. MES platforms have become more and more important as companies need to trace and guide individual production orders in a data-driven manner. Manufacturing Execution Systems (and platforms) have their own data model. However, they require input from other platforms and will provide specific information to other platforms.

For example, if we want to know the serial number of a product and the exact production details of this product (used parts, quality status), we would use an MES platform. Examples of MES platforms (none PLM/ERP related vendors) are Parsec and Critical Manufacturing

The IoT platform

these platforms are new and are used to monitor and manage connected products. For example, if you want to trace the individual behavior of a product of a process, you need an IoT platform. The IoT platform provides the product user with performance insights and alerts.

However, it also provides the product manufacturer with the same insights for all their products. This allows the manufacturer to offer predictive maintenance or optimization services based on the experience of a large number of similar products.  Examples of IoT platforms (none PLM/ERP-related vendors) are Hitachi and Microsoft.

The Product Innovation Platform (PIP)

All the above platforms would not have a reason to exist if there was not an environment where products were invented, developed, and managed. The Product Innovation Platform PIP – as described by CIMdata  -is the place where Intellectual Property (IP) is created, where companies decide on their portfolio and more.

The PIP contains the traditional PLM domain. It is also a logical place to manage product quality and technical portfolio decisions, like what kind of product platforms and modules a company will develop. Like all previous platforms, the PIP cannot exist without other platforms and requires connectivity with the other platforms is applicable.

Look below at the CIMdata definition of a Product Innovation Platform.

You will see that most of the historical PLM vendors aiming to be a PIP (with their different flavors): Aras, Dassault Systèmes, PTC and Siemens.

Of course, several vendors sell more than one platform or even create the impression that everything is connected as a single platform. Usually, this is not the case, as each platform has its specific data model and combining them in a single platform would hurt the overall performance.

Therefore, the interaction between these platforms will be based on standardized interfaces or ad-hoc connections.

Standard interfaces or ad-hoc connections?

Suppose your role and information needs can be satisfied within a single platform. In that case, most likely, the platform will provide you with the right environment to see and manipulate the information.

However, it might be different if your role requires access to information from other platforms. For example, it could be as simple as an engineer analyzing a product change who needs to know the actual stock of materials to decide how and when to implement a change.

This would be a PIP/ERP platform collaboration scenario.

Or even more complex, it might be a product manager wanting to know how individual products behave in the field to decide on enhancements and new features. This could be a PIP, CRM, IoT and MES collaboration scenario if traceability of serial numbers is needed.

The company might decide to build a custom app or dashboard for this role to support such a role. Combining in real-time data from the relevant platforms, using standard interfaces (preferred) or using API’s, web services, REST services, microservices (for specialists) and currently in fashion Low-Code development platforms, which allow users to combine data services from different platforms without being an expert in coding.

Without going too much in technology, the topics in this paragraph require an enterprise architecture and vision. It is opportunistic to think that your existing environment will evolve smoothly into a digital highway for the future by “fixing” demands per user. Your infrastructure is much more likely to end up congested as spaghetti.

In that context, I read last week an interesting post Low code: A promising trend or Pandora’s box. Have a look and decide for yourself

I am less focused on technology, more on methodology. Therefore, I want to come back to the theme of my series: The road to model-based and connected PLM. For sure, in the ideal world, the platforms I mentioned, or other platforms that run across these five platforms, are cloud-based and open to connect to other data sources. So, this is the infrastructure discussion.

In my upcoming blog post, I will explain why platforms require a model-based approach and, therefore, cause a challenge, particularly in the PLM domain.

It took us more than fifty years to get rid of vellum drawings. It took us more than twenty years to introduce 3D CAD for design and engineering. Still primarily relying on drawings. It will take us for sure one generation to switch from document-based engineering to model-based engineering.

Conclusion

In this post, I tried to paint a picture of the ideal future based on connected platforms. Such an environment is needed if we want to be highly efficient in designing, delivering, and maintaining future complex products based on hardware and software. Concepts like Digital Twin and Industry 4.0 require a model-based foundation.

In addition, we will need Digital Twins to reach our future sustainability goals efficiently. So, there is work to do.

Your opinion, Your contribution?

 

 

 

 

 

 

In March 2018, I started a series of blog posts related to model-based approaches. The first post was:  Model-Based – an introduction.  The reactions to these series of posts can be summarized in two bullets:

  • Readers believed that the term model-based was focusing on the 3D CAD model. A logical association as PLM is often associated with 3D CAD-model data management (actually PDM), and in many companies, the 3D CAD model is (yet) not a major information carrier/
  • Readers were telling me that a model-based approach is too far from their day-to-day life. I have to agree here. I was active in some advanced projects where the product’s behavior depends on a combination of hardware and software. However, most companies still work in a document-driven, siloed discipline manner merging all deliverables in a BOM.

More than 3 years later, I feel that model-based approaches have become more and more visible for companies. One of the primary reasons is that companies start to collaborate in the cloud and realize the differences between a coordinated and a connected manner.

Initiatives as Industry 4.0 or concepts like the Digital Twin demand a model-based approach. This post is a follow-up to my recent post, The Future of PLM.

History has shown that it is difficult for companies to change engineering concepts. So let’s first look back at how concepts slowly changed.

The age of paper drawings

In the sixties of the previous century, the drawing board was the primary “tool” to specify a mechanical product. The drawing on its own was often a masterpiece drawn on special paper, with perspectives, details, cross-sections.

All these details were needed to transfer the part or assembly information to manufacturing. The drawing set should contain all information as there were no computers.

Making a prototype was, depending on the complexity of the product, the interpretation of the drawings and manufacturability of a product, not always that easy.  After a first release, further modifications to the product definition were often marked on the manufacturing drawings using a red pencil. Terms like blueprint and redlining come from the age of paper drawings.

There are still people talking nostalgically about these days as creating and interpreting drawings was an important skill. However, the inefficiencies with this approach were significant.

  • First, updating drawings because there was redlining in manufacturing was often not done – too much work.
  • Second, drawing reuse was almost impossible; you had to start from scratch.
  • Third, and most importantly, you needed to be very skilled in interpreting a drawing set. In particular, when dealing with suppliers that might not have the same skillset and the knowledge of which drawing version was actual.

However, paper was and still is the cheapest neutral format to distribute designs. The last time I saw companies still working with paper drawings was at the end of the previous century.

Curious to learn if they are now extinct?

The age of electronic drawings (CAD)

With the introduction of AutoCAD and personal computers around 1982, more companies started to look into drafting with the computer. There was already the IBM drafting system in 1965, but it was Autodesk that pushed the 2D drafting business with their slogan:

“80 percent of the functionality for 20 percent of the price (Autodesk 1982)”

A little later, I started to work for an Autodesk distributor/reseller. People would come to the showroom to see how a computer drawing could be plotted in the finest quality at the end. But, of course, the original draftsman did not like the computer as the screen was too small.

However, the enormous value came from making changes, the easy way of sharing drawings and the ease of reuse. The picture on the left is me in 1989, demonstrating AutoCAD with a custom-defined tablet and PS/2 computer.

The introduction of electronic drawings was not a disruption, more optimization of the previous ways of working.

The exchange with suppliers and manufacturing could still be based on plotted drawings – the most neutral format. And thanks to the filename, there was better control of versions between all stakeholders.

Aren’t we all happy?

The introduction of mainstream 3D CAD

In 1995,  3D CAD became available for the mid-market, thanks to SolidWorks, Solid Edge and a little later Inventor. Before that working with 3D CAD was only possible for companies that could afford expensive graphic stations, provided by IBM, Silicon Graphics, DEC and SUN. Where are they nowadays? The PC is an example of disruptive innovation, purely based on technology. See Clayton Christensen’s famous book: The Innovator’s Dilemma.

The introduction of 3D CAD on PCs in the mid-market did not lead directly to new ways of working. Designing a product in 3D was much more efficient if you mastered the skills. 3D brought a better understanding of the product dimensions and shape, reducing the number of interpretation errors.

Still, (electronic) drawings were the contractual deliverable when interacting with suppliers and manufacturing.  As students were more and more trained with the 3D CAD tools, the traditional art of the draftsman disappeared.

3D CAD introduced some new topics to solve.

  • First of all, a 3D CAD Assembly in the system was a collection of separate files, subassemblies, parts, and drawings that relate to each other with a specific version. So how to ensure the final assembly drawings were based on the correct part revisions? Companies were solving this by either using intelligent filenames (with revisions) or by using a PDM system where the database of the PDM system managed all the relations and their status.
  • The second point was that the 3D CAD assembly also introduced a new feature, the product structure, or the “Bill of Materials”. This logical structure of the assembly up resembled a lot of the Bill of Material of the product. You could even browse deeper levels, which was not the case in the traditional Bill of Material on a drawing.

Note: The concept of EBOM and MBOM was not known in most companies. People were talking about the BOM as a one-level definition of parts or subassemblies in the assembly. See my Where is the MBOM? Post from July 2008 when this topic was still under discussion.

  • The third point that would have a more significant impact later is that parts and assemblies could be reused in other products. This introduced the complexity of configuration management. For example, a 3D CAD part or assembly file could contain several configurations where only one configuration would be valid for the given product. Managing this in the 3D CAD system lead to higher productivity of the designer, however downstream when it came to data management with PDM systems, it became a nightmare.

I experienced these issues a lot when discussing with companies and implementers, mainly the implementation of SmarTeam combined with SolidWorks and Inventor. Where to manage the configuration constraints? In the PDM system or inside the 3D CAD system.

These environments were not friends (image above), and even if they came from the same vendor, it felt like discussing with tribes.

The third point also covered another topic. So far, CAD had been the first step for the detailed design of a product. However, companies now had an existing Bill of Material in the system thanks to the PDM systems. It could be a Bill of Material of a sub-assembly that is used in many other products.

Configuring a product no longer started from CAD; it started from a Product or Bill of Material structure. Sales and Engineers identified the changes needed on the BoM, keeping as much as possible released information untouched. This led to a new best practice.

The item-centric approach

Around 2005, five years after introducing the term Product Lifecycle Management, slowly, a new approach became the standard. Product Lifecycle Management was initially introduced to connect engineering and manufacturing, driven by the automotive and aerospace industry.

It was with PLM that concepts as EBOM and MBOM became visible.

In particular, the EBOM was closely linked to engineering practices, i.e., modularity and reuse. The EBOM and its related information represented the product as it was specified. It is essential to realize that the parts in the EBOM could be generic specified purchase parts to be resolved when producing the product or that the EBOM contained Make-parts specified by drawings.

At that time, the EBOM was often used as the foundation for the ERP system – see image above. The BOM was restructured and organized according to the manufacturing process specifying materials and resources needed in the ERP system. Therefore, although it was an item-like structure, this BOM (the MBOM) always had a close relation to the Bill of Process.

For companies with a single manufacturing site, the notion of EBOM and MBOM was not that big, as the ERP system would be the source of the MBOM. However, the complexity came when companies have several manufacturing sites. That was when a generic MBOM in the PLM system made more sense to centralize all product information in a single system.

The EBOM-MBOM approach has become more and more a standard practice since 2010. As a result, even small and medium-sized enterprises realized a need to manage the EBOM and the MBOM.

There were two disadvantages introduced with this EBOM-MBOM approach.

  • First, the EBOM and the MBOM as information structures require a lot of administrative maintenance if information needs to be always correct (and that is the CM target).  Some try to simplify this by keeping the EBOM part the same as the MBOM part, meaning the EBOM specification already targets a single supplier or manufacturer.
  • The second disadvantage of making every item in the BOM behave like a part creates inefficiencies in modern environments. Products are a mix of hardware(parts) and software(models/behavior). This BOM-centric view does not provide the proper infrastructure for a data-driven approach as part specifications are still done in drawings. We need 3D annotated models related to all kinds of other behavior and physical models to specify a product that contains hard-and software.

A new paradigm is needed to manage this mix efficiently, the enabling foundation for Industry 4.0 and efficient Digital Twins; there is a need for a model-based approach based on connected data elements.

More next week.

Conclusion

The age of paper drawings 1960 – now dead
The age of electronic drawings 1982 – potentially dead in 2030
The mainstream 3D CAD 1995 – to be evolving through MBD and MBSE to the future – not dead shortly
Item-centric approach 2005 – to be evolving to a connected model-based approach – not dead shortly

In April this year, I published the post PLM and Modularity in which I had a dialogue with Daniel Strandhammar from Brick Strategy. Daniel and his colleague Bjorn Eriksson published the book “the Modular Way” written during the COVID-19 lockdowns.

We promised a recorded follow-up discussion with readers from the book. The follow-up initially planned for somewhere in May happened last week in June, with a significant contribution from the participants.

Theodor Ernstson, Henk Jan Pels, Jan Johansson and François Sychowicz shared their impression of the book with Daniel and Bjorn. Next, the following questions were posed and discussed:

  • Modular design as a concept is already more than 50 years old, using different definitions, approaches and methodologies. In the book, an interesting list of steps is proposed. Is this list shared across modularity experts, or are they specific to this book?
  • Do you see different ways of approaching modularity depending on the industry, or is it the same?
  • When implementing modularization, which departments need to change their way of working most?
  • How big a factor is the use of common technology in modularization?
  • How do you position modularization vs. system engineering?
  • As a measure of module quality, the concept of “independent” modules is often used to avoid that adding or changing a module might cause another module to fail. Have you seen this happening in your projects, and do you consider the concept of an “independent” module realizable?
  • How do we make modularization stand out on the C-level agenda?

Watch the discussion here:

 

We felt that with this discussion, we only touched the tip of the iceberg. Each of the questions could be a theme for a deep conversation for some of us. Perhaps also for you – feel free to comment on this post or express your opinion. Based on the feedback, I am happy to moderate more detailed discussions related to modularity.

Conclusion

Reading books makes sense. Having a discussion afterward with some readers and the authors makes even more sense. Normally we would do this during a physical conference, meanwhile enjoying a drink or a snack. However, having a global and sustainable model of discussing and learning these virtual events might be the future. An entry point for enriching your network and knowledge.

Another episode of “The PLM Doctor is IN“. This time a question from Ilan Madjar, partner and co-founder of XLM Solutions. Ilan is my co-moderator at the PLM Global Green Alliance for sustainability topics.

All these activities resulted in the following question(s) related to the Digital Twin. Now sit back and enjoy.

PLM and the Digital Twin

Is it a new concept? How to implement and certify the result?

Relevant topics discussed in this video

Conclusion

I hope you enjoyed the answer and look forward to your questions and comments. Let me know if you want to be an actor in one of the episodes.


The main rule: A (single) open question that is puzzling you related to PLM.

After the first article discussing “The Future of PLM,” now again a post in the category of PLM and complementary practices/domains a topic that is already for a long time on the radar: Model-Based Definition, I am glad to catch up with Jennifer Herron, founder of Action Engineering, who is one of the thought leaders related to Model-Based Definition (MBD) and Model-Based Enterprise (MBE).

In 2016 I spoke with Jennifer after reading her book: “Re-Use Your CAD – The Model-Based CAD Handbook”. At that time, the discussion was initiated through two articles on Engineering.com. Action Engineering introduced OSCAR seven years later as the next step towards learning and understanding the benefits of Model-Based Definition.

Therefore, it is a perfect moment to catch up with Jennifer. Let’s start.

 

Model-Based Definition

Jennifer, first of all, can you bring some clarity in terminology. When I discussed the various model-based approaches, the first response I got was that model-based is all about 3D Models and that a lot of the TLA’s are just marketing terminology.
Can you clarify which parts of the model-based enterprise you focus on and with the proper TLA’s?

Model-Based means many things to many different viewpoints and systems of interest. All these perspectives lead us down many rabbit holes, and we are often left confused when first exposed to the big concepts of model-based.

At Action Engineering, we focus on Model-Based Definition (MBD), which uses and re-uses 3D data (CAD models) in design, fabrication, and inspection.

There are other model-based approaches, and the use of the word “model” is always a challenge to define within the proper context.

For MBD, a model is 3D CAD data that comes in both native and neutral formats

Another model-based approach is Model-Based Systems Engineering (MBSE). The term “model” in this context is a formalized application of modeling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later lifecycle phases.

<Jos> I will come back on Model-Based Systems Engineering in future posts

Sometimes MBSE is about designing widgets, and often it is about representing the entire system and the business operations. For MBD, we often focus our education on the ASME Y14.47 definition that MBD is an annotated model and associated data elements that define the product without a drawing.

Model-Based Definition for Everybody?

I believe it took many years till 3D CAD design became a commodity; however, I still see the disconnected 2D drawing used to specify a product or part for manufacturing or suppliers. What are the benefits of model-based definition?
Are there companies that will not benefit from the model-based definition?

There’s no question that the manufacturing industry is addicted to their drawings. There are many reasons why, and yet mostly the problem is lack of awareness of how 3D CAD data can make design, fabrication, and inspection work easier.

For most, the person doing an inspection in the shipping and receiving department doesn’t have exposure to 3D data, and the only thing they have is a tabulated ERP database and maybe a drawing to read. If you plop down a 3D viewable that they can spin and zoom, they may not know how that relates to their job or what you want them to do differently.

Today’s approach of engineering championing MBD alone doesn’t work. To evolve information from the 2D drawing onto the 3D CAD model without engaging the stakeholders (machinists, assembly technicians, and inspectors) never yields a return on investment.

Organizations that succeed in transitioning to MBD are considering and incorporating all departments that touch the drawing today.

Incorporating all departments requires a vision from the management. Can you give some examples of companies that have transitioned to MBD, and what were the benefits they noticed?

I’ll give you an example of a small company with no First Article Inspection (FAI) regulatory requirements and a huge company with very rigorous FAI requirements.

 

Note: click on the images below to enjoy the details.

The small company instituted a system of CAD modeling discipline that allowed them to push 3D viewable information directly to the factory floor. The assembly technicians instantly understood engineering’s requirements faster and better.

The positive MBD messages for these use cases are 3D  navigation, CAD Re-Use, and better control of their revisions on the factory floor.

 

The large company has added inspection requirements directly onto their engineering and created a Bill of Characteristics (BOC) for the suppliers and internal manufacturers. They are removing engineering ambiguity, resulting in direct digital information exchange between engineering, manufacturing, and quality siloes.

These practices have reduced error and reduced time to market.

The positive MBD messages for these use cases are unambiguous requirements capture by Engineering, Quality Traceability, and Model-Based PMI (Product and Manufacturing Information).

Model-Based Definition and PLM?

How do you see the relation between Model-Based Definition and PLM? Is a PLM system a complication or aid to implement a Model-Based Definition? And do you see a difference between the old and new PLM Vendors?

Model-Based Definition data is complex and rich in connected information, and we want it to be. With that amount of connected data, a data management system (beyond upload/download of documents) must keep all that data straight.

Depending on the size and function of an organization, a PLM may not be needed. However, a way to manage changes and collaboration amongst those using 3D data is necessary. Sometimes that results in a less sophisticated Product Data Management (PDM) system. Large organizations often require PLM.

There is significant resistance to doing MBD and PLM implementations simultaneously because PLM is always over budget and behind schedule. However, doing just MBD or just PLM without the other doesn’t work either. I think you should be brave and do both at once.

I think we can debate why PLM is always over budget and behind schedule. I hear the same about ERP implementations. Perhaps it has to deal with the fact that enterprise applications have to satisfy many users?

I believe that working with model versions and file versions can get mixed in larger organizations, so there is a need for PDM or PLM. Have you seen successful implementations of both interacting together?

Yes, the only successful MBD implementations are those that already have a matured PDM/PLM (scaled best to the individual business).

 

Model-Based Definition and Digital Transformation

In the previous question, we already touched on the challenge of old and modern PLM. How do you see the introduction of Model-Based Definition addressing the dreams of Industry 4.0, the Digital Twin and other digital concepts?

I just gave a presentation at the ASME Digital Twin Summit discussing the importance of MBD for the Digital Twin. MBD is a foundational element that allows engineering to compare their design requirements to the quality inspection results of digital twin data.

The feedback loop between Engineering and Quality is fraught with labor-intensive efforts in most businesses today.

Leveraging the combination of MBD and Digital Twin allows automation possibilities to speed up and increase the accuracy of the engineering to inspection feedback loop. That capability helps organizations realize the vision of Industry 4.0.

And then there is OSCAR.

I noticed you announced OSCAR. First, I thought OSCAR was a virtual aid for model-based definition, and I liked the launching page HERE. Can you tell us more about what makes OSCAR unique?

One thing that is hard with MBD implementation is there is so much to know. Our MBDers at Action Engineering have been involved with MBD for many years and with many companies. We are embedded in real-life transitions from using drawings to using models.

Suppose you start down the model-based path for digital manufacturing. In that case, there are significant investments in time to learn how to get to the right set of capabilities and the right implementation plan guided by a strategic focus. OSCAR reduces that ramp-up time with educational resources and provides vetted and repeatable methods for an MBD implementation.

OSCAR combines decades of Action Engineering expertise and lessons learned into a multi-media textbook of sorts. To kickstart an individual or an organization’s MBD journey, it includes asynchronous learning, downloadable resources, and CAD examples available in Creo, NX, and SOLIDWORKS formats.

CAD users can access how-to training and downloadable resources such as the latest edition of Re-Use Your CAD (RUYC). OSCAR enables process improvement champions to make their case to start the MBD journey. We add content regularly and post what’s new. Free trials are available to check out the online platform.

Learn more about what OSCAR is here:

Want to learn more?

In this post, I believe we only touched the tip of the iceberg. There is so much to learn and understand. What would you recommend to a reader of this blog who got interested?

 

RUYC (Re-Use Your CAD)  is an excellent place to start, but if you need more audio-visual, and want to see real-life examples of MBD in action, get a Training subscription of OSCAR to get rooted in the vocabulary and benefits of MBD with a Model-Based Enterprise. Watch the videos multiple times! That’s what they are for. We love to work with European companies and would love to support you with a kickstart coaching package to get started.

What I learned

First of all, I learned that Jennifer is a very pragmatic person. Her company (Action Engineering) and her experience are a perfect pivot point for those who want to learn and understand more about Model-Based Definition. In particular, in the US, given her strong involvement in the American Society of Mechanical Engineers (ASME).

I am still curious if European or Asian counterparts exist to introduce and explain the benefits and usage of Model-Based Definition to their customers.  Feel free to comment.

Next, and an important observation too, is the fact that Jennifer also describes the tension between Model-Based Definition and PLM. Current PLM systems might be too rigid to support end-to-end scenarios, taking benefit of the Model-Based definition.

I have to agree here. PLM Vendors mainly support their own MBD (model-based definition), where the ultimate purpose is to share all product-related information using various models as the main information carriers efficiently.

We have to study and solve a topic in the PLM domain, as I described in my technical highlights from the PLM Road Map & PDT Spring 2021 conference.

There is work to do!

Conclusion

Model-Based Definition is, for me, one of the must-do steps of a company to understand the model-based future. A model-based future sometimes incorporates Model-Based Systems Engineering, a real Digital Thread and one or more Digital Twins (depending on your company’s products).

It is a must-do activity because companies must transform themselves to depend on digital processes and digital continuity of data to remain competitive. Document-driven processes relying on the interpretation of a person are not sustainable.

 

After the first article discussing “The Future of PLM,” now again a post in the category of PLM and complementary practices/domains a topic that is already for a long time on the radar: Model-Based Definition, I am glad to catch up with Jennifer Herron, founder of Action Engineering, who is one of the thought leaders related to Model-Based Definition (MBD) and Model-Based Enterprise (MBE).

In 2016 I spoke with Jennifer after reading her book: “Re-Use Your CAD – The Model-Based CAD Handbook”. At that time, the discussion was initiated through two articles on Engineering.com. Action Engineering introduced OSCAR seven years later as the next step towards learning and understanding the benefits of Model-Based Definition.

Therefore, it is a perfect moment to catch up with Jennifer. Let’s start.

 

Model-Based Definition

Jennifer, first of all, can you bring some clarity in terminology. When I discussed the various model-based approaches, the first response I got was that model-based is all about 3D Models and that a lot of the TLA’s are just marketing terminology.
Can you clarify which parts of the model-based enterprise you focus on and with the proper TLA’s?

Model-Based means many things to many different viewpoints and systems of interest. All these perspectives lead us down many rabbit holes, and we are often left confused when first exposed to the big concepts of model-based.

At Action Engineering, we focus on Model-Based Definition (MBD), which uses and re-uses 3D data (CAD models) in design, fabrication, and inspection.

There are other model-based approaches, and the use of the word “model” is always a challenge to define within the proper context.

For MBD, a model is 3D CAD data that comes in both native and neutral formats

Another model-based approach is Model-Based Systems Engineering (MBSE). The term “model” in this context is a formalized application of modeling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later lifecycle phases.

<Jos> I will come back on Model-Based Systems Engineering in future posts

Sometimes MBSE is about designing widgets, and often it is about representing the entire system and the business operations. For MBD, we often focus our education on the ASME Y14.47 definition that MBD is an annotated model and associated data elements that define the product without a drawing.

Model-Based Definition for Everybody?

I believe it took many years till 3D CAD design became a commodity; however, I still see the disconnected 2D drawing used to specify a product or part for manufacturing or suppliers. What are the benefits of model-based definition?
Are there companies that will not benefit from the model-based definition?

There’s no question that the manufacturing industry is addicted to their drawings. There are many reasons why, and yet mostly the problem is lack of awareness of how 3D CAD data can make design, fabrication, and inspection work easier.

For most, the person doing an inspection in the shipping and receiving department doesn’t have exposure to 3D data, and the only thing they have is a tabulated ERP database and maybe a drawing to read. If you plop down a 3D viewable that they can spin and zoom, they may not know how that relates to their job or what you want them to do differently.

Today’s approach of engineering championing MBD alone doesn’t work. To evolve information from the 2D drawing onto the 3D CAD model without engaging the stakeholders (machinists, assembly technicians, and inspectors) never yields a return on investment.

Organizations that succeed in transitioning to MBD are considering and incorporating all departments that touch the drawing today.

Incorporating all departments requires a vision from the management. Can you give some examples of companies that have transitioned to MBD, and what were the benefits they noticed?

I’ll give you an example of a small company with no First Article Inspection (FAI) regulatory requirements and a huge company with very rigorous FAI requirements.

 

Note: click on the images below to enjoy the details.

The small company instituted a system of CAD modeling discipline that allowed them to push 3D viewable information directly to the factory floor. The assembly technicians instantly understood engineering’s requirements faster and better.

The positive MBD messages for these use cases are 3D  navigation, CAD Re-Use, and better control of their revisions on the factory floor.

 

The large company has added inspection requirements directly onto their engineering and created a Bill of Characteristics (BOC) for the suppliers and internal manufacturers. They are removing engineering ambiguity, resulting in direct digital information exchange between engineering, manufacturing, and quality siloes.

These practices have reduced error and reduced time to market.

The positive MBD messages for these use cases are unambiguous requirements capture by Engineering, Quality Traceability, and Model-Based PMI (Product and Manufacturing Information).

Model-Based Definition and PLM?

How do you see the relation between Model-Based Definition and PLM? Is a PLM system a complication or aid to implement a Model-Based Definition? And do you see a difference between the old and new PLM Vendors?

Model-Based Definition data is complex and rich in connected information, and we want it to be. With that amount of connected data, a data management system (beyond upload/download of documents) must keep all that data straight.

Depending on the size and function of an organization, a PLM may not be needed. However, a way to manage changes and collaboration amongst those using 3D data is necessary. Sometimes that results in a less sophisticated Product Data Management (PDM) system. Large organizations often require PLM.

There is significant resistance to doing MBD and PLM implementations simultaneously because PLM is always over budget and behind schedule. However, doing just MBD or just PLM without the other doesn’t work either. I think you should be brave and do both at once.

I think we can debate why PLM is always over budget and behind schedule. I hear the same about ERP implementations. Perhaps it has to deal with the fact that enterprise applications have to satisfy many users?

I believe that working with model versions and file versions can get mixed in larger organizations, so there is a need for PDM or PLM. Have you seen successful implementations of both interacting together?

Yes, the only successful MBD implementations are those that already have a matured PDM/PLM (scaled best to the individual business).

 

Model-Based Definition and Digital Transformation

In the previous question, we already touched on the challenge of old and modern PLM. How do you see the introduction of Model-Based Definition addressing the dreams of Industry 4.0, the Digital Twin and other digital concepts?

I just gave a presentation at the ASME Digital Twin Summit discussing the importance of MBD for the Digital Twin. MBD is a foundational element that allows engineering to compare their design requirements to the quality inspection results of digital twin data.

The feedback loop between Engineering and Quality is fraught with labor-intensive efforts in most businesses today.

Leveraging the combination of MBD and Digital Twin allows automation possibilities to speed up and increase the accuracy of the engineering to inspection feedback loop. That capability helps organizations realize the vision of Industry 4.0.

And then there is OSCAR.

I noticed you announced OSCAR. First, I thought OSCAR was a virtual aid for model-based definition, and I liked the launching page HERE. Can you tell us more about what makes OSCAR unique?

One thing that is hard with MBD implementation is there is so much to know. Our MBDers at Action Engineering have been involved with MBD for many years and with many companies. We are embedded in real-life transitions from using drawings to using models.

Suppose you start down the model-based path for digital manufacturing. In that case, there are significant investments in time to learn how to get to the right set of capabilities and the right implementation plan guided by a strategic focus. OSCAR reduces that ramp-up time with educational resources and provides vetted and repeatable methods for an MBD implementation.

OSCAR combines decades of Action Engineering expertise and lessons learned into a multi-media textbook of sorts. To kickstart an individual or an organization’s MBD journey, it includes asynchronous learning, downloadable resources, and CAD examples available in Creo, NX, and SOLIDWORKS formats.

CAD users can access how-to training and downloadable resources such as the latest edition of Re-Use Your CAD (RUYC). OSCAR enables process improvement champions to make their case to start the MBD journey. We add content regularly and post what’s new. Free trials are available to check out the online platform.

Learn more about what OSCAR is here:

Want to learn more?

In this post, I believe we only touched the tip of the iceberg. There is so much to learn and understand. What would you recommend to a reader of this blog who got interested?

 

RUYC (Re-Use Your CAD)  is an excellent place to start, but if you need more audio-visual, and want to see real-life examples of MBD in action, get a Training subscription of OSCAR to get rooted in the vocabulary and benefits of MBD with a Model-Based Enterprise. Watch the videos multiple times! That’s what they are for. We love to work with European companies and would love to support you with a kickstart coaching package to get started.

What I learned

First of all, I learned that Jennifer is a very pragmatic person. Her company (Action Engineering) and her experience are a perfect pivot point for those who want to learn and understand more about Model-Based Definition. In particular, in the US, given her strong involvement in the American Society of Mechanical Engineers (ASME).

I am still curious if European or Asian counterparts exist to introduce and explain the benefits and usage of Model-Based Definition to their customers.  Feel free to comment.

Next, and an important observation too, is the fact that Jennifer also describes the tension between Model-Based Definition and PLM. Current PLM systems might be too rigid to support end-to-end scenarios, taking benefit of the Model-Based definition.

I have to agree here. PLM Vendors mainly support their own MBD (model-based definition), where the ultimate purpose is to share all product-related information using various models as the main information carriers efficiently.

We have to study and solve a topic in the PLM domain, as I described in my technical highlights from the PLM Road Map & PDT Spring 2021 conference.

There is work to do!

Conclusion

Model-Based Definition is, for me, one of the must-do steps of a company to understand the model-based future. A model-based future sometimes incorporates Model-Based Systems Engineering, a real Digital Thread and one or more Digital Twins (depending on your company’s products).

It is a must-do activity because companies must transform themselves to depend on digital processes and digital continuity of data to remain competitive. Document-driven processes relying on the interpretation of a person are not sustainable.

 

Last week I wrote about the recent PLM Road Map & PDT Spring 2021 conference day 1, focusing mainly on technology. There were also interesting sessions related to exploring future methodologies for a digital enterprise. Now on Day 2, we started with two sessions related to people and methodology, indispensable when discussing PLM topics.

Designing and Keeping Great Teams

This keynote speech from Noshir Contractor, Professor of Behavioral Sciences in the McCormick School of Engineering & Applied Science, intrigued me as the subtitle states: Lessons from Preparing for Mars. What Can PLM Professionals Learn from This?

You might ask yourself, is a PLM implementation as difficult and as complex as a mission to Mars? I hoped, so I followed with great interest Noshir’s presentation.

Noshir started by mentioning that many disruptive technologies have emerged in recent years, like Teams, Slack, Yammer and many more.

The interesting question he asked in the context of PLM is:

As the domain of PLM is all about trying to optimize effective collaboration, this is a fair question

Structural Signatures

Noshir shared with us that it is not the most crucial point to look at people’s individual skills but more about who they know.
Measure who they work with is more important than who they are.

Based on this statement, Noshir showed some network patterns of different types of networks.

Click on the image to see the enlarged picture.

It is clear from these patterns how organizations communicate internally and/or externally. It would be an interesting exercise to perform in a company and to see if the analysis matches the perceived reality.

Noshir’s research was used by NASA to analyze and predict the right teams for a mission to Mars.

Noshir went further by proposing what PLM can learn from teams that are going into space. And here, I was not sure about the parallel. Is a PLM project comparable to a mission to Mars? I hope not! I have always advocated that a PLM implementation is a journey. Still, I never imagined that it could be a journey into the remote unknown.

Noshir explained that they had built tools based on their scientific model to describe and predict how teams could evolve over time. He believes that society can also benefit from these learnings. Many inventions from the past were driven by innovations coming from space programs.

I believe Noshir’s approach related to team analysis is much more critical for organizations with a mission. How do you build multidisciplinary teams?

The proposed methodology is probably best for a holocracy based organization. Holocrazy is an interesting concept for companies to get their employees committed, however, it also demands a type of involvement that not every person can deliver.  For me, coming back to PLM, as a strategy to enable collaboration, the effectiveness of collaboration depends very much on the organizational culture and created structure.

DISRUPTION – EXTINCTION or still EVOLUTION?

We talk a lot about disruption because disruption is a painful process that you do not like to happen to yourself or your company. In the context of this conference’s theme, I discussed the awareness that disruptive technologies will be changing the PLM Value equation.

However, disruptive technologies are not alone sufficient. In PLM, we have to deal with legacy data, legacy processes, legacy organization structures, and often legacy people.

A disruption like the switch from mini-computers to PCs (killed DEC) or from Symbian to iOS (killed Nokia) is therefore not likely to happen that fast. Still, there is a need to take benefit from these new disruptive technologies.

My presentation was focusing on describing the path of evolution and focus areas for the PLM community. Doing nothing means extinction; experimenting and learning towards the future will provide an evolutionary way.

Starting from acknowledging that there is an incompatibility between data produced most of the time now and the data needed in the future, I explained my theme: From Coordinated to Connected. As a PLM community, we should spend more time together in focus groups, conferences on describing and verifying methodology and best practices.

Nigel Shaw (EuroStep) and Mark Williams (Boeing) hinted in this direction during this conference  (see day 1). Erik Herzog (SAAB Aeronautics) brought this topic to last year’s conference (see day 3). Outside this conference, I have comparable touchpoints with Martijn Dullaert when discussing Configuration Management in the future in relation to PLM.

In addition, this decade will probably be the most disruptive decade we have known in humanity due to external forces that push companies to change. Sustainability regulations from governments (the Paris agreement),  the implementation of circular economy concepts combined with the positive and high Total Share Holder return will push companies to adapt themselves more radical than before.

What is clear is that disruptive technologies and concepts, like Industry 4.0, Digital Thread and Digital Twin, can serve a purpose when implemented efficiently, ensuring the business becomes sustainable.

Due to the lack of end-to-end experience, we need focus groups and conferences to share progress and lessons learned. And we do not need to hear the isolated vendor success stories here as a reference, as often they are siloed again and leading to proprietary environments.

You can see my full presentation on SlideShare: DISRUPTION – EXTINCTION or still EVOLUTION?

 

Building a profitable Digital T(win) business

Beatrice Gasser,  Technical, Innovation, and Sustainable Development Director from the Egis group, gave an exciting presentation related to the vision and implementation of digital twins in the construction industry.

The Egis group both serves as a consultancy firm as well as an asset management organization. You can see a wide variety of activities on their website or have a look at their perspectives

Historically the construction industry has been lagging behind having low productivity due to fragmentation, risk aversion and recently, more and more due to the lack of digital talent. In addition, some of the construction companies make their money from claims inside of having a smooth and profitable business model.

Without innovation in the construction industry, companies working the traditional way would lose market share and investor-focused attention, as we can see from the BCG diagram I discussed in my session.

The digital twin of construction is an ideal concept for the future. It can be built in the design phase to align all stakeholders, validate and integrate solutions and simulate the building operational scenarios at almost zero materials cost. Egis estimates that by using a digital twin during construction, the engineering and construction costs of a building can be reduced between 15 and 25 %

More importantly, the digital twin can also be used to first simulate operations and optimize energy consumption. The connected digital twin of an existing building can serve as a new common data environment for future building stakeholders. This could be the asset owner, service companies, and even the regulatory authorities needing to validate the building’s safety and environmental impact.

Beatrice ended with five principles essential to establish a digital twin, i.e

I think the construction industry has a vast potential to disrupt itself. Faster than the traditional manufacturing industries due to their current needs to work in a best-connected manner.

Next, there is almost no legacy data to deal with for these companies. Every new construction or building is a unique project on its own. The key differentiators will be experience and efficient ways of working.

It is about the belief, the guts and the skilled people that can make it work – all for a more efficient and sustainable future.

 

 

Leveraging PLM and Cloud Technology for Market Success

Stan Przybylinski, Vice President of CIMdata, reported their global survey related to the cloud, completed in early 2021.  Also, Stan typified Industry 4.0 as a connected vision and cloud and digital thread as enablers to implementing this vision.

The companies interviewed showed a lot of goodwill to make progress – click on the image to see the details. CIMdata is also working with PLM Vendors to learn and describe better the areas of beneft. I remain curious about who comes with a realization and business case that is future-proof. This will define our new PLM Value Equation.

 

Conclusion

These were two exciting days with enough mentioning of disruptive technologies. Our challenge in the PLM domain will be to give them a purpose. A purpose is likely driven by external factors related to the need for a sustainable future.  Efficiency and effectiveness must come from learning to work in connected environments (digital twin, digital thread, industry 4.0, Model-Based (Systems) Engineering.

Note: You might have seen the image below already – a nice link between sustainability and the mission to Mars

One of my favorite conferences is the PLM Road Map & PDT conference. Probably because in the pre-COVID days, it was the best PLM conference to network with peers focusing on PLM practices, standards, and sustainability topics. Now the conference is virtual, and hopefully, after the pandemic, we will meet again in the conference space to elaborate on our experiences further.

Last year’s fall conference was special because we had three days filled with a generic PLM update and several A&D (Aerospace & Defense) working groups updates, reporting their progress and findings. Sessions related to the Multiview BOM researchGlobal Collaboration, and several aspects of Model-Based practices: Model-Based Definition, Model-Based Engineering & Model-Based Systems engineering.

All topics that I will elaborate on soon. You can refresh your memory through these two links:

This year, it was a two-day conference with approximately 200 attendees discussing how emerging technologies can disrupt the current PLM landscape and reshape the PLM Value Equation. During the first day of the conference, we focused on technology.

On the second day, we looked in addition to the impact new technology has on people and organizations.

Today’s Emerging Trends & Disrupters

Peter Bilello, CIMdata’s President & CEO, kicked off the conference by providing CIMdata observations of the market. An increasing number of technology capabilities, like cloud, additive manufacturing, platforms, digital thread, and digital twin, all with the potential of realizing a connected vision. Meanwhile, companies evolve at their own pace, illustrating that the gap between the leaders and followers becomes bigger and bigger.

Where is your company? Can you afford to be a follower? Is your PLM ready for the future? Probably not, Peter states.

Next, Peter walked us through some technology trends and their applicability for a future PLM, like topological data analytics (TDA), the Graph Database, Low-Code/No-Code platforms, Additive Manufacturing, DevOps, and Agile ways of working during product development. All capabilities should be related to new ways of working and updated individual skills.

I fully agreed with Peter’s final slide – we have to actively rethink and reshape PLM – not by calling it different but by learning, experimenting, and discussing in the field.

Digital Transformation Supporting Army Modernization

An interesting viewpoint related to modern PLM came from Dr. Raj Iyer, Chief Information Officer for IT Reform from the US Army. Rai walked us through some of the US Army’s challenges, and he gave us some fantastic statements to think about. Although an Army cannot be compared with a commercial business, its target remains to be always ahead of the competition and be aware of the competition.

Where we would say “data is the new oil”, Rai Iyer said: “Data is the ammunition of the future fight – as fights will more and more take place in cyberspace.”

The US Army is using a lot of modern technology – as the image below shows. The big difference here with regular businesses is that it is not about ROI but about winning fights.

Also, for the US Army, the cloud becomes the platform of the future. Due to the wide range of assets, the US Army has to manage, the importance of product data standards is evident.  – Rai mentioned their contribution and adherence to the ISO 10303 STEP standard crucial for interoperability. It was an exciting insight into the US Army’s current and future challenges. Their primary mission remains to stay ahead of the competition.

Joining up Engineering Data without losing the M in PLM

Nigel Shaw’s (Eurostep) presentation was somehow philosophical but precisely to the point what is the current dilemma in the PLM domain.  Through an analogy of the internet, explaining that we live in a world of HTTP(s) linking, we create new ways of connecting information. The link becomes an essential artifact in our information model.

Where it is apparent links are crucial for managing engineering data, Nigel pointed out some of the significant challenges of this approach, as you can see from his (compiled) image below.

I will not discuss this topic further here as I am planning to come back to this topic when explaining the challenges of the future of PLM.

As Nigel said, they have a debate with one of their customers to replace the existing PLM tools or enhance the existing PLM tools. The challenge of moving from coordinated information towards connected data is a topic that we as a community should study.

Integration is about more than Model Format.

This was the presentation I have been waiting for. Mark Williams from Boeing had built the story together with Adrian Burton from Airbus. Nigel Shaw, in the previous session, already pointed to the challenge of managing linked information. Mark elaborated further about the model-based approach for system definition.

All content was related to the understanding that we need a  model-based information infrastructure for the future because storing information in documents (the coordinated approach) is no longer viable for complex systems. Mark ‘slide below says it all.

Mark stressed the importance of managing model information in context, and it has become a challenge.

Mark mentioned that 20 years ago, the IDC (International Data Corporation) measured Boeing’s performance and estimated that each employee spent 2 ½ hours per day. In 2018, the IDC estimated that this number has grown to 30 % of the employee’s time and could go up to 50 % when adding the effort of reusing and duplicating data.

The consequence of this would be that a full-service enterprise, having engineering, manufacturing and services connected, probably loses 70 % of its information because they cannot find it—an impressive number asking for “clever” ways to find the correct information in context.

It is not about just a full indexed search of the data, as some technology geeks might think. It is also about describing and standardizing metadata that describes the models. In that context, Mark walked through a list of existing standards, all with their pros and cons, ending up with the recommendation to use the ISO 10303-243 – MoSSEC standard.

MoSSEC standing for Modelling and Simulation information in a collaborative Systems Engineering Context to manage and connect the relationships between models.

MoSSEC and its implication for future digital enterprises are interesting, considering the importance of a model-based future. I am curious how PLM Vendors and tools will support and enable the standard for future interoperability and collaboration.

Additive Manufacturing
– not as simple as paper printing – yet

Andreas Graichen from Siemens Energy closed the day, coming back to the new technologies’ topic: Additive Manufacturing or in common language 3D Printing. Andreas shared their Additive Manufacturing experiences, matching the famous Gartner Hype Cycle. His image shows that real work needs to be done to understand the technology and its use cases after the first excitement of the hype is over.

Material knowledge was one of the important topics to study when applying additive manufacturing. It is probably a new area for most companies to understand the material behaviors and properties in an Additive Manufacturing process.

The ultimate goal for Siemens Energy is to reach an “autonomous” workshop anywhere in the world where gas turbines could order their spare parts by themselves through digital warehouses. It is a grand vision, and Andreas confirmed that the scalability of Additive Manufacturing is still a challenge.

For rapid prototyping or small series of spare parts, Additive Manufacturing might be the right solution. The success of your Additive Manufacturing process depends a lot on how your company’s management has realistic expectations and the budget available to explore this direction.

Conclusion

Day 1 was enjoyable and educational, starting and ending with a focus on disruptive technologies. The middle part related to data the data management concepts needed for a digital enterprise were the most exciting topics to follow up in my opinion.

Next week I will follow up with reviewing day 2 and share my conclusions. The PLM Road Map & PDT Spring 2021 conference confirmed that there is work to do to understand the future (of PLM).

 

Last Friday, we discussed with several members of the PLM Global Green Alliance the book: “How to avoid a Climate Disaster” written by Bill Gates. I was happy to moderate the session between Klaus Brettschneider, Rich McFall, Lionel Grealou, Ilan Madjar and Patrick Hillberg. From the LinkedIn profiles of each of them, you can see we are all active in the domain of PLM. And they have read the book upfront before the discussion.

I think the book addresses climate change in a tangible manner. Bill Gates brings structure into addressing climate changes and encourages you to be active. What you can do as an individual, as a citizen. My only comment to this book would be that as a typical nerd, Bill Gates does not understand so much human behavior, understanding people’s emotions that might lead to non-logical behavior.

When you browse through the book’s reviews, for example, on Goodreads, you see the extreme, rating from 1 to 5. Some people believe that Bill Gates, due to his wealth and ways of living, is not allowed to write this book. Other like the transparent and pragmatic approach discussing the related themes in the book.

Our perspective

Klaus, Rich, Lio, Ilan and Patrick did not have extreme points of view – so don’t watch the recording if you are looking for anxiety. They reviewed How to Avoid a Climate Disaster from their perspective and how it could be relevant for PLM practitioners.  It became a well-balanced dialogue. You can watch or listen to the recording following this link:

Book discussion: How to avoid a climate disaster written by Bill Gates

Note: we will consolidate all content on our PLMGreenAlliances website to ensure nothing is lost – feel free to comment/discuss further.

More on sustainability

If you want to learn more about all sorts of disruption, not only disruption caused by climate change, have a look at the upcoming conference this week: DISRUPTION—the PLM Professionals’ Exploration of Emerging Technologies that Will Reshape the PLM Value Equation.

My contribution will be on day 2, where I combine disruptive technology with the need to become really sustainable in our businesses.

It will be a call for action from our PLM community. In the coming nine years, we have to change our business, become sustainable and use the relevant new technologies. This requires system thinking – will mankind being able to deal with so many different parameters.

Conclusion

Start the dialogue with us, the PLM Global Green Alliance, by watching and reading content from the website. Or become an active member participating in discussion sessions related to any relevant topic for our alliance. More to come at the end of May, you too?

 

 

 

 

 

 

 

 

Last summer, I wrote a series of blog posts grouped by the theme “Learning from the past to understand the future”. These posts took you through the early days of drawings and numbering practices towards what we currently consider the best practice: PLM BOM-centric backbone for product lifecycle information.

You can find an overview and links to these posts on the page Learning from the past.

If you have read these posts, or if you have gone yourself through this journey, you will realize that all steps were more or less done evolutionarily. There were no disruptions. Affordable 3D CAD systems, new internet paradigms (interactive internet),  global connectivity and mobile devices all introduced new capabilities for the mainstream. As described in these posts, the new capabilities sometimes created friction with old practices. Probably the most popular topics are the whole Form-Fit-Function interpretation and the discussion related to meaningful part numbers.

What is changing?

In the last five to ten years, a lot of new technology has come into our lives. The majority of these technologies are related to dealing with data. Digital transformation in the PLM domain means moving from a file-based/document-centric approach to a data-driven approach.

A Bill of Material on the drawing has become an Excel-like table in a PLM system. However, an Excel file is still used to represent a Bill of Material in companies that have not implemented PLM.

Another example, the specification document has become a collection of individual requirements in a system. Each requirement is a data object with its own status and content. The specification becomes a report combining all valid requirement objects.

Related to CAD, the 2D drawing is no longer the deliverable as a document; the 3D CAD model with its annotated views becomes the information carrier for engineering and manufacturing.

And most important of all, traditional PLM methodologies have been based on a mechanical design and release process. Meanwhile, modern products are systems where the majority of capabilities are defined by software. Software has an entirely different configuration and lifecycle approach conflicting with a mechanical approach, which is too rigid for software.

The last two aspects, from 2D drawings to 3D Models and Mechanical products towards Systems (hardware and software), require new data management methods.  In this environment, we need to learn to manage simulation models, behavior models, physics models and 3D models as connected as possible.

I wrote about these changes three years ago:  Model-Based – an introduction, which led to a lot of misunderstanding (too advanced – too hypothetical).

I plan to revisit these topics in the upcoming months again to see what has changed over the past three years.

What will I discuss in the upcoming weeks?

My first focus is on participating and contributing to the upcoming PLM Roadmap  & PDS spring 2021 conference. Here speakers will discuss the need for reshaping the PLM Value Equation due to new emerging technologies. A topic that contributes perfectly to the future of PLM series.

My contribution will focus on the fact that technology alone cannot disrupt the PLM domain. We also have to deal with legacy data and legacy ways of working.

Next, I will discuss with Jennifer Herron from Action Engineering the progress made in Model-Based Definition, which fits best practices for today – a better connection between engineering and manufacturing. We will also discuss why Model-Based Definition is a significant building block required for realizing the concepts of a digital enterprise, Industry 4.0 and digital twins.

Another post will focus on the difference between the digital thread and the digital thread. Yes, it looks like I am writing twice the same words. However, you will see based on its interpretation, one definition is hanging on the past, the other is targeting the future. Again here, the differentiation is crucial if the need for a maintainable Digital Twin is required.

Model-Based Systems Engineering (MBSE) in all its aspects needs to be discussed too. MBSE is crucial for defining complex products. Model-Based Systems Engineering is seen as a discipline to design products. Understanding data management related to MBSE will be the foundation for understanding data management in a Model-Based Enterprise. For example, how to deal with configuration management in the future?

 

Writing Learning from the past was an easy job as explaining with hindsight is so much easier if you have lived it through. I am curious and excited about the outcome of “The Future of PLM”. Writing about the future means you have digested the information coming to you, knowing that nobody has a clear blueprint for the future of PLM.

There are people and organizations are working on this topic more academically, for example read this post from Lionel Grealou related to the Place of PLM in the Digital Future. The challenge is that an academic future might be disrupted by unpredictable events, like COVID, or disruptive technologies combined with an opportunity to succeed. Therefore I believe, it will be a learning journey for all of us where we need to learn to give technology a business purpose. Business first – then technology.

 

No Conclusion

Normally I close my post with a conclusion. At this moment. there is no conclusion as the journey has just started. I look forward to debating and learning with practitioners in the field. Work together on methodology and concepts that work in a digital enterprise. Join me on this journey. I will start sharing my thoughts in the upcoming months

 

 

 

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