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In my last post related to Learning from the past to understand the future, I discussed what happened when 3D CAD became available for the mid-market. In the large automotive or aerospace & defense companies, 3D CAD has been introduced along the path of defining processes and selecting tools. In the mid-market 3D CAD started from the other side, first as a productivity tool, not thinking further to change methodologies or processes.

The approach starting with 3D CAD without changing processes, has created several complexities. Every company that is aiming to move towards a digital future needs to reduce complexity to remain competitive. Now let us focus on the relation between the 3D CAD-structure and a BOM.

The 3D CAD-structure

When building a product in a 3D CAD system, the concept is that you have individual parts designed in 3D.  Every single part has a unique identifier.

If possible, the (file) name would equal the physical part number.

Next, a group of parts could be stored as a subassembly. Such an assembly is sometimes called a phantom assembly, in case they only group together several 3D parts. The usage of this type of assemblies increased CAD productivity. For data management reasons, these assemblies need to have a unique identifier, preferably not with the same numbering scheme for physical part numbers. It would consume part numbers that would never be used during manufacturing.

Note: in the early days of connecting 3D CAD to ERP, there was a considerable debate about which system could generate the part number.

ERP has always been the leading system for parts definition, why change ? And why generate part numbers that might not be used later in production. “Wasting” part numbers was a bad practice as historically, the part number was like a catalog number: 6 to 7 digits.

Next, there is also another group of subassemblies that represent one or more primary components of a product. For example, a pump assembly, that might be the combination of the pump, the motor, and the base frame. This type of assembly appears most of the time high in the CAD-structure. They can be considered as a phantom assembly too, regarding a required identifier for this subassembly.

Finally, there might be parts in the CAD-structure that will not exist in reality as part but need to be created during the manufacturing process. Sheet metal parts are created during the manufacturing process. Cappings, strips and cables shown in the CAD-structure might come from materials that are purchased in standardized sizes (1 meter / 2 meter / 10 meter) and need to be cut during manufacturing. Here the instances in the CAD-structure will have a unique identifier. What type of identifier to use depends on the manufacturing process. It might be a physical part number, as it is a half-fabricate,  or it remains a unique identifier for the CAD-structure only.

The reason I am coming back to these identifiers is that as described before, companies wanted to keep a relation between the part number and the file name.

There was a problem with flexible parts. A rubber hose with a specific length could be shaped differently in an assembly based on its connection. Two different shapes would create two files and therefore break the rule of a part number equals file name. The 3D CAD vendors “solved” this issue by storing configurable views of the same part inside one file and allow the user to select the active view.

Later we will see that management of views inside the 3D CAD model is not a wrong choice. This, contrary to managing different configurations of a part/product inside a single file, which creates complexity in the PLM domain.

In the end, the product became an assembly with several levels of subassemblies. At that time, when I worked a lot with CAD-integrations, the average depth of 3D CAD-structures was 6 to 7 levels deep, with exceptions in both directions.

The entire product CAD-structure is mainly used for a final digital mock-up, to allow engineers to analyze the full product behavior.  One of my favorite YouTube movies is the one from Airbus – seven years ago, they described the power of a full digital mock-up used for the A380.

In ETO-processes, the 3D CAD-structure is unique for a given customer solution – like the A380.

In the case of large assemblies with a lot of parts and subassemblies,  there were situations where the full product could not be resolved anymore. For Airbus a must, for the mid-market not always easy to reach.  Graphics memory, combined with the way graphics were represented, are the major constraint. This performance issue is resolved in the gaming world, however then the 3D representation had no longer the required accuracy or definition.

The Version pop-up problem

Working with a 3D CAD structure created a new problem when designers were sharing parts and assemblies between themselves and suppliers. The central storage of the files required a versioning mechanism, supported by a check-in and check-out mechanism.

Depending on the type of 3D CAD integration, the PDM system generated a new minor revision of the file after check-in again. In this way, there was full traceability of the changes before release. The image below shows an example of how SmarTeam was dealing with minor and major revisions combined with lifecycle stages.

When revising a part, all assemblies that contained the changed part need to be updated too, in case you want to have traceability and preventing others from overwriting your version. Making sure this assembly file points to the right file again. In the cases of a 6-level deep CAD-structure, this has led to a lot of methodology problems on how to deal (or not to deal) with file changes.

In the case of a unique delivery for a customer, the ETO-process, the issue might not be so big. As everything in the 3D CAD-structure is work in progress, you only need to be sure during the release process of the 3D CAD-structure that all parts and assemblies are resolved to the latest version (and verified)

Making changes on an existing product is way more complicated, as assemblies are released, and parts exist in production.  In that case, the Bill of Material is the leading structure to control the versions and the change impact, as we will see.

Note: Most CAD- and PLM-vendors loved to show you their demos, where starting from the CAD-structure, a product gets created (the ETO-process). The reality is that most companies do not start from the CAD-structure, but from an existing Bill of Material. In 2010, I wrote a few posts, discussing the relation between CAD and the BOM:

to explain there is more than a CAD-driven scenario.

The EBOM

In most PDM-systems with CAD-integrations, it is possible to create a Bill of Materials from the 3D CAD-structure. The Bill of Materials will be based on the parts inside the 3D CAD-structure. There is often the option to filter out phantom assemblies.

The structures are not the same. The 3D CAD-structure is instance-based, where the extracted Bill of Materials will summarize the part quantities on the same level.  See the image below. There are four Wheel instances in the CAD structure, in the EBOM-structure, we have only one Wheel reference with quantity 4.

I named the structure on the right the EBOM as the structure represents the Bill of Materials from the engineering point of view. This definition is a little arbitrary, as we will see. In companies that started to develop products based on a conceptual BOM, often, this conceptual BOM was an “early” EBOM that had to be developed further. This EBOM was more representing a logical or modular structure driving the design, instead of an extract from the 3D CAD-structure. In the next post, I will zoom in on these differences. I want to conclude this time with a critical methodology needed to manage the 3D CAD structure changes in relation to an EBOM.

Breaking the rule Drawing ID (Model ID)  = Part ID

Although I have been writing mostly about the 3D CAD structure, I want to remind us that the 3D Model in the mid-market is mainly used for design purposes. The primary delivery for manufacturing or a supplier is still a 2D-drawing for most companies. The 3D Model might be “nice to have” for CAM- or quality usage. Still, in case of a dispute, the 2D Drawing will be leading.

For that reason, in many mid-market companies, there was the following relation below:

In an environment without file versioning through check-in/check-out, this relation was easy to maintain. In the electronic world, every change in the 3D Model (which could be an assembly) triggers a new file version and, therefore, most of the time, a new version of the drawing and the physical part. However, you do not want to have a physical part with many revisions, in particular when this part could be again part of a Bill of Material.

To solve this issue, the Physical Part and the related Drawing/Model should have different lifecycles. The relation between the Physical Part and the Drawing Model should no longer be based on numbers but on a relation in the PDM/PLM-system. One of the main characteristics of a PDM/PLM-system is that it allows users to navigate through relations to find information in context.  For example, solving a Where Used – question is a (few) mouse-click(s) in a PDM/PLM-system.

Click on the image to see the details.

Breaking this one-to-one numbering rule is a must if you want to evolve to an item-centric or data-driven PLM-environment. When to introduce this change and how to implement this new behavior is a methodology exercise, not an implementation of a new tool.

There is a lot to read about this topic as it is related to the Form-Fit-Function-discussion we had earlier this year. A collection of information can be found in these two LinkedIn-post, where the comments are providing the insights:

 

I will not dive deeper into this theme (reached 1700 words ☹) – next time I will zoom in on the EBOM and leave the world of 3D CAD behind (for a while)

 

 

This time a short post (for me) as I am in the middle the series “Learning from the past to understand the future” and currently collecting information for next week’s post. However, recently Rob Ferrone, the original Digital Plumber, pointed me to an interesting post from Scott Taylor, the Data Whisperer.

In code: The Virtual Dutchman discovered the Data Whisperer thanks to the original Digital Plumber.

Scott’s article with the title: “Data Management Hasn’t Failed, but Data Management Storytelling Has” matches precisely the discussion we have in the PLM community.

Please read his article, and just replace the words Data Management by PLM, and it could have been written for our community. In a way, PLM is a specific application of data management, so not a real surprise.

Scott’s conclusions give food for thought in the PLM community:

To win over business stakeholders, Data Management leadership must craft a compelling narrative that builds urgency, reinvigorates enthusiasm, and evangelizes WHY their programs enable the strategic intentions of their enterprise. If the business leaders whose support and engagement you seek do not understand and accept the WHY, they will not care about the HOW. When communicating to executive leadership, skip the technical details, the feature functionality, and the reference architecture and focus on:

  • Establishing an accessible vocabulary
  • Harmonizing to a common voice
  • Illuminating the business vision

When you tell your Data Management story with that perspective, it can end happily ever after.

It all resonates well with what I described in the PLM ROI Myth – it is clear that when people hear the word Myth, they have a bad connotation, same btw for PLM.

The fact that we still need to learn storytelling is because most of us are so much focused on technology and sometimes on discovering the new name for PLM in the future.

Last week I pointed to a survey from the PLMIG (PLM Interest Group) and XLifcycle, inviting you to help to define the future definition of PLM.

You are still welcome here: Towards a digital future: the evolving role of PLM in the future digital world.

Also, I saw a great interview with Martin Eigner on Minerva PLM TV interview by Jennifer Moore. Martin is well known in the PLM world and has done foundational work for our community

. According to Jennifer, he is considered as The Godfather of PLM.  This tittle fits nicely in today’s post. Those who have seen his presentations in recent years will remember Martin is talking about SysLM (System Lifecycle Management) as the future for PLM.

It is an interesting recording to watch – click on the image above to see it. Martin explains nicely why we often do not get the positive feedback from PLM implementations – starting at minute 13 for those who cannot wait.

In the interview, you will discover we often talk too much about our discipline capabilities where the real discussion should be talking business. Strategy and objectives are discussed and decided at the management level of a company. By using storytelling, we can connect to these business objectives.

The end result will be more likely that a company understands why to invest significantly in PLM as now PLM is part of its competitiveness and future continuity.

Conclusion

I shared links to two interesting posts from the last weeks. Studying them will help you to create a broader view. We have to learn to tell the right story. People do not want PLM – they have personal objectives. Companies have business objectives, and they might lead to the need for a new and changing PLM. Connecting to the management in an organization, therefore, is crucial.

Next week again more about learning from the past to understand the future

To understand our legacy in the PLM-domain, what are the types of practices we created, I started this series of posts: Learning from the past to understand the future. My first post (The evolution of the BOM) focused on the disconnected world between engineering  – generation of drawings as a  deliverable – and execution MRP/ERP – the first serious IT-systems in a company.

At that time, due to minimal connectivity, small and medium-sized companies had, most of the time, an informal connection between engineering and manufacturing. I remember a statement at that time, PLM was just introduced. One person during a conference claimed:

“You guys make our lives so difficult with your systems. If we have a problem, we gather around the machine, and we fix it.”

PLM started at large enterprises

Of course, large enterprises could not afford such behavior as they operate globally. The leading enterprises for PDM/PLM were the Aerospace & Defense and Automotive companies. They needed consistent processes and formal ways of working to guarantee quality output.

In that sense, I was happy with the reaction from Jean-Jacques Urban-Galindo, who shared in the LinkedIn comments a reference to a relevant chapter of John Stark’s PLM book. In the pdf describing the evolution of CAD / PDM / PLM at PSA. Jean-Jacques was responsible at that time for Responsible for the re-engineering of the Product & Process Engineering processes using digital tools (CAD/CAM, DMU, and more).

Read the PSA story here: PLM at GROUPE PSA. It describes nicely where 3D CAD and EBOM are coming in.  In large enterprise like PSA, the need for tools are driven by the processes. When you read it to the end, you will also see the need for a design and a manufacturing view. A topic I will touch in future posts too.

The introduction of 3D CAD in the mid-market

Where large automotive and aerospace companies already invested in (expensive) 3D CAD hard and software, for the majority of the midsize companies, the switch from 2D CAD (AutoCAD mainly) towards 3D CAD (SolidWorks, Solid Edge, Inventor) started at the end of the 20th century.

It was the time that Microsoft NT became a serious platform beside the existing mainframe and mini-computer based CAD-systems. The switch to PCs went so fast that the disruption from DEC (Digital Equipment Company) is one of the cases discussed by Clayton Christensen in his groundbreaking book: The Innovator’s dilemma

3D CAD introduced a lot of new capabilities, like DMU (Digital Mock-Up), for clash detection, and above all, a better understanding of a product’s behavior. The introduction of 3D CAD introduced a new set of challenges to be resolved.

For example, the concept of reusing 3D CAD parts. Mid-market companies, most of the time, are buying productivity tools. Can I design my product faster and with higher quality in 3D instead of using only the 2D definitions?

Mid-market companies usually do not redesign their business processes – no people available for strategy – the pain of lack of strategy is felt in a different way compared to large enterprises—a crucial differentiator for the future of PLM.

Reuse of (3D) CAD parts / Assemblies

In the 2D CAD world, there was not so much reuse of CAD parts. Standard parts were saved in libraries or generated on demand by parametric libraries. Now with 3D CAD, designers might spend more time to define the part. The benefits come from the reuse of small sub-assemblies (modules) into a larger product assembly. Something not relevant in the 2D CAD world.

As every 3D CAD part had to have a file name, it became difficult to manage the file names without a system. How do you secure that the file with name Part01.xxx is unique? Another designer might also create an assembly, where the 3D CAD tool would suggest Part01.xxx as the name. And what about revisions? Do you store them in the filename, and how do you know you have the correct and latest version of the file?

Companies had already part naming rules for drawings, often related to the part’s usage similar to “intelligent” numbers I mentioned in my previous post.

With 3D CAD it became a little more complicated as now in electronic formats, companies wanted to maintain the relation:

Drawing ID = Part ID = File Name

The need for a PDM-system,

If you look to the image on the left, which I found in one of my old SmarTeam files, there is a part number combined with additional flags A-A-C, which also have meaning (I don’t know ☹ ) and a description.

 

The purpose of these meaningful flags was to maintain the current ways of working. Without a PDM-system, parts of the assembly could be shared with an OEM or a supplier. File-based 3D CAD without using a PDM-system was not a problem for small and medium enterprises.

The 3D CAD-system maintained the relations in the assembly files, including relations to the 2D Drawings. Despite the introduction of 3D CAD, the 2D Drawing remained the deliverable the rest of the company or supply chain, was waiting for. Preferably a drawing containing a parts list and balloon numbers, the same as it has been done before.  Why would you need a PDM-system?

PDM for traceability and reuse

If you were working in your 3D CAD-system for a single product, or on individual projects for OEMs, there was no significant benefit for a PDM-system. All deliveries needed for the engineering department were in the 3D CAD environment. Assembly files and drawing files are already like small databases, containing references to the source files of the part (image above).

A PDM-system at this stage could help you build traceability and prevent people from overwriting files. The ROI for this part only depends on the cost and risks of making mistakes.

However, when companies started to reuse parts or subassemblies, there was a need for a system that could manage the 3D models separately. This had an impact on the design methodology.

Now parts could be used in various products. How do you discover parts for reuse, and how do you know you have the last released version.  For sure their naming cannot be related anymore to a single product or project (a practice still used a lot)

This is where PDM-systems came in. Using additional attributes per file combined with relations between parts,  allowing companies to structure and deliver more details related to a part. A detailed description for internal usage, a part type (classification), and the part material were commonly used attributes. And not to forget the status and revision.

For reuse, it was important that the creators of content had a strategy to define a part for future reuse or discovery. Engineerings were not used to provide such services, filling in data in a PDM-system was seen as an overhead – bureaucracy.

As they were measured on the number of drawings they produced, why do extra work with no immediate benefits?

The best compromise was to have the designer fill in properties in the CAD-file when creating a part. Using the CAD-integration with the PDM-system could be used to fill attributes in the PDM-system.

This “beautiful” simple concept lead later to a lot of complexity.

Is the CAD-model the source of data, meaning designers should always start from CAD when designing a product. If someone added or modified data in the PDM-system, should we open the CAD-file to update some properties? Changing a file means it is a new version. What happens if the CAD-file is released, and I update some connected attributes in PDM?

To summarize this topic. Companies have missed the opportunity here to implement data governance. However, none of the silos (manufacturing preparation, service) recognized the need. Implementing new tools (3D CAD and PDM) did not affect the company’s way of working.

Instead of people, processes, tools, the only focus was on new tools and satisfying the people withing the same process.

Of course, when introducing PDM, which happened for mid-market companies at the beginning of this century, there was no PLM vision. Talking about lifecycle support was a waste of time for management. As we will discover in the future posts, large enterprises and small and medium enterprises have the same PLM needs. However, there is already a fundamentally different starting point. Where large enterprises are analyzing and designing business processes, the small and medium enterprises are buying tools to improve the current ways of working

The Future?

Although we have many steps to take in the upcoming posts, I want to raise your attention to an initiative from the PLM Interest Group together with Xlifecycle.com. The discussion is about what will be PLM’s role in digital transformation.

As you might have noticed, there are people saying the word PLM is no longer covering the right context, and all kinds of alternatives have been suggested. I recommend giving your opinion without my personal guidance. Feel free to answer the questionnaire, and we will be all looking forward to the results.

Find the survey here: Towards a digital future: the evolving role of PLM in the future digital world

 

Conclusion

We are going slow. Discovering here in this post the split in strategy between large enterprises (process focus) and small and medium enterprises (tool focus) when introducing 3D CAD. This different focus, at this time for PDM, is one of the reasons why vendors are creating functions and features that require methodology solving – however, who will provide the methodology.

Next time more on 3D CAD structures and EBOM

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 post is based on a mix of interactions I had the last two weeks in my network, mainly on LinkedIn.  First, I enjoyed the discussion that started around Yoann Maingon post: Thoughts about PLM Business models. Yoann is quite seasoned in PLM, as you can see from his LinkedIn profile, and we have had interesting discussions in the past, and recently about a new PLM-system, he is developing Ganister PLM, based on a flexible Graph database.

Perhaps in that context, Yoann was exploring the various business models. Do you pay for the software (and maintenance), do you pay through subscription, what about a modular approach or a full license for all the functionality? All these questions made me think about the various business models that I encountered and how hard it is for a customer to choose the optimal solution.  And is the space for a new type of PLM? Is there space for free PLM? Some of my thoughts here:

PLM vendors need to be profitable

One of the most essential points to consider is that whatever PLM solution you are aiming to buy, make sure that your PLM vendor has a profitable business model. As once you started with a PLM solution, it is your company’s IP that will be stored in this environment, and you do not want to change every few years your PLM system. Switching PLM systems would be affordable if the PLM system would store their data in a standard format – I will share a more in-depth link under PLM and standards.

For the moment, you cannot state PLM vendors endorse standards. None of the real PLM vendors have a standardized data model, perhaps closest to standards are Eurostep, who have based that ShareAspace solution on top of the PLCS (ISO 10303) standard. However, ShareAspace is more positioned as a type of middleware, connecting between OEMs/Owner/Operators and their suppliers to benefit for standardized connectivity.

Coming back to the statement, PLM Vendors need to be profitable to provide a guarantee for the future of your company’s data is the first step. The major PLM Vendors are now profitable as during a consolidation phase starting 15 years ago, a lot of non-profitable PLM Vendors disappeared. Matrix One, Agile, Eigner & Partner PLM are the best-known companies that were bought for either their technology or market share. In that context, you might also look at OnShape.

Would they be profitable as a separate company, or would investors give up? To survive, you need to be profitable, so giving software away for free is not a good sign (see the software for free paragraph) as a company needs continuity.

PLM startups

In the past 10 years, I have seen and evaluated several new PLM companies. All of them did not really change the PLM paradigm, most of them were still focusing on being an engineering collaboration tools. Several of these companies have in their visionary statement that they are going to be the “Excel killer.” We all know Excel has the best user interface and capabilities to manipulate a collection of metadata.

Very popular is the BOM in Excel, extracted from the CAD-system (no need for an “expensive” PDM or PLM) or BOM used to share with suppliers and stakeholders (ERP is too rigid, purchasing does not work with PDM).

The challenge I see here is that these startups do not bring real new value. The cost of manipulating Excels is a hidden cost, and companies relying on Excel communication are the type of companies that do not have a strategic point of view. This is typical for Small and Medium businesses where execution (“let’s do it”) gets all the attention.

PLM startups often collect investor’s money because they promise to kill Excel, but is Excel the real problem? Modern PLM is about data sharing, which is an attitude change, not necessarily a technology change from Excel tables to (cloud) shared tables. However, will one of these “new Excel killers” PLMs be disruptive? I don’t think so.

PLM disruption?

A week ago, I read an interview with Clayton Christensen (thanks Hakan Karden), which I shared on LinkedIn a week ago. Clayton Christensen is the father of the Disruptive Innovation theory, and I have cited him several times in my blogs. His theory is, in my opinion, fundamental to understand how traditional businesses can be disrupted. The interview took place shortly before he died at the age of 67. He died due to complications caused by leukemia.

A favorite part of this interview is, where he restates what is really Disruptive Innovation as we often talk about disruption without understanding the context, just echoing other people:

Christensen: Disruptive innovation describes a process by which a product or service powered by a technology enabler initially takes root in simple applications at the low end of a market — typically by being less expensive and more accessible — and then relentlessly moves upmarket, eventually displacing established competitors. Disruptive innovations are not breakthrough innovations or “ambitious upstarts” that dramatically alter how business is done but, rather, consist of products and services that are simple, accessible, and affordable. These products and services often appear modest at their outset but over time have the potential to transform an industry.

Many of the PLM startups dream and position themselves as the new disruptor.  Will they succeed? I do not believe so if they only focus on replacing Excel, there is a different paradigm needed. Voice control and analysis perhaps (“Hey PLM if I change Part XYZ what will be affected”)?

This would be disruptive and open new options. I think PLM startups should focus here if they want my investment money.

PLM for free?

There are some voices that PLM should be free in an analogy to software management and collaboration tools. There are so many open-source software management tools, why not using them for PLM? I think there are two issues here:

  • PLM data is not like software data. A lot of PLM data is based on design models (3D CAD / Simulation), which is different from software. Designs are often not that modular as software for various reasons. Companies want to be modular in their products, but do they have the time and resources to reinvent their existing product. For software, these costs are so much lower as it is only a brain exercise. For hardware, the impact is significant. Bringing me to the second point.
  • The cost of change for hardware is entirely different compared to software. Changing software does not have an impact on existing stock or suppliers and, therefore, can be implemented once tested for its purpose. A hardware change impacts the existing production process. First, use the old parts before introducing the change, or do we accept the (costs) of scrap. Is our supply chain, or are our production tools ready to deliver continuity for the new version? Hardware changes are costly, and you want to avoid them. Software changes are cheap, therefore design your products to be configurable based on software (For example Tesla’s software controlling the features to be allowed)

Now imagine, with enough funding, you could provide a PLM for free.  Because of ease of deployment, this would be very likely a cloud offering, easy and scalable. However, all your IP is in that cloud too, and let’s imagine that the cloud is safer than on-premise, so it does not matter in which country your data is hosted (does it ?).

Next, the “free” PLM provider starts asking a small service fee after five years, as the promised ROI on the model hasn’t delivered enough value for the shareholders, they become anxious. Of course, you do not like to pay the fee. However, where is your data, and what happens when you do not pay?

If the PLM provider switches you off, you are without your IP. If you ask the PLM provider to provide your data, what will you get? A blob of XML-files, anything you can use?

In general, this is a challenge for all cloud solutions.

  • What if you want to stop your subscription?
  • What is the allowed Exit-strategy?

Here I believe customers should ask for clarity, and perhaps these questions will lead to a renewed understanding that we need standards.

PLM and standards

We had a vivid discussion in the blogging community in September last year. You can read more related to this topic in my post: PLM and the need for standards which describes the aspects of lock-in and needs for openness.

Finally, a remark related to the PLM-acronym. Another interesting discussion started around Joe Barkai’s post: Why I do not do PLM . Read the comments and the various viewpoint on PLM here. It is clear that the word PLM unites us all; however, the interpretation is different.

If someone in the street asks me what is your profession, I never mention I do PLM. I say: “I assist mainly manufacturing companies in redesigning their business processes using best practices and modern digital technologies”. The focus is on the business value, not on the ultimate definition of PLM

Conclusion

There are many business aspects related to PLM to consider. Yoann Maingon’s post started the thinking process, and we ended up with the PLM-definition. It all illustrates that being involved in PLM is never a boring journey. I am curious to learn about your journey and where we meet.

At the beginning of this week, I was attending the 9th edition of the PI conference in London. Where it started as a popular conference with 300 – 400 attendees at its best, we were now back to a smaller number of approximately 100 attendees.

It illustrates that PLM as a standalone topic is no longer attracts a broad audience as Marketkey (the organization of the conference) confirms. The intention is that future conferences will be focusing on the broader scope of PLM, where business transformation will be one of the main streams.

In this post, I will share my highlights of the conference, knowing that other sessions might have been valuable too, but I had to make a choice.

It is about people

Armin Prommersberger, CTO from DIRAC and the chairman of the conference, made a great point: “What we will discuss in the upcoming two days, it is all about people not about technology.”

I am not sure if this opening has influenced the mood of the conference, as when I look back to what was the central theme: It is all about how we deal with people when explaining, implementing and justifying PLM.

AI at the Forefront of a Digital Transformation

Muhannad Alomari from R2 Data Labs as a separate unit within Rolls Royce to explore and provide data innovation started with his keynote speech sharing the AI initiatives within his team.

He talked about several projects where AI will become crucial.

For example, the EHM program related to engine behavior. How to detect anomalies, how to establish predictive maintenance and maximize the time an airplane engine is in operation. Interesting to mention is that Muhannad explained that most simulation models are based on simplified simulation models, not accurate enough to discover anomalies.

Modeling in the PLM world with feedback from reality

Machine learning and feedback loops are crucial to optimize the models both for the discovery of irregularities and, of course, to improve understanding of the engine behavior and predict maintenance. Currently, maintenance is defined based on the worst-case scenario for the engine, which in reality, of course, will not be the case for most engines. There is a lot (millions) to gain here for a company.

Interesting to mention is that Muhannad gave a realistic view of the current status of Artificial Intelligence (AI). AI is currently still dumb – it is a set of algorithms that need to be adapted whenever new patterns are discovered. Deep learning is still not there – currently, we still need human beings for that.

This was in contrast with the session from Kalypso later with the title: Supercharge your PLM with advanced analytics. It was a typical example of where a realistic story (R2 Data Labs) shows such a big difference with what is sold by PLM vendors or implementers. Kalypso introduced Product Lifecycle Intelligence (PLI) – you can see the dream on the left (click on the image to enlarge).

Combine PLM with Analytics, and you have Intelligence.  My main comment is, knowing from the field the first three phases in most companies have a lack of data quality and consistency. Therefore any “Intelligence” probably will be based on unreliable sources. Not an issue if you are working in the domain of politics, however when it comes to direct cost and quality implications, it can be a significant risk. We still have a way to go before we have a reliable PLM data backbone for analytics.

 

Keeping PLM Momentum after a Successful Campaign

Susanna Mäentausta from Kemira in Finland gave an exciting update of their PLM project. Where in 2019, she shared with us their PLM roadmap (see my 2019 post: The weekend after PI PLMx London 2019); this time, Susanna shared with us how they are keeping the PLM momentum.

Often PLM implementations are started based on a hypothetical business case (I talked about this in my post The PLM ROI Myth). But then, when you implement PLM, you need to take care you provide proof points to motivate the management. And this is exactly what the PLM team in Kemira has been doing. Often management believes that after the first investment, the project is done (“We bought the software – so we are done”) however the business and process change that will deliver the value is not reported.

Susanna shared with us how they defined measurable KPIs for two reasons.  First, to motivate the management that there are business progress and benefits, however, it is a journey. And secondary the facts are used to kill the legends that “Before PLM we were much faster or efficient.” These types of legends are often expressed loudly by persons who consider PLM as an overhead (killing their freedom) instead of a way to be more efficient in business. In the end, for a company, the business is more important than the person’s belief.

On the question for Susanna, what she would have done better with hindsight, she answered: “Communicate, communicate, communicate.” A response I fully support as often PLM teams are too busy completing their day-to-day work, that there is no spare time for communication. Crucial to achieving a business change.

My agreement: PLM needs facts based during implementation and support combined with the understanding we are dealing with people and their emotions too. Both need full attention.

Acceleration Digitalization at Stora Enso

Samuli Savo, Chief Digital Officer at Stora Enso, explained the principles of innovation, related to digitalization at his company. Stora Enso, a Swedish/Finish company, historically one of the largest forestry companies in the world as well as one of the most significant paper and packaging producers, is working on a transformation to become the renewable materials company. For me, he made two vital points on how Stora Enso’s digitalization’s journey is organized.

He pleads for experimentation funded by corporate as in the experimental stage, as it does not make sense to have a business case. First DO and then ANALYZE, where many companies have to policy first to ANALYZE and then DO, killing innovative thinking.

The second point was the active process to challenge startups to solve business challenges they foresee and, combined with a governance process for startups, allow these companies to be supported and become embedded within member companies of the Combient Foundry, like Stora Enso. By doing such in a structured way, the outcome must lead to innovation.

I was thinking about the hybrid enterprise model that I have been explaining in the past. Great story.

Cyber-security and Future Mobility

Out of interest, I followed the session from Madeline Cheah, Cybersecurity Innovation Lead at HORIBA MIRA. She gave an excellent and well-structured overview. Madeline leads the cybersecurity research program. Part of this job is investigating ways to prevent vehicles from being attacked.  In particular, when it comes to connected and autonomous vehicles. How to keep them secure.

She discussed the known gaps are and the cybersecurity implications of future mobility so extensive that I even doubted will there ever be an autonomous vehicle on the road. So much to define and explore. She looked at it from the perspective of the Internet of Everything, where Everything is divided into Things, Data, Processes, and People. Still, a lot of work to do, see image below

Good Times Ahead: Delay Mitigation Through a Plan for Every Part

Ian Quest, director at Quick Release, gave an overview of what their company aims to be. You could translate it as the plumbers of the automotive industry Where in the ideal world information should be flowing from design to release, there are many bottlenecks, leakages, hiccups that need to be resolved as the image shows.

Where their customers often do not have the time and expertise to fix these issues, Quick Release brings in various skillsets and common sense. For example, how to deal with the Bill of Materials, Configuration Management, and many other areas that you need to address with methodology first instead of (vendor-based) technology. I believe there is a significant need for this type of company in the PLM-domain.

The second part, presented by Nick Solly, with a focus on their QRonos tool, was perhaps a little too much a focus on the capabilities of the tool. Ian Quest, in his introduction,  already made the correct statement:

The QRonos tool, which is more or less a reporting tool, illustrates again that when people care about reliable data (planning, tasks, parts, deliverables, …..), you can improve your business significantly by creating visibility to delays or bottlenecks. The value lies in measurable activities and from there, learn to predict or enhance – see R2 Labs, Kemira and the PLI dream.

Conclusion

It is clear that a typical PLM conference is no longer a technology festival – it is about people. People are trying to change or improve their business. Trying to learn from each other, knowing that the technical concepts and technology are there.

I am looking forward to the upcoming PI events where this change will become more apparent.

 

In my previous post, I shared my observations from the past 10 years related to PLM. It was about globalization and digitization becoming part of our daily business. In the domain of PLM, the coordinated approach has become the most common practice.

Now let’s look at the challenges for the upcoming decade, as to my opinion, the next decade is going to be decisive for people, companies and even our current ways of living. So let’s start with the challenges from easy to difficult

Challenge 1: Connected PLM

Implementing an end-to-end digital strategy, including PLM, is probably business-wise the biggest challenge. I described the future vision for PLM to enable the digital twin –How PLM, ALM, and BIM converge thanks to the digital twin.

Initially, we will implement a digital twin for capital-intensive assets, like satellites, airplanes, turbines, buildings, plants, and even our own Earth – the most valuable asset we have. To have an efficient digital continuity of information, information needs to be stored in connected models with shared parameters. Any conversion from format A to format B will block the actual data to be used in another context – therefore, standards are crucial. When I described the connected enterprise, this is the ultimate goal to be reached in 10 (or more) years. It will be data-driven and model-based

Getting to connected PLM will not be the next step in evolution. It will be disruptive for organizations to maintain and optimize the past (coordinated) and meanwhile develop and learn the future (connected). Have a look at my presentation at PLM Roadmap PDT conference to understand the dual approach needed to maintain “old” PLM and work on the future.

Interesting also my blog buddy Oleg Shilovitsky looked back on the past decade (here) and looked forward to 2030 (here). Oleg looks at these topics from a different perspective; however, I think we agree on the future quoting his conclusion:

PLM 2030 is a giant online environment connecting people, companies, and services together in a big network. It might sound like a super dream. But let me give you an idea of why I think it is possible. We live in a world of connected information today.

 

Challenge 2: Generation change

At this moment, large organizations are mostly organized and managed by hierarchical silos, e.g., the marketing department, the R&D department, Manufacturing, Service, Customer Relations, and potentially more.

Each of these silos has its P&L (Profit & Loss) targets and is optimizing itself accordingly. Depending on the size of the company, there will be various layers of middle management. Your level in the organization depends most of the time on your years of experience and visibility.

The result of this type of organization is the lack of “horizontal flow” crucial for a connected enterprise. Besides, the top of the organization is currently full of people educated and thinking linear/analog, not fully understanding the full impact of digital transformation for their organization. So when will the change start?

In particular, in modern manufacturing organizations, the middle management needs to transform and dissolve as empowered multidisciplinary teams will do the job. I wrote about this challenge last year: The Middle Management dilemma. And as mentioned by several others – It will be: Transform or Die for traditionally managed companies.

The good news is that the old generation is retiring in the upcoming decade, creating space for digital natives. To make it a smooth transition, the experts currently working in the silos will be missed for their experience – they should start coaching the young generation now.

 

Challenge 3: Sustainability of the planet.

The biggest challenge for the upcoming decade will be adapting our lifestyles/products to create a sustainable planet for the future. While mainly the US and Western Europe have been building a society based on unlimited growth, the effect of this lifestyle has become visible to the world. We consume with the only limit of money and create waste and landfill (plastics and more) form which the earth will not recover if we continue in this way. When I say “we,” I mean the group of fortunate people that grew up in a wealthy society. If you want to discover how blessed you are (or not), just have a look at the global rich list to determine your position.

Now thanks to globalization, other countries start to develop their economies too and become wealthy enough to replicate the US/European lifestyle. We are overconsuming the natural resources this earth has, and we drop them as waste – preferably not in our backyard but either in the ocean or at fewer wealth countries.

We have to start thinking circular and PLM can play a role in this. From linear to circular.

In my blog post related to PLM Roadmap/PDT Europe – day 1,  I described Graham Aid’s (Ragn-Sells) session:

Enabling the Circular Economy for Long Term Prosperity.

He mentioned several examples where traditional thinking just leads to more waste, instead of starting from the beginning with a sustainable model to bring products to the market.

Combined with our lifestyle, there is a debate on how the carbon dioxide we produce influences the climate and the atmosphere. I am not a scientist, but I believe in science and not in conspiracies. So there is a problem. In 1970 when scientists discovered the effect of CFK on the Ozone-layer of the atmosphere, we ultimately “fixed” the issue. That time without social media we still trusted scientists – read more about it here: The Ozone hole

I believe mankind will be intelligent enough to “fix” the upcoming climate issues if we trust in science and act based on science. If we depend on politicians and lobbyists, we will see crazy measures that make no sense, for example, the concept of “biofuel.” We need to use our scientific brains to address sustainability for the future of our (single) earth.

Therefore, together with Rich McFall (the initiator), Oleg Shilovitsky, and Bjorn Fidjeland (PLM-peers), we launched the PLM Green Alliance, where we will try to focus on sharing ideas, discussion related to PLM and PLM-related technologies to create a network of innovative companies/ideas. We are in the early stages of this initiative and are looking for ways to make it an active alliance. Insights, stories, and support are welcome. More to come this year (and decade).

 

Challenge 4: The Human brain

The biggest challenge for the upcoming decade will be the human brain. Even though we believe we are rational, it is mainly our primitive brain that drives our decisions. Thinking Fast and Slow from Daniel Kahneman is a must-read in this area. Or Predictably Irrational: The Hidden Forces that shape our decisions.  Note: these books are “old” books from years ago. However, due to globalization and social connectivity, they have become actual.

Our brain does not like to waste energy. If we see the information that confirms our way of thinking, we do not look further. Social media like Facebook are using their algorithms to help you to “discover” even more information that you like. Social media do not care about facts; they care about clicks for advertisers. Of course, controversial headers or pictures get the right attention. Facts are no longer relevant, and we will see this phenomenon probably this year again in the US presidential elections.

The challenge for implementing PLM and acting against human-influenced Climate Change is that we have to use our “thinking slow” mode combined with a general trust in science. I recommend reading Enlightenment now from Steven Pinker. I respect Steven Pinker for the many books I have read from him in the past. Enlightenment Now is perhaps a challenging book to complete. However, it illustrates that a lot of the pessimistic thinking of our time has no fundamental grounds. As a global society, we have been making a lot of progress in the past century. You would not go back to the past anymore.

Back to PLM.

PLM is not a “wonder tool/concept,” and its success is mainly depending on a long-term vision, organizational change, culture, and then the tools. It is not a surprise that it is hard for our brains to decide on a roadmap for PLM. In 2015 I wrote about the similarity of PLM and acting against Climate Change  – read it here: PLM and Global Warming

In the upcoming PI PLMx London conference, I will lead a Think Tank session related to Getting PLM on the Executive’s agenda. Getting PLM on an executive agenda is about connecting to the brain and not about a hypothetical business case only.  Even at exec level, decisions are made by “gut feeling” – the way the human brain decides. See you in London or more about this topic in a month.

Conclusion

The next decade will have enormous challenges – more than in the past decades. These challenges are caused by our lifestyles AND the effects of digitization. Understanding and realizing our biases caused by our brains is crucial.  There is no black and white truth (single version of the truth) in our complex society.

I encourage you to keep the dialogue open and to avoid to live in a silo.

Last week I shared the first impression from my favorite conference, the PLM Roadmap / PDT conference organized by CIMdata and Eurostep. You can read some of the highlights here: The weekend after PLM Roadmap / PDT 2019 Day 1.

Click on the logo to see what was the full agenda. In this post, I will focus on some of the highlights of day 2.

Chernobyl, The megaproject with the New Arch

Christophe Portenseigne from the Bouygues Construction Group shared with us his personal story about this megaproject, called Novarka. 33 years ago, reactor #4 exploded and has been confined with an object shelter within six months in 1986. This was done with heroic speed, and it was anticipated that the shelter would only last for 20 – 30 years.  You can read about this project here.

The Novarka project was about creating a shelter for Confinement of the radioactive dust and protection of the existing against external actions (wind, water, snow…) for the next 100 years!

And even necessary, the inside the arch would be a plant where people could work safely on the process of decommissioning the existing contaminated structures. You can read about the full project here at the Novarka website.

What impressed me the most the personal stories of Christophe taking us through some of the massive challenges that need to be solved with innovative thinking. High complexity, a vast number of requirements, many parties, stakeholders involved closed in June 2019. As Christophe mentioned, this was a project to be proud of as it creates a kind of optimism that no matter how big the challenges are, with human ingenuity and effort, we can solve them.

A Model Factory for the Efficient Development of High Performing Vehicles

Eric Landel, expert leader for Numerical Modeling and Simulation at Renault, gave us an interesting insight into an aspect of digitalization that has become very valuable, the connection between design and simulation to develop products, in this case, the Renault CLIO V, as much as possible in the virtual world. You need excellent simulation models to match future reality (and tests). The target of simulation was to get the highest safety test results in the Europe NCAP rating – 5 stars.

The Renault modeling factory implemented a digital loop (below) to ensure that at the end of the design/simulation, a robust design would exist.  Eric mentioned that for the Clio, they did not build a prototype anymore. The first physical tests were done on cars coming from the plant. Despite the investment in simulation software, a considerable saving in crash part over cost before TGA (Tooling Go Ahead).

Combined with the savings, the process has been much faster than before. From 10 weeks for a simulation loop towards 4 weeks. The next target is to reduce this time to 1 week. A real example of digitization and a connected model-based approach.

From virtual prototype to hybrid twin

ESI – their sponsor session Evolving from Virtual Prototype Testing to Hybrid Twin: Challenges & Benefits was an excellent complementary session to the presentation from Renault

PLM, MBSE and Supply chain – challenges and opportunities

Nigel Shaw’s presentation was one of my favorite presentations, as Nigel addressed the same topics that I have been discussing in the past years. His focus was on collaboration between the OEM and supplier with the various aspects of requirements management, configuration management, simulation and the different speeds of PLM (focus on mechanical) and ALM (focus on software)

How can such activities work in a digitally-connected environment instead of a document-based approach?  Nigel looked into the various aspects of existing standards in their domains and their future. There is a direction to MBE (Model-Based Everything) but still topics to consider. See below:

I agree with Nigel – the future is model-based – when will be the issue for the market leaders.

The ISO AP239 ed3 Project and the Through Life Cycle Interoperability Challenge

Yves Baudier from AFNET,  a reference association in France regarding industry digitation, digital threads, and digital processes for Extended Enterprise/Supply chain. All about a digital future and Yves presentation was about the interoperability challenge, mentioning three of my favorite points to consider:

  • Data becoming more and more a strategic asset – as digitalization of Industry and Services, new services enabled by data analytics
  • All engineering domains (from concept design to system end of life) need to develop a data-centric approach (not only model-centric)– An opportunity for PLM to cover the full life-cycle
  • Effectivity and efficiency of data interoperability through the life-cycle is now an essential industry requirement – e.g., “virtual product” and “digital twin” concepts

All the points are crucial for the domain of PLM.

In that context, Yves discussed the evolution of the ISO 10303-239 standard, also known as PLCS. The target with ISO AP239 ed3 is to become the standard for Aerospace and Defense for the full product lifecycle and through this convergence being able to push IT/PLM Vendors to comply – crucial for a digital enterprise

Time for the construction / civil industry

Christophe Castaing, director of digital engineering at Egis, shared with us their solution framework to manage large infrastructure projects by focusing on both the Asset Information (BIM-based) and the collaborative processes between the stakeholders, all based on standards. It was a broad and in-depth presentation – too much to share in a blog post. To conclude (see also Christophe’s slide below) in the construction industry more and more, there is the desire to have a digital twin of a given asset (building/construction), creating the need for standard information models.

Pierre Benning, IT director from Bouygues Public Works gave us an update on the MINnD project. MINnD standing for Modeling INteroperable INformation for sustainable INfrastructures in xD, a French research project dedicated to the deployment of BIM and digital engineering in the infrastructure sector. Where BIM has been starting from the construction industry, there is a need for a similar, digital modeling approach for civil infrastructure. In 2014 Christophe Castaing already reported the activities of the MINnD project – see The weekend after PDT 2014. Now Pierre was updating us on what are the activities for MINnD Season 2 – see below:

As you can see, again, the interest in digital twins for operations and maintenance. Perhaps here, the civil infrastructure industry will be faster than traditional industries because of its enormous value. BIM and GIS reconciliation is a precise topic as many civil infrastructures have a GIS aspect – Road/Train infrastructure for example. The third bullet is evident to me. With digitization and the integration of contractors and suppliers, BIM and PLM will be more-and-more conceptual alike. The big difference still at this moment: BIM has one standard framework where PLM-standards are still not in a consolidation stage.

Digital Transformation for PLM is not an evolution

If you have been following my blog in the past two years, you may have noticed that I am exploring ways to solve the transition from traditional, coordinated PLM processes towards future, connected PLM. In this session, I shared with the audience that digital transformation is disruptive for PLM and requires thinking in two modes.

Thinking in two modes is not what people like, however, organizations can run in two modes. Also, I shared some examples from digital transformation stories that illustrate there was no transformation, either failure or smoke, and mirrors. You can download my presentation via SlideShare here.

Fireplace discussion: Bringing all the Trends Together, What’s next

We closed the day and the conference with a fireplace chat moderated by Dr. Ken Versprille from CIMdata, where we discussed, among other things, the increasing complexity of products and products as a service. We have seen during the sessions from BAE Systems Maritime and Bouygues Construction Group that we can do complex projects, however, when there are competition and time to deliver pressure, we do not manage the project so much, we try to contain the potential risk. It was an interactive fireplace giving us enough thoughts for next year.

Conclusion

Nothing to add to Håkan Kårdén’s closing tweet – I hope to see you next year.

 

 

For me, the joint conference from CIMdata and Eurostep is always a conference to look forward too. The conference is not as massive as PLM-Vendor conferences (slick presentations and happy faces); it is more a collection of PLM-practitioners (this time a 100+) with the intent to discuss and share their understanding and challenges, independent from specific vendor capabilities or features.  And because of its size a great place to network with everyone.

Day 1 was more a business/methodology view on PLM and Day 2 more in-depth focusing on standards and BIM. In this post, the highlights from the first day.

The State of PLM

 

 

Peter Bilello, CIMdata’s president, kicked of with a review of the current state of the PLM industry. Peter mentioned the PLM-market grew by 9.4 % to $47.8 billion (more than the expected 7 %). Good for the PLM Vendors and implementers.

However, Peter also mentioned that despite higher spending, PLM is still considered as a solution for engineering, often implemented as PDM/CAD data management. Traditional organizational structures, marketing, engineering, manufacturing, quality were defined in the previous century and are measured as such.

This traditional approach blocks the roll-out of PLM across these disciplines. Who is the owner of PLM or where is the responsibility for a certain dataset are questions to solve. PLM needs to transform to deliver end-to-end support instead of remaining the engineering silo. Are we still talking about PLM in the future? See Peter’s takeaways below:

 

 

We do not want to open the discussion if the the name PLM should change – too many debates – however unfortunate too much framing in the past too.

The Multi View BOM

 

 

Fred Feru from Airbus presented a status the Aerospace & Defense PLM action group are working on: How to improve and standardize on a PLM solution for multi-view BOM management, in particular, the interaction between the EBOM and MBOM. See below:

 

You might think this is a topic already solved when you speak with your PLM-vendor. However, all existing solutions at the participant implementations rely on customizations and vary per company. The target is to come up with common requirements that need to be addressed in the standard methodology. Initial alignment on terminology was already a first required step as before you standardize, you need to have a common dictionary. Moreover, a typical situation in EVERY PLM implementation.

 

 

An initial version was shared with the PLM Editors for feedback and after iterations and agreement to come with a solution that can be implemented without customization. If you are interested in the details, you can read the current status here with Appendix A en Appendix B.

 

Enabling the Circular Economy for Long Term Prosperity

Graham Aid gave a fascinating presentation related to the potentials and flaws of creating a circular economy. Although Graham was not a PLM-expert (till he left this conference), as he is the Strategy and Innovation Coordinator for the Ragn-Sells Group, which performs environmental services and recycling across Sweden, Norway, Denmark, and Estonia. Have a look at their website here.

 

 

Graham shared with us the fact that despite logical arguments for a circular economy – it is more profitable at the end – however, our short term thinking and bias block us from doing the right things for future generations.

Look at the missing link for a closed resource-lifecycle view below.

Graham shared weird examples where scarce materials for the future currently were getting cheaper, and therefore there is no desire for recycling them. A sound barrier with rubble could contain more copper than copper ore in a mine.

In the PLM-domain, there is also an opportunity for supporting and working on more sustainable products and services. It is a mindset and can be a profitable business model. In the PDT 2014 conference, there was a session on circular product development with Xerox as the best example. Circular product development but also Product As A Service can be activities that contribute to a more sustainable world. Graham’s presentation was inspiring for our PLM community and hopefully planted a few seeds for the future. As it is all about thinking long-term.

 

 

With the PLM Green Alliance, I hope we will be able to create a larger audience and participation for a sustainable future. More about the PLM Green Alliance next week.

 

The Fundamental Role of PLM in Data-driven Product Portfolio Management

 

 

Hannu Hannila (Polar) presented his study related to data-driven product portfolio management and why it should be connected to PLM.  For many companies, it is a challenge to understand which products are performing well and where to invest. These choices are often supported by Data Damagement as Hannu called it.

An example below:

The result of this fragmented approach is that organizations make their decisions on subjective data and emotions. Where the assumption is that 20 % of the products a company is selling is related to 80 % of the revenue, Hannu found in his research companies where only 10 % of the products were contributing to the revenue. As PPM (Product Portfolio Management)  often is based on big emotions – who shouts the loudest mentality, influenced by the company’s pet products and influence by the HIPPO (HIghest Paid Person in the Office).  So how to get a better rationale?

 

 

Hannu explained a data-driven framework that would provide the right analytics on management level, depending on overall data governance from all disciplines and systems.  See below:

I liked Hannu’s conclusions as it aligns with my findings:

  • To be data-driven, you need Master Data Management and Data Governance
  • Product Portfolio Management is the driving discipline for PLM, and in a modern digital enterprise, it should be connected.

Sponsor sessions

Sponsors are always needed to keep a conference affordable for the attendees.  The sponsor sessions on day 1 were of good quality.  Here a quick overview and a link if you want to invest further

 

 

Configit – explaining the value of a configurator that connects marketing, technical and sales, introducing CLM (Configuration Lifecycle Management) – a new TLA

 

 

Aras – explaining their view on what we consider the digital thread

 

 

Variantum – explaining their CPQ solution as part of a larger suite of cloud offerings

 

 

Quick Release – bringing common sense to PLM implementations, similar to what I am doing as PLM coach – focusing on the flow of information

 

 

SAP – explaining the change in focus when a company moves toward a product as a service model

 

 

SharePLM – A unique company addressing the importance of PLM training delivered through eLearning

Conclusion

The first day was an easy to digest conference with a good quality of presentations. I only shared 50 % of the session as we already reached 1000+ words.  The evening I enjoyed the joint dinner, being able to network and discuss in depth with participants and finished with a social network event organized by SharePLM. Next week part 2.

Three weeks ago, I closed my PLM-twisted mind for a short holiday. Meanwhile, some interesting posts appeared about the PLM journey.

  • Is it a journey?
  • Should the journey be measurable?
  • And what kind of journey could you imagine?

Together these posts formed a base for a decent discussion amongst the readers.  I like these discussions. For me, the purpose of blogging is not the same as tweeting. It is not about just making noise so others will chime in or react (tweeting), it is about sharing an opinion, and if more people are interested, the discussion can start. And a discussion is not about right or false, as many conversations happen to be nowadays, it is about learning.

Let’s start with the relevant posts.

How to measure PLM?

The initial discussion started with Oleg Shilovitsky’s post about the need to measure the value of PLM. As Oleg mentions in his comments:

“During the last decades, I learned that every company that measured what they do was winning the business and succeeded (let’s count Google, Amazon, etc ..)”

This is an interesting statement, just measure! The motto people are using for digital businesses. In particular for the fast-moving software business. Sounds great, so let’s measure PLM. What can we measure with PLM? Oleg suggests as an example:

“Let’s say before PLM implemented a specific process, sales needed 2 days to get a quote. After PLM process implementation, it is 15 min.”

So what does this result tell us? Your sales can do 64 times more sales quotes. Do we need fewer salespeople now? We do not know from this KPI what is the real value for the company. This because there are so many other dependencies related to this process, and that makes PLM different from, for example, ERP. We do not talk about optimizing a process as Oleg might suggest below:

“Some of my PLM friends like to say – PLM is a journey and not some kind of software. Well, I’m not sure to agree about “journey,” but I can take PLM as a process. A process, which includes all stages of product development, manufacturing, support, and maintenance.”

Note: I do not want to be picky on Oleg, as he is provoking us all many times with just his thoughts. Moreover, several of them are a good points for discussion. So please dive into his LinkedIn posts and follow the conversation.

In Oleg’s follow-up post on measuring the value, he continued with Can we measure the PLM-journey which summarizes the comments from the previous post with a kind of awkward conclusion:

What is my conclusion? It is a time for PLM get out of old fashion guessing and strategizing and move into digital form of thinking – calculating everything. Modern digital businesses are strongly focused on the calculation and measurement of everything. Performance of websites, metrics of application usage, user experience, efficiency, AB testing of everything. Measurement of PLM related activity sounds like no brainier decision to me. Just my thoughts…

I think all of us agree that there needs to be a kind of indicative measurement in place to justify investments in place. There must be expected benefits that solve current business problems or bottlenecks.

My points that I want to share with you are:

  • It is hard to measure non-comparable ways of working – how do you measure collaboration?
  • Do you know what to measure? – engineering/innovation is not an ERP process
  • People and culture have so much impact on the results – how do you measure your company’s capability to adapt to new ways of working?

Meanwhile, we continue our journey…

Is PLM a never-ending journey?

In the context of the discussion related to the PLM journey, I assume Chad Jackson from Lifecycle Insights added his 3 minutes of thoughts. You can watch the video here:

Vlogging seems to become more prevalent in the US. The issue for me is that vlogs only touch the surface, and they are hard to scan for interesting reusable content. Something you miss when you are an experienced speed-reader. I like written content as it is easier to pick and share relevant pieces, like what I am doing now in this post.

Chad states that as long as PLM delivers quantified value, PLM could be expanding. This sounds like a journey, and I could align here. The only additional thought I would like to add to this point is that it is not necessary expanding all the time, it is also about a continuous change in the world and therefore your organization. So instead of expanding, there might be a need to do things differently: Have you noticed PLM is changing.

Next Chad mentions organizational fatigue. I understand the point – our society and business are currently changing extremely fast, which causes people to long for the past. A typical behavior I observe everywhere: in the past, everything was better. However, if companies would go back and operate like in the past, they would be out of business. We moved from the paper drawing board to 3D CAD, managing it through PDM and PLM to remain significant. So there is always a journey.

Fatigue comes from choosing the wrong directions, having a reactive culture – instead of being inspired and motivated to reach the next stage, the current stage is causing already so much stress. Due to the reactive culture, people cannot imagine a better future – they are too busy. I believe it is about culture and inspiration that makes companies successful – not by just measuring.  For avoiding change, think about the boiling frog metaphor, and you see what I mean

 

Upgrading to PLM when PDM falls short

At the same time, Jim Brown from Tech-Clarity published a PTC-sponsored eBook: Upgrading to PLM when PDM fall short, in which as he states:

This eBook explains how to recognize that you’ve outgrown PDM and offers several options to find the data and process management capabilities your company needs, whether it’s time to find a more capable PDM or upgrade to PLM. It also provides practical advice on what to look for in a PLM solution, to ensure a successful implementation, and in a software partner.

Jim is mentioning various business drivers that can drive this upgrade path. Enlarge the image to the left. I challenge all the believers in measurable digital results to imagine which KPIs they would use and how they can be related to pure PLM.

Here the upgrade process is aiming at replacing PDM by PLM something PLM vendors like. Immediate a significant numbers of licenses for the same basic PDM functionality – for your company hard to justify there is no additional value.

In many situations, I have seen that this type of PDM upgrade projects became advanced PDM projects – not PLM. The new PLM system was introduced in the engineering department and became an even bigger silo than before as other disciplines/departments were not willing to work with this new “monster” and preferred their own system. They believe that PLM is a system to be purchased and implemented, which is killing for a real PLM strategy.

Therefore I liked Oleg Shilovitsky’s post: 3 Reasons for Not Growing Existing PDM Into the Full PLM System.  Where Oleg’s points were probably more technology-driven, the value of this post was extended in the discussion. It became a discussion where various people and different opinions which I would like to have in real-time. The way LinkedIn filters/prioritizes comments makes it hard to have a chronological view of the discussion.

Still, if you are interested and have time for a puzzle, follow this discussion and add your thoughts

Conclusion

During my holidays, there was a vivid discussion related to the PLM value and journey. Looking back, it is clear we are part of a PLM journey. Some do not take part in the journey and keep on hanging to the past, those who understand the journey are all seeing different Points Of Interests – the characteristics of a journey

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