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In my last post in this series, The road to model-based and connected PLM, I mentioned that perhaps it is time to talk about SLM instead of PLM when discussing popular TLA’s for our domain of expertise. There were not so many encouraging statements for SLM so far.

SLM could mean for me, Solution Lifecycle Management, considering that the company’s offering more and more is a mix of products and services. Or SLM could mean System Lifecycle Management, in that case pushing the idea that more and more products are interacting with the outside world and therefore could be considered systems. Products are (almost) dead.

In addition, I mentioned that the typical product lifecycle and related configuration management concepts need to change as in the SLM domain. There is hardware and software with different lifecycles and change processes.

It is a topic I want to explore further. I am curious to learn more from Martijn Dullaart, who will be lecturing at the  PLM Road map and PDT 2021 fall conference in November. I hope my expectations are not too high, knowing it is a topic of interest for Martijn. Feel free to join this discussion

In this post, it is time to follow up on my third statement related to what data-driven implies:

Data-driven means that we need to manage data in a much more granular manner. We have to look different at data ownership. It becomes more about data accountability per role as the data can be used and consumed throughout the product lifecycle

On this topic, I have a list of points to consider; let’s go through them.

The dataset

In this post, I will often use the term dataset (you are also allowed to write the data set I understood).

A dataset means a predefined number of attributes and values that belong logically to each other. Datasets should be defined based on the purpose and, if possible, designated for a single goal. In this way, they can be stored in a database.

Combined with other datasets, a combination can result in relevant business information. Note a dataset is not only transactional data; a dataset could also describe geometry.

Identify the dataset

In the document-based world, a lot of information could be stored in a single file. In a data-driven world, we should define a dataset that contains a specific piece of information, logically belonging together. If we are more precise, a part would have various related datasets that make up the definition of a part. These definitions could be:

  • Core identification attributes like ID, Name, Type and Status
  • The Type could define a set of linked information. For example, a valve would have different characteristics as a resistor. Through classification, we can link data sets to the core definition of a part.
  • The part can have engineering-specific data (CAD and metadata), manufacturing-specific data, supplier-specific data, and service-specific data. Each of these datasets needs to be defined as a unique element in a data-driven environment
  • CAD is a particular case as most current CAD systems don’t treat geometry as a single dataset. In a file-based world, many other datasets are stored in the file (e.g., engineering or manufacturing details). In a data-driven environment, we want to have the CAD definition to be treated like a dataset. Dassault Systèmes with their CATIA V6 and 3DEXPERIENCE platform or PTC with OnShape are examples of this approach.Having CAD as separate datasets makes sharing and collaboration so much easier, as we can see from these solutions. The concept for CAD stored in a database is not new, and this approach has been used in various disciplines. Mechanical CAD was always a challenge.

Thanks to Moore’s Law (approximate every 2 years, processor power doubled – click on the image for the details) and higher network connection speed, it starts to make sense to have mechanical CAD also stored in a database instead of a file

An important point to consider is a kind of standardization of datasets. In theory, there should be a kind of minimum agreed collection of datasets. Industry standards provide these collections in their dictionary. Whenever you optimize your data model for a connected enterprise, make sure you look first into the standards that apply to your industry.

They might not be perfect or complete, but inventing your own new standard is a guarantee for legacy issues in the future. This remark is also valid for the software vendors in this domain. A proprietary data model might give you a competitive advantage.

Still, in the long term, there is always the need to connect with outside stakeholders.

 

Identify the RACI

To ensure a dataset is complete and well maintained, the concept of RACI could be used. RACI is the abbreviation for Responsible Accountable Consulted and Informed and a simplification of the RASCI Model, see also a responsibility assignment matrix.

In a data-driven environment, there is no data ownership anymore like you have for documents. The main reason that data ownership can no longer be used is that datasets can be consumed by anyone in the ecosystem. No longer only your department or the manufacturing or service department.

Data sets in a data-driven environment bring value when connected with other datasets in applications or dashboards.

A dataset describing the specification attributes of a part could be used in a spare part app and a service app. Of course, the dataset will be used in a different context – still, we need to ensure we can trust the data.

Therefore, per identified dataset, there should be governed by a kind of RACI concept. The RACI concept is a way to break the siloes in an organization.

Identify Inside / outside

There is a lot of fear that a connected, data-driven environment will expose Intellectual Property (IP). It came up in recent discussions. If you like storytelling and technology, read my old SmarTeam colleague Alex Bruskin’s post: The Bilbo Baggins Threat to PLM Assets. Alex has written some “poetry” with a deep technical message behind it.

It is true that if your data set is too big, you have the challenge of exposing IP when connecting this dataset with others. Therefore, when building a data model, you should make it possible to have datasets pure for internal usage and datasets for sharing.

When you use the concept of RACI, the difference should be defined by the I(informed) – is it PLM-data or PIM-data for example?

Tracking relations

Suppose we follow up on the concept of datasets. In that case, it becomes clear that relations between the datasets are as crucial as the dataset. In traditional PLM applications, these relations are often predefined as part of the core data model/

For example, the EBOM parts have relationships between themselves and specification data – see image.

The MBOM parts have links with the supplier data or the manufacturing process.

The prepared relations in a PLM system allow people to implement the system relatively quickly to map their approaches to this taxonomy.

However, traditional PLM systems are based on a document-based (or file-based) taxonomy combined with related metadata. In a model-based and connected environment, we have to get rid of the document-based type of data.

Therefore, the datasets will be more granular, and there is a need to manage exponential more relations between datasets.

This is why you see the graph database coming up as a needed infrastructure for modern connected applications. If you haven’t heard of a graph database yet, you are probably far from technology hypes. To understand the principles of a graph database you can read this article from neo4j:  Graph Databases for Beginners: Why graph technology is the future

As you can see from the 2020 Gartner Hype Cycle for Artificial Intelligence this technology is at the top of the hype and conceptually the way to manage a connected enterprise. The discussion in this post also demonstrates that besides technology there is a lot of additional conceptual thinking needed before it can be implemented.

Although software vendors might handle the relations and datasets within their platform, the ultimate challenge will be sharing datasets with other platforms to get a connected ecosystem.

For example, the digital web picture shown above and introduced by Marc Halpern at the 2018 PDT conference shows this concept. Recently CIMdata discussed this topic in a similar manner: The Digital Thread is Really a Web, with the Engineering Bill of Materials at Its Center
(Note I am not sure if CIMdata has published a recording of this webinar – if so I will update the link)

Anyway, these are signs that we started to find the right visuals to imagine new concepts. The traditional digital thread pictures, like the one below, are, for me, impressions of the past as they are too rigid and focusing on some particular value streams.

From a distance, it looks like a connected enterprise should work like our brain. We story information on different abstraction levels. We keep incredibly many relations between information elements. As the brain is a biological organ, connections degrade or get lost. Or the opposite other relationships become so strong that we cannot change them anymore. (“I know I am always right”)

Interestingly, the brain does not use the “single source of truth”-concept – there can be various “truths” inside a brain. This makes us human beings with all the good and the harmful effects of that.

As long as we realize there is no single source of truth.

In business and our technological world, we need sometimes the undisputed truth. Blockchain could be the basis for securing the right connections between datasets to guarantee the result is valid. I am curious if blockchain can scale to complex connected situations, although Moore’s Law might ultimately help us here too(if still valid).

The topic is not new – in 2014 I wrote a post with the title: PLM is doomed unless ….   Where I introduced the topic of owning and sharing in the context of the human brain.  In the post, I refer to the book On Intelligence by Jeff Hawkins how tries to analyze what is human-based intelligence and how could we apply it to our technology concepts. Still a fascinating book worth reading if you have the time and opportunity.

 

Conclusion

A data-driven approach requires a more granular definition of information, leading to the concepts of datasets and managing relations between datasets. This is a fundamental difference compared to the past, where we were operating systems with information. Now we are heading towards connected platforms that provide a filtered set of real-time data to act upon.

I am curious to learn more about how people have solved the connected challenges and in what kind of granularity. Let us know!

 

 

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

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

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

 

System of Record and System of Engagement

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

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

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

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

Introducing SysML and SML

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

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

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

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

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

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

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

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

 

How to implement both approaches?

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

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

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

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

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

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

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

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

What about Configuration Management?

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

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

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

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

In his abstract for this session, Martijn writes:

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

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

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

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

 

Conclusion

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

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

Please, share your thoughts in the comments.

 

After a short summer break with almost no mentioning of the word PLM, it is time to continue this series of posts exploring the future of “connected” PLM. For those who also started with a cleaned-up memory, here is a short recap:

In part 1, I rush through more than 60 years of product development, starting from vellum drawings ending with the current PLM best practice for product development, the item-centric approach.

In part 2, I painted a high-level picture of the future, introducing the concept of digital platforms, which, if connected wisely, could support the digital enterprise in all its aspects. The five platforms I identified are the ERP and CRM platform (the oldest domains).

Next, the MES and PIP platform(modern domains to support manufacturing and product innovation in more detail) and the IoT platform (needed to support connected products and customers).

In part 3, I explained what is data-driven and how data-driven is closely connected to a model-based approach. Here we abandon documents (electronic files) as active information carriers. Documents will remain, however, as reports, baselines, or information containers. In this post, I ended up with seven topics related to data-driven, which I will discuss in upcoming posts.

Hopefully, by describing these topics – and for sure, there are more related topics – we will better understand the connected future and make decisions to enable the future instead of freezing the past.

 

Topic 1 for this post:

Data-driven does not imply, there needs to be a single environment, a single database that contains all information. As I mentioned in my previous post, it will be about managing connected datasets federated. It is not anymore about owned the data; it is about access to reliable data.

 

Platform or a collection of systems?

One of the first (marketing) hurdles to take is understanding what a data platform is and what is a collection of systems that work together, sold as a platform.

CIMdata published in 2017 an excellent whitepaper positioning the PIP (Product Innovation Platform):  Product Innovation Platforms: Definition, Their Role in the Enterprise, and Their Long-Term Viability. CIMdata’s definition is extensive and covers the full scope of product innovation. Of course, you can find a platform that starts from a more focused process.

For example, look at OpenBOM (focus on BOM collaboration), OnShape (focus on CAD collaboration) or even Microsoft 365 (historical, document-based collaboration).

The idea behind a platform is that it provides basic capabilities connected to all stakeholders, inside and outside your company. In addition, to avoid that these capabilities are limited, a platform should be open and able to connect with other data sources that might be either local or central available.

From these characteristics, it is clear that the underlying infrastructure of a platform must be based on a multitenant SaaS infrastructure, still allowing local data to be connected and shielded for performance or IP reasons.

The picture below describes the business benefits of a Product Innovation Platform as imagined by Accenture in 2014

Link to CIMdata’s 2014 commentary of Digital PLM HERE

Sometimes vendors sell their suite of systems as a platform. This is a marketing trick because when you want to add functionality to your PLM infrastructure, you need to install a new system and create or use interfaces with the existing systems, not really a scalable environment.

In addition, sometimes, the collaboration between systems in such a marketing platform is managed through proprietary exchange (file) formats.

A practice we have seen in the construction industry before cloud connectivity became available. However, a so-called end-to-end solution working on PowerPoint implemented in real life requires a lot of human intervention.

 

Not a single environment

There has always been the debate:

“Do I use best-in-class tools, supporting the end-user of the software, or do I provide an end-to-end infrastructure with more generic tools on top of that, focusing on ease of collaboration?”

In the system approach, the focus was most of the time on the best-in-class tools where PLM-systems provide the data governance. A typical example is the item-centric approach. It reflects the current working culture, people working in their optimized siloes, exchanging information between disciplines through (neutral) files.

The platform approach makes it possible to deliver the optimized user interface for the end-user through a dedicated app. Assuming the data needed for such an app is accessible from the current platform or through other systems and platforms.

It might be tempting as a platform provider to add all imaginable data elements to their platform infrastructure as much as possible. The challenge with this approach is whether all data should be stored in a central data environment (preferably cloud) or federated.  And what about filtering IP?

In my post PLM and Supply Chain Collaboration, I described the concept of having an intermediate hub (ShareAspace) between enterprises to facilitate real-time data sharing, however carefully filtered which data is shared in the hub.

It may be clear that storing everything in one big platform is not the future. As I described in part 2, in the end, a company might implement a maximum of five connected platforms (CRM, ERP, PIP, IoT and MES). Each of the individual platforms could contain a core data model relevant for this part of the business. This does not imply there might be no other platforms in the future. Platforms focusing on supply chain collaboration, like ShareAspace or OpenBOM, will have a value proposition too.  In the end, the long-term future is all about realizing a digital tread of information within the organization.

Will we ever reach a perfectly connected enterprise or society? Probably not. Not because of technology but because of politics and human behavior. The connected enterprise might be the most efficient architecture, but will it be social, supporting all humanity. Predicting the future is impossible, as Yuval Harari described in his book:  21 Lessons for the 21st Century. Worth reading, still a collection of ideas.

 

Proprietary data model or standards?

So far, when you are a software vendor developing a system, there is no restriction in how you internally manage your data. In the domain of PLM, this meant that every vendor has its own proprietary data model and behavior.

I have learned from my 25+ years of experience with systems that the original design of a product combined with the vendor’s culture defines the future roadmap. So even if a PLM vendor would rewrite all their software to become data-driven, the ways of working, the assumptions will be based on past experiences.

This makes it hard to come to unified data models and methodology valid for our PLM domain. However, large enterprises like Airbus and Boeing and the major Automotive suppliers have always pushed for standards as they will benefit the most from standardization.

The recent PDT conferences were an example of this, mainly the 2020 Fall conference. Several Aerospace & Defense PLM Action groups reported their progress.

You can read my impression of this event in The weekend after PLM Roadmap / PDT 2020 – part 1 and The next weekend after PLM Roadmap PDT 2020 – part 2.

It would be interesting to see a Product Innovation Platform built upon a data model as much as possible aligned to existing standards. Probably it won’t happen as you do not make money from being open and complying with standards as a software vendor. Still, companies should push their software vendors to support standards as this is the only way to get larger connected eco-systems.

I do not believe in the toolkit approach where every company can build its own data model based on its current needs. I have seen this flexibility with SmarTeam in the early days. However, it became an upgrade risk when new, overlapping capabilities were introduced, not matching the past.

In addition, a flexible toolkit still requires a robust data model design done by experienced people who have learned from their mistakes.

The benefit of using standards is that they contain the learnings from many people involved.

 

Conclusion

I did not like writing this post so much, as my primary PLM focus lies on people and methodology. Still, understanding future technologies is an important point to consider. Therefore, this time a not-so-exciting post. There is enough to read on the internet related to PLM technology; see some of the recent articles below. Enjoy

 

Matthias Ahrens shared:  Integrated Product Lifecycle Management (Google translated from German)

Oleg Shilovitsky wrote numerous articles related to technology –
in this context:
3 Challenges of Unified Platforms and System Locking and
SaaS PLM Acceleration Trends

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

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

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

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

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

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

What means data-driven?

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

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

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

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

Examples of a data-driven approach – the item

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

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

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

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

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

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

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

Examples of a data-driven approach – the requirement

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

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

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

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

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

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

Data-driven and Models – the 3D CAD model

3D PDF Model

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

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

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

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

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

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

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

Data-driven and mathematical models

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

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

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

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

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

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

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

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

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

What does data-driven imply?

 

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

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

 

Conclusion

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

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

 

 

 

 

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?

 

 

 

 

 

 

PLM and Complementary domains/practices

After “The PLM Doctor is IN #2,” now again a written post in the category of PLM and complementary practices/domains.

After PLM and Configuration Lifecycle ManagementCLM (January 2021) and PLM and Configuration Management CM (February 2021), now it is time to address the third interesting topic:
PLM and Supply Chain collaboration.

In this post, I am speaking with Magnus Färneland from Eurostep, a company well known in my PLM ecosystem, through their involvement in standards (STEP and PLCS), the PDT conferences, and their PLM collaboration hub, ShareAspace.

Supply Chain collaboration

The interaction between OEMs and their suppliers has been a topic of particular interest to me. As a warming-up, read my post after CIMdata/PDT Roadmap 2020:  PLM and the Supply Chain. In this post, I briefly touched on the Eurostep approach – having a Supply Chain Collaboration Hub. Below an image from that post – in this case, the Collaboration Hub is positioned between two OEMs.

Slide: PDT Europe 2016 RENAULT PLM Challenges

Recently Eurostep shared a blog post in the same context: 3 Steps to remove data silos from your supply chain addressing the dreams of many companies: moving from disconnected information silos towards a logical flow of data. This topic is well suited for all companies in the digital transformation process with their supply chain. So, let us hear it from Eurostep.

Eurostep – the company / the mission

First of all, can you give a short introduction to Eurostep as a company and the unique value you are offering to your clients?


Eurostep was founded in 1994 by several world-class experts on product data and information management. In the year 2000, we started developing ShareAspace. We took all the experience we had from working with collaboration in the extended enterprise, mixed it with our standards knowledge, and selected Microsoft as the technology for our software platform.

We now offer ShareAspace as a solution for product information collaboration in all three industry verticals where we are active: Manufacturing, Defense and AEC & Plant.

In the Manufacturing offering – the Supply Chain Collaboration Hub

ShareAspace is based on an information standard called PLCS (ISO 10300-239). This means we have a data model covering the complete life cycle of a product from requirements and conceptual design to an existing installed base. We have added things needed, such as consolidation and security. Our partnership with Microsoft has also resulted in ShareAspace being available in Azure as a service (our Design to Manufacturing software).

 

Why a supply chain collaboration hub?

Currently, most suppliers work in a disconnected manner with their clients – sending files up and down or the need to work inside the OEM environment. What are the reasons to consider a supply chain collaboration hub or, as you call it, a product information collaboration solution?

The hub concept is not new per se. There are plenty of examples of file sharing hubs. Once you realize that sending files back and forth by email is a disaster for keeping control of your information being shared with suppliers, you would probably try out one of the available file-sharing alternatives.

However, after a while, you begin to realize that a file share can be quite time consuming to keep up to date. Files are being changed. Files are being removed! Some files are enormous, and you realize that you only need a fraction of what is in the file. References within one file to another file becomes corrupt because the other file is of a new version. Etc. Etc.

This is about the time when you realize that you need similar control of the data you share with suppliers as you have in your internal systems. If not better.

A hub allows all partners to continue to use their internal tools and processes. It is also a more secure way of collaboration as the suppliers and partners are not let into the internal systems of the OEM.

Another significant side effect of this is that you only expose the data in the hub intended for external sharing and avoid sharing too much or exposing internal sensitive data.

A hub is also suitable for business flexibility as partners are not hardwired with the OEM. Partners can change, and IT systems in the value chain can change without impacting more than the single system’s connecting to the hub.

Should every company implement a supply chain collaboration hub?

Based on your experience, what types of companies should implement a supply chain collaboration hub and what are the expected benefits?

 

The large OEMs and 1st tier suppliers certainly benefit from this since they can incorporate hundreds, if not thousands, of suppliers. Sharing technical data across the supply chain from a dedicated hub will remove confusions, improve control of the shared data, and build trust with their partners.

With our cloud-based offering, we now also make it possible for at least mid-sized companies (like 200+ employees) to use ShareAspace. They may not have a well-adopted PLM system or the issues of communicating complex specifications originating from several internal sources. However still, they need to be professional in dealing with suppliers.

The smallest client we have is a manufacturer of pool cleaners, a complex product with many suppliers. The company Weda [www.weda.se] has less than 10 employees, and they use ShareAspace as SaaS. With ShareAspace, they have improved their collaboration process with suppliers and cut costs and lowered inventory levels.

ShareAspace can really scale big. It serves as a collaboration solution for the two new Aircraft carriers in the UK, the QUEEN ELIZABETH class. The aircraft carriers were built by a consortium that was closed in early 2020.

ShareAspace is being used to hold the design data and other documentation from the consortium to be available to the multiple organizations (both inside and outside of the Ministry of Defence) that need controlled access.

 

What is the dependency on standards?

I always associate Eurostep with the PLCS (ISO 10303-239) standard, providing an information model for “hardware” products along the lifecycle. How important is this standard for you in the context of your ShareAspace offering?
Should everyone adapt to this standard?

We have used PLCS to define the internal data schema in ShareAspace. This is an excellent starting point for capturing information from different systems and domains and still getting it to fit together. Why invent something new?

However, we can import data in most formats, and it does not have to be according to a standard. When connecting to Teamcenter, Windchill, Enovia, SAP, Oracle, Maximo etc., it is more often in a proprietary format than according to any standards.

Capital Facilities Information HandOver Specification (CFHOS) exchange

On the other hand, in some industries like Defense, standards-based data exchange is required and put into contracts. Sometimes it prescribes PLCS.  For the plant industry, it could be CFIHOS or ISO15926.

Supply Chain Collaboration and digital transformation

As stated at the beginning of this post, digital transformation is about connecting the information siloes through a digital thread. How important is this related to the supply chain?

Many companies have come a long way in improving their internal management of product data. But still, the exchange and sharing of data with the external world has considerable potential for improvement. Just look at the chaos everyone has experienced with emails, still used a lot, in finding the latest Word document or PowerPoint file. Imagine if you collaborate on a ship, a truck, a power plant, or a piece of complex infrastructure. FTP is not the answer, and for product data, Dropbox is not doing the trick.

A Digital Thread must support versions and changes in all directions, as changes are natural with reasonably advanced products. Much of the information created about or around a product is generated within the supply chain, like production parameters, test and inspection protocols, certifications, and more. Without an intelligent way of capturing this data, companies will continue to spend a fortune on administration trying to manage this manually.

As the Digital Thread extends across the value chain, a useful sharing tool is needed to allow for configuration management across the complete chain – ShareAspace is designed for this. The great thing with PLCS is that it gives a standard model for the Digital Thread covering several Digital Twins. PLCS adds the life cycle component, which is essential, and there is no alternative. Therefore, we are welcome with ShareAspace and PLCS to add capabilities to snapshot standards like IFC etc., that are outside the STEP series of standards.

Learning more

We discussed that a supply chain collaboration hub can have specific value to a company. Where can readers learn more?

There is a lot of information available. Of course, on our Eurostep website, you will find information under the tab Resources or on the ShareAspace website under the tab News.
Other sources are:

CIMdata A Controlled and Protected Partner and Supplier Collaboration Environment
Boston Consulting Group Share to Gain: Unlocking Data Value in Manufacturing
Eurostep Data sharing and collaboration across global value chains worth 100 Billion USD is waiting for you!
McKinsey Digital supply chains: Do you have the skills to run them?

 

What I have learned

  • I am surprised to see that the type of Supplier Collaboration Platform delivered by Eurostep is not a booming market. Where Time to Market is significantly impacted by how companies work with their suppliers, most companies still rely on the exchange of data packages.
  • The most advanced exchanges are using a model-based definition if relevant. Traditional PLM Vendors will not develop such platforms as the platform needs to be agnostic in both directions.
  • Having a recommended data model based on PLCS or a custom-data model in case of a large OEM can provide such a collaboration hub. Relative easy to implement (as you do not change your own PLM) and relatively easy to scale (adding a new supplier is easy).  For me, the supplier collaboration platform is a must in a modern, digital connected enterprise.

Conclusion

A lot of marketing money is spent on “Digital Thread” or “Digital Continuity”.  If you are looking at the full value chain of product development and operational support, there are still many manual hand-over processes with suppliers. A supplier collaboration hub might be the missing piece of the puzzle to realize a real digital thread or continuity.

Last week I shared my first review of the PLM Roadmap / PDT Fall 2020 conference, organized by CIMdata and Eurostep. Having digested now most of the content in detail, I can state this was the best conference of 2020. In my first post, the topics I shared were mainly the consultant’s view of digital thread and digital twin concepts.

This time, I want to focus on the content presented by the various Aerospace & Defense working groups who shared their findings, lessons-learned (so far) on topics like the Multi-view BOM, Supply Chain Collaboration, MBSE Data interoperability.

These sessions were nicely wrapped with presentations from Alberto Ferrari (Raytheon), discussing the digital thread between PLM and Simulation Lifecycle Management and Jeff Plant (Boeing) sharing their Model-Based Engineering strategy.

I believe these insights are crucial, although there might be people in the field that will question if this research is essential. Is not there an easier way to achieve to have the same results?

Nicely formulated by Ilan Madjar as a comment to my first post:

Ilan makes a good point about simplifying the ideas to the masses to make it work. The majority of companies probably do not have the bandwidth to invest and understand the future benefits of a digital thread or digital twins.

This does not mean that these topics should not be studied. If your business is in a small, simple eco-system and wants to work in a connected mode, you can choose a vendor and a few custom interfaces.

However, suppose you work in a global industry with an extensive network of partners, suppliers, and customers.

In that case, you cannot rely on ad-hoc interfaces or a single vendor. You need to invest in standards; you need to study common best practices to drive methodology, standards, and vendors to align.

This process of standardization is so crucial if you want to have a sustainable, connected enterprise. In the end, the push from these companies will lead to standards, allowing the smaller companies to ad-here or connect to.

The future is about Connected through Standards, as discussed in part 1 and further in this post. Let’s go!

Global Collaboration – Defining a baseline for data exchange processes and standards

Katheryn Bell (Pratt & Whitney Canada) presented the progress of the A&D Global Collaboration workgroup. As you can see from the project timeline, they have reached the phase to look towards the future.

Katheryn mentioned the need to standardize terminology as the first point of attention. I am fully aligned with that point; without a standardized terminology framework, people will have a misunderstanding in communication.

This happens even more in the smaller businesses that just pick sometimes (buzz) terms without a full understanding.

Several years ago, I talked with a PLM-implementer telling me that their implementation focus was on systems engineering. After some more explanations, it appeared they were making an attempt for configuration management in reality. Here the confusion was massive. Still, a standard, common terminology is crucial in our domain, even if it seems academic.

The group has been analyzing interoperability standards, standards for long-time archival and retrieval (LOTAR), but also has been studying the ISO 44001 standard related to Collaborative business relationship management systems

In the Q&A session, Katheryn explained that the biggest problem to solve with collaboration was the risk of working with the wrong version of data between disciplines and suppliers.

Of course, such errors can lead to huge costs if they are discovered late (or too late). As some of the big OEMs work with thousands of suppliers, you can imagine it is not an issue easily discovered in a more ad-hoc environment.

The move to a standardized Technical Data Package based on a Model-Based Definition is one of these initiatives in this domain to reduce these types of errors.

You can find the proceedings from the Global Collaboration working group here.

 

Connect, Trace, and Manage Lifecycle of Models, Simulation and Linked Data: Is That Easy?

I loved Alberto Ferrari‘s (Raytheon) presentation how he described the value of a model-based digital thread, positioning it in a targeted enterprise.

Click on the image and discover how business objectives, processes and models go together supported by a federated infrastructure.

Alberto’s presentation was a kind of mind map from how I imagine the future, and it is a pity if you have not had the chance to see his session.

Alberto also focused on the importance of various simulation capabilities combined with simulation lifecycle management. For Alberto, they are essential to implement digital twins. Besides focusing on standards, Alberto pleas for a semantic integration, open service architecture with the importance of DevSecOps.

Enough food for thought; as Alberto mentioned, he presented the corporate vision, not the current state.

More A&D Action Groups

There were two more interesting specialized sessions where teams from the A&D action groups provided a status update.

Brandon Sapp (Boeing) and Ian Parent (Pratt & Whitney) shared the activities and progress on Minimum Model-Based Definition (MBD) for Type Design Certification.

As Brandon mentioned, MBD is already a widely used capability; however, MBD is still maturing and evolving.  I believe that is also one of the reasons why MBD is not yet accepted in mainstream PLM. Smaller organizations will wait; however, can your company afford to wait?

More information about their progress can be found here.

Mark Williams (Boeing) reported from the A&D Model-Based Systems Engineering action group their first findings related to MBSE Data Interoperability, focusing on an Architecture Model Exchange Solution.  A topic interesting to follow as the promise of MBSE is that it is about connected information shared in models. As Mark explained, data exchange standards for requirements and behavior models are mature, readily available in the tools, and easily adopted. Exchanging architecture models has proven to be very difficult. I will not dive into more details, respecting the audience of this blog.

For those interested in their progress, more information can be found here

Model-Based Engineering @ Boeing

In this conference, the participation of Boeing was significant through the various action groups. As the cherry on the cake, there was Jeff Plant‘s session, giving an overview of what is happening at Boeing. Jeff is Boeing’s director of engineering practices, processes, and tools.

In his introduction, Jeff mentioned that Boeing has more than 160.000 employees in over 65 countries. They are working with more than 12.000 suppliers globally. These suppliers can be manufacturing, service or technology partnerships. Therefore you can imagine, and as discussed by others during the conference, streamlined collaboration and traceability are crucial.

The now-famous MBE Diamond symbol illustrates the model-based information flows in the virtual world and the physical world based on the systems engineering approach. Like Katheryn Bell did in her session related to Global Collaboration, Jeff started explaining the importance of a common language and taxonomy needed if you want to standardize processes.

Zoom in on the Boeing MBE Taxonomy, you will discover the clarity it brings for the company.

I was not aware of the ISO 23247 standard concerning the Digital Twin framework for manufacturing, aiming to apply industry standards to the model-based definition of products and process planning. A standard certainly to follow as it brings standardization on top of existing standards.

As Jeff noted: A practical standard for implementation in a company of any size. In my opinion, mandatory for a sustainable, connected infrastructure.

Jeff presented the slide below, showing their standardization internally around federated platforms.

This slide resembles a lot the future platform vision I have been sharing since 2017 when discussing PLM’s future at PLM conferences, when explaining the differences between Coordinated and Connected – see also my presentation here on Slideshare.

You can zoom in on the picture to see the similarities. For me, the differences were interesting to observe. In Jeff’s diagram, the product lifecycle at the top indicates the platform of (central) interest during each lifecycle stage, suggesting a linear process again.

In reality, the flow of information through feedback loops will be there too.

The second exciting detail is that these federated architectures should be based on strong interoperability standards. Jeff is urging other companies, academics and vendors to invest and come to industry standards for Model-Based System Engineering practices.  The time is now to act on this domain.

It reminded me again of Marc Halpern’s message mentioned in my previous post (part 1) that we should be worried about vendor alliances offering an integrated end-to-end data flow based on their solutions. This would lead to an immense vendor-lock in if these interfaces are not based on strong industry standards.

Therefore, don’t watch from the sideline; it is the voice (and effort) of the companies that can drive standards.

Finally, during the Q&A part, Jeff made an interesting point explaining Boeing is making a serious investment, as you can see from their participation in all the action groups. They have made the long-term business case.

The team is confident that the business case for such an investment is firm and stable, however in such long-term investment without direct results, these projects might come under pressure when the business is under pressure.

The virtual fireside chat

The conference ended with a virtual fireside chat from which I picked up an interesting point that Marc Halpern was bringing in. Marc mentioned a survey Gartner has done with companies in fast-moving industries related to the benefits of PLM. Companies reported improvements in accuracy and product development. They did not see so much a reduced time to market or cost reduction. After analysis, Gartner believes the real issue is related to collaboration processes and supply chain practices. Here lead times did not change, nor the number of changes.

Marc believes that this topic will be really showing benefits in the future with cloud and connected suppliers. This reminded me of an article published by McKinsey called The case for digital reinvention. In this article, the authors indicated that only 2 % of the companies interview were investing in a digital supply chain. At the same time, the expected benefits in this area would have the most significant ROI.

The good news, there is consistency, and we know where to focus for early results.

Conclusion

It was a great conference as here we could see digital transformation in action (groups). Where vendor solutions often provide a sneaky preview of the future, we saw people working on creating the right foundations based on standards. My appreciation goes to all the active members in the CIMdata A&D action groups as they provide the groundwork for all of us – sooner or later.

Last week I was happy to attend the PLM Roadmap / PDT Fall 2020 conference as usual organized by CIMdata and Eurostep. I wrote about the recent PI DX conference, which touched a lot on the surface of PLM and Digital Transformation. This conference is really a conference for those who want to understand the building blocks needed for current and future PLM.

In this conference, usually with approximately 150 users on-site, now with over 250 connected users for 3 (half) days. Many of us, following every session of the conference. As an active participant in the physical events, it was a little disappointing not to be in the same place with the other participants this time. The informal network meetings in this conference have always been special thanks to a relatively small but stable group of experts.  Due to the slightly reduced schedule, there was this time, less attention for some of the typical PDT-topics most of the time coming from Sweden and related to sustainability.

The conference’s theme was Digital Thread—the PLM Professionals’ Path to Delivering Innovation, Efficiency, and Quality and might sound like a marketing statement.  However, the content presented was much more detailed than just marketing info. The fact that you watched the presentation on your screen made it an intense conference with many valuable details.

Have a look at the agenda, and I will walk you through some of the highlights for me. As there was so much content to discuss, I will share this time part 1. Next week, in part 2, you will see the coherence of all the presentations.

As if there was a Coherent Thread.

Digital Twin, It Requires a Digital Thread

Peter Bilello, President & CEO, CIMdata, ‘s keynote with the title Digital Twin, It Requires a Digital Thread was immediately an illustration of discussing reality.  When I stated at the Digital Twin conference in the Netherlands that “Digital Twins do not run on Documents“, it had the same meaning as when Peter stated,” A Digital Twin without a Digital Thread is an orphan”.

Digital Thread

And Peter’s statement, “All companies do PLM, most of the time however disconnected”, is another way to stimulate companies working in a connected manner.

As usual Peter’s session was a good overview of the various aspect related to the Digital Thread and Digital Twin.

Digital Twin

The concept of a virtual twin is not new. The focus is as mentioned before now more on the term “Connected” Peter provided the CIMdata definition for Digital Thread and Digital Twin. Click on the images to the left to read the full definition.

Peter’s overview also referred to the Boeing Diamond, illustrating the mapping of the physical and virtual world, connected through a Digital Thread the various Digital Twins that can exist. The Boeing Diamond was one of the favorites during the conference.

When you look at Peter’s conclusions, there is an alignment with what I wrote in the post: A Digital Twin for Everyone and the fact that we need to strive for a connected enterprise. Only then we can benefit from a Digital Twin concept.

 

The Multi-view BOM Solution Evaluation
– Process, Results, and Industry Impacts

The reports coming from the various A&D PLM action groups are always engaging sessions to watch. Here, nine companies, even competitors, discuss and explore PLM themes between themselves supported by CIMdata.

These companies were the first that implemented PLM; it is interesting to watch how they move forward like supertankers. They cannot jump from one year to another year on a new fashionable hype. Their PLM-infrastructure needs to be consistent and future-proof due to their data’s longevity and the high standards for regulatory compliance and safety.

However, these companies are also pioneers for the future. They have been practicing Model-Based approaches for over ten years already and are still learning. In next week’s post, you will read later that these frontrunners are pushing for standards to make a Model-Based future affordable and achievable.

In that context, the action group Multi-View BOM shared their evaluation results for a study related to the multi-view BOM. A year ago, I wrote about this topic when Fred Feru from Airbus presented the intermediate results at the CIMdata Roadmap/PDT 2019 conference.

Dan Ganser (Gulfstream) and Javier Reines (Airbus) presented the findings. The conclusion was that the four vendors evaluated, i.e., Aras, Dassault Systems, PTC and Siemens, all passed the essential requirements and use cases. You can find the report and the findings here: Multi-view Bill of Materials

One interesting remark.

When the use cases were evaluated, the vendors could score on a level from 0 to 5, see picture. Interesting to see that apparently, it was possible to exceed the requirement, something that seems like a contradiction.

In particular, in this industry, where formal requirements management is a must – either you meet a requirement or not.

Dan Ganser explained that the current use cases were defined based on the minimum expectations, therefore there was the option to exceed the requirement. I still would be curious to see what does it mean to exceed the requirement. Is it usability, time, or something innovative we might have missed?

 

5G for Digital Twins & Shadows

I learned a lot from the presentation from Niels Koenig, working at the Fraunhofer Institute for Production Technology. Niels explained how important 5G is for realizing the Industry 4.0 targets. At the 5G Industry Campus, several projects are running to test and demonstrate the value of 5G in relation to manufacturing.

If you want to get an impression of the 5G Industry Campus – click on the Youube movie.

One of the examples Niels discussed was closed-loop manufacturing. Thanks to the extremely low latency (< 1ms), a connected NC machine can send real-time measurements to be compared with the expected values. For example, in the case of resonance, the cutting might not be smooth. Thanks to the closed-loop, the operator will be able to interfere or adjust the operation. See the image below.

Digital Thread: Be Careful What you Wish For, It Just Might Come True

I was looking forward to Marc Halpern‘s presentation. Marc often brings a less technical viewpoint but a more business-related viewpoint to the discussion. Over the past ten years, there have been many disruptive events, most recently the COVID-pandemic.

Companies are asking themselves how they can remain resilient. Marc shared some of his thoughts on how Digital Twins and Digital Threads can support resilience.

In that context, Gartner saw a trend that their customers are now eagerly looking for solutions related to Digital Twin, Digital Thread, Model-Based Approaches, combined with the aim to move to the cloud. Related to Digital Thread and Digital Twin, most of Gartner’s clients are looking for traceability and transparency along the product lifecycle. Most Digital Twin initiatives focus on a twin of operational assets, particularly inside the manufacturing facility. Nicely linking to Niels Konig’s session related to 5G.

Marc stated that there seems to be a consensus that a Digital Thread is compelling enough for manufacturers to invest. In the end, they will have to. However, there are also significant risks involved. Marc illustrated the two extremes; in reality, companies will end up somewhere in the middle, illustrated later by Jeff Plant from Boeing. The image on the left is a sneaky preview for next week.

When discussing the Digital Thread, Marc again referred to it more as a Digital Net, a kind of connected infrastructure for various different threads based on the various areas of interest.

I show here a slide from Marc’s presentation at the PDT conference in 2018. It is more an artist’s impression of the same concept discussed during this conference again, the Boeing Diamond.

Related to the risk of implementing a Digital Thread and Digital Twin, Marc showed another artistic interpretation; The two extremes of two potential end states of Digital Thread investment. Marc shared the critical risks for both options.

For the Vendor Black Hole, his main points were that if you choose a combined solution, diminished negotiating power, higher implementation costs, and potentially innovative ideas might not be implemented as they are not so relevant for the vendor. They have the power!

As an example of combined solutions Marc mentioned, the recently announced SAP-Siemens partnership, the Rockwell Automation-PTC partnership, the Schneider Electric-Aveva-partnership, and the ABB-Dassault Systemes partnership.

Once you are in the black hole, you cannot escape. Therefore, Marc recommended making sure you do not depend on a few vendors for your Digital Twin infrastructure.

The picture on the left illustrates the critical risks of the Enterprise Architecture “Mess”. It is a topic that I am following for a long time. Suppose you have a collection of services related to the product lifecycle, like Workflow-services, 3D Modeling-services, BOM-services, Manufacturing-services.

Together they could provide a PLM-infrastructure.

The idea behind this is that thanks to openness and connectivity, every company can build its own unique enterprise architecture. No discussion about standard best practices. You build your company’s best practices (for the future, the current ?)

It is mainly promoted as a kind of bottom-up PLM. If you are missing capabilities, just build them yourselves, using REST-services, APIs, using Low-Code platforms. It seems attractive for the smaller enterprises, however most of the time, only a short time. I fully concur with Marc’s identified risks here.

As I often illustrated in presentations related to a digital future, you will need a mix of both. Based on your point of focus, you could imagine five major platforms being connected together to cover all aspects of a business. Depending on your company’s business model and products, one of them might be the dominant one. With my PLM-focus, this would be the Product Innovation Platform, where the business is created.

Marc ended with five priorities to enable a long-term Digital Thread success.

  • First of all – set the ground rules for data governance. A topic often mentioned but is your company actively engaging on that already?
  • Next, learn from Model-Based Systems Engineering as a foundation for a Model-Based Enterprise.  A topic often discussed during the previous CIMdata Roadmap / PDT-conference.
  • The change from storing and hiding information in siloes towards an infrastructure and mindset of search and access of data, in particular, the access to Bill of Materials

The last point induced two more points.

  • The need for an open architecture and standards. We would learn more on this topic on day 3 of the conference.
  • Make sure your digital transformation sticks within the organization by investing and executing on organizational change management.

Conclusion

The words “Digital Thread” and “Digital Twin” are mentioned 18 times in this post and during the conference even more. However, at this conference, they were not hollow marketing terms. They are part of a dictionary for the future, as we will see in next week’s post when discussing some of the remaining presentations.

Closing this time with a point we all agreed upon: “A Digital Twin without a Digital Thread is an orphan”. Next week more!

In the series learning from the past to understand the future, we have almost reached the current state of PLM before digitization became visible. In the last post, I introduced the value of having the MBOM preparation inside a PLM-system, so manufacturing engineering can benefit from early visibility and richer product context when preparing the manufacturing process.

Does everyone need an MBOM?

It is essential to realize that you do not need an EBOM and a separate MBOM in case of an Engineering To Order primary process. The target of ETO is to deliver a unique customer product with no time to lose. Therefore, engineering can design with a manufacturing process in mind.

The need for an MBOM comes when:

  • You are selling a specific product over a more extended period of time. The engineering definition, in that case, needs to be as little as possible dependent on supplier-specific parts.
  • You are delivering your portfolio based on modules. Modules need to be as long as possible stable, therefore independent of where they are manufactured and supplier-specific parts. The better you can define your modules, the more customers you can reach over time.
  • You are having multiple manufacturing locations around the world, allowing you to source locally and manufacture based on local plant-specific resources. I described these options in the previous post

The challenge for all companies that want to move from ETO to BTO/CTO is the fact that they need to change their methodology – building for the future while supporting the past. This is typically something to be analyzed per company on how to deal with the existing legacy and installed base.

Configurable EBOM and MBOM

In some previous posts, I mentioned that it is efficient to have a configurable EBOM. This means that various options and variants are managed in the same EBOM-structure that can be filtered based on configuration parameters (date effectivity/version identifier/time baseline). A configurable EBOM is often called a 150 % EBOM

The MBOM can also be configurable as a manufacturing plant might have almost common manufacturing steps for different product variants. By using the same process and filtered MBOM, you will manufacture the specific product version. In that case, we can talk about a 120 % MBOM

Note: the freedom of configuration in the EBOM is generally higher than the options in the configurable MBOM.

The real business change for EBOM/MBOM

So far, we have discussed the EBOM/MBOM methodology. It is essential to realize this methodology only brings value when the organization will be adapted to benefit from the new possibilities.

One of the recurring errors in PLM implementations is that users of the system get an extended job scope, without giving them the extra time to perform these activities. Meanwhile, other persons downstream might benefit from these activities. However, they will not complain. I realized that already in 2009, I mentioned such a case: Where is my PLM ROI, Mr. Voskuil?

Now let us look at the recommended business changes when implementing an EBOM/MBOM-strategy

  1. Working in a single, shared environment for engineering and manufacturing preparation is the first step to take.

Working in a PLM-system is not a problem for engineers who are used to the complexity of a PDM-system. For manufacturing engineers, a PLM-environment will be completely new. Manufacturing engineers might prepare their bill of process first in Excel and ultimately enter the complete details in their ERP-system. ERP-systems are not known for their user-friendliness. However, their interfaces are often so rigid that it is not difficult to master the process. Excel, on the other side, is extremely flexible but not connected to anything else.

And now, this new PLM-system requires people to work in a more user-friendly environment with limited freedom. This is a significant shift in working methodology. This means manufacturing engineers need to be trained and supported  over several months. Changing habits and keep people motivated takes energy and time. In reality, where is the budget for these activities?  See my 2016 post: PLM and Cultural Change Management – too expensive?

  1. From sequential to concurrent

Once your manufacturing engineers are able to work in a PLM-environment, they are able to start the manufacturing definition before the engineering definition is released. Manufacturing engineers can participate in design reviews having the information in their environment available. They can validate critical manufacturing steps and discuss with engineers potential changes that will reduce the complexity or cost for manufacturing. As these changes will be done before the product is released, the cost of change is much lower. After all, having engineering and manufacturing working partially in parallel will reduce time to market.

Reducing time to market by concurrent engineering

One of the leading business drivers for many companies is introducing products or enhancements to the market. Bringing engineering and manufacturing preparation together also means that the PLM-system can no longer be an engineering tool under the responsibility of the engineering department.

The responsibility for PLM needs to be at a level higher in the organization to ensure well-balanced choices. A higher level in the organization automatically means more attention for business benefits and less attention for functions and features.

From technology to methodology – interface issues?

The whole EBOM/MBOM-discussion often has become a discussion related to a PLM-system and an ERP-system. Next, the discussion diverted to how these two systems could work together, changing the mindset to the complexity of interfaces instead of focusing on the logical flow of information.

In an earlier PI Event in München 2016, I lead a focus group related to the PLM and ERP interaction. The discussion was not about technology, all about focusing on what is the logical flow of information. From initial creation towards formal usage in a product definition (EBOM/MBOM).

What became clear from this workshop and other customer engagements is that people are often locked in their siloed way of thinking. Proposed information flows are based on system capabilities, not on the ideal flow of information. This is often the reason why a PLM/ERP-interface becomes complicated and expensive. System integrators do not want to push for organizational change, they prefer to develop an interface that adheres to the current customer expectations.

SAP has always been promoting that they do not need an interface between engineering and manufacturing as their data management starts from the EBOM. They forgot to mention that they have a difficult time (and almost no intention) to manage the early ideation and design phase. As a Dutch SAP country manager once told me: “Engineers are resources that do not want to be managed.” This remark says all about the mindset of ERP.

After overlooking successful PLM-implementations, I can tell the PLM-ERP interface has never been a technical issue once the methodology is transparent. A company needs to agree on logical data flow from ideation through engineering towards design is the foundation.

It is not about owning data and where to store it in a single system. It is about federated data sets that exist in different systems and that are complementary but connected, requiring data governance and master data management.

The SAP-Siemens partnership

In the context of the previous paragraph, the messaging around the recently announced partnership between SAP and Siemens made me curious. Almost everyone has shared an opinion about the partnership. There is a lot of speculation, and many questions were imaginarily answered by as many blog posts in the field. Last week Stan Przybylinski shared CIMdata’s interpretations in a webinar Putting the SAP-Siemens Partnership In Context, which was, in my opinion, the most in-depth analysis I have seen.

For what it is worth, my analysis:

  • First of all, the partnership is a merger of slide decks at this moment, aiming to show to a potential customer that in the SAP/Siemens-combination, you find everything you need. A merger of slides does not mean everything works together.

  • It is a merger of two different worlds. You can call SAP a real data platform with connected data, where Siemens offering is based on the Teamcenter backbone providing a foundation for a coordinated approach. In the coordinated approach, the data flexibility is lower. For that reason, Mendix is crucial to make Siemens portfolio behave like a connected platform too.
    You can read my doubts about having a coordinated and connected system working together (see image above). It was my #1 identified challenge for this decade: PLM 2020 – PLM the next decade (before COVID-19 became a pandemic and illustrated we need to work connected)
  • The fact that SAP will sell TC PLM and Siemens will sell SAP PPM seems like loser’s statement, meaning our SAP PLM is probably not good enough, or our TC PPM capabilities are not good enough. In reality, I believe they both should remain, and the partnership should work on logical data flows with data residing in two locations – the federated approach. This is how platforms reside next to each other instead of the single black hole.

  • The fact that standard interfaces will be developed between the two systems is a subtle sales argument with relatively low value. As I wrote in the “from technology to methodology”-paragraph, the challenges are in the organizational change within companies. Technology is not the issue, although system integrators also need to make a living.
  • What I believe makes sense is that both SAP and Siemens, have to realize their Industry 4.0 end-to-end capabilities. It is a German vision now for several years and it is an excellent vision to strive for. Now it is time to build the two platforms working together. This will be a significant technical challenge mainly for Siemens as its foundation is based on a coordinated backbone.
  • The biggest challenge, not only for this partnership, is the organizational change within companies that want to build an end-to-end connected solution. In particular, in companies with a vast legacy, the targeted industries by the partnership, the chasm between coordinated legacy data and intended connected data is enormous. Technology will not fix it, perhaps smoothen the pain a little.

 

Conclusion

With this post, we have reached the foundation of the item-centric approach for PLM, where the EBOM and MBOM are managed in a real-time context. Organizational change is the biggest inhibitor to move forward. The SAP-Siemens partnership is a sales/marketing approach to create a simplified view for the future at C-level discussions.
Let us watch carefully what happens in reality.

Next time potentially the dimension of change management and configuration management in an item-centric approach.
Or perhaps Martijn Dullaart will show us the way before, following up on his tricky poll question

 

I usually write a post after participating in a PLM conference. Last week, I participated in TECHNIA’s PLM Innovation Forum, which was a 100 % virtual event with over 1500 registered participants from 58 countries. These numbers show the power of a virtual conference during these difficult times. It is an excellent option for a sustainable future – less travel to be there.

The additional beauty of this event is that, although the live sessions are over, all the content will be available until May 31st. You can still join!

It was (and is) a well-organized and massive event with over 70 sessions; the majority pre-recorded. As you can imagine 70 live sessions in two days would be too massive to grasp. Today the Friday after the event, I have been watching other sessions that have my interest, and it felt like another conference day.

TECHNIA, globally the largest Dassault Systèmes (DS)  implementer after DS themselves as Jonas Geyer, Technia’s CEO,  mentioned in his introduction speech, illustrated the breadth of their industry and technology skills complementary or based on the 3DEXPERIENCE platform.

TECHNIA was supported by Dassault Systèmes Execs and subject experts. In addition, a larger group of companies and interest groups supported the conference, even our humble PLM Green Alliance as you can see in the image above.

I followed the full two live days in real-time, meanwhile man sitting in my virtual booth to chat with virtual visitors. To my surprise, the anxiety during the conference felt like a physical conference – you get energized.

The positive point for me,  no finger food or a standing lunch and decent coffee when needed. The point to enhance and learn for this type of event, is to make the booth a little more human – perhaps supported by video?

At the end,  a great event, and if you are interested in the Dassault Systèmes/TECHNIA combined offering, supported by customer stories, take the chance till the end of May to register and browse the rich content.

 

Now I will share some of my picks from the live event. Another post will come based on my additional discoveries and networking discussions.

 

 

The B.CONNECT project

Fabien Hoefer and Philip Haller both from B.Braun, a medical device, and pharmaceutical company, with a wide range of products.  Their massive PLM-project, approx. sixty persons involved was driven by the fact that every product has a lot of related data stored in different silos that it becomes impossible to have the correct understanding and status and to maintain it for the product and service lifecycle, on average, 10 – 15 years.

Their target is a real PLM-platform implementation connecting the people, the processes, data, and systems. Their aim is really about the “connected” approach, a characteristic of a digital company.

As you can still watch the presentation, look at the following topics discussed:

  • focus on product archetypes instead of division (portfolio management)
  • data templates based on classification, global and specific data sets (data governance)
  • the need to have a Master Data Management in place (data governance)
  • the unique product identifier (remember the FFF-discussion in my blog)
  • data-driven documentation (a perfect example of a digital PLM implementation)
  • platform strategy (one application for one capability in a heterogeneous systems environment)
  • Ownership of the PLM implementation at board level (it is not an engineering tool)
  • in the Q&A – the mix of waterfall & agile – the hybrid approach (as in the medical world the validation of the system is required – a point we missed in the SmarTeam FDA toolkit – validation of a system is needed when the system/processes change)

In the Q&A session, it was clear that the big elephant in the room, the migration, has been identified, but no answers yet. See my presentation to understand the reference to the elephant.  I am curious about B. Braun’s approach, given my experience with PLM digital transformations. Will it be entirely digital or hybrid.

Looking forward to learning more from Fabien or Philip.

Business drivers for Sustainable Manufacturing

This session, presented by Hannes Lindfred from TECHNIA, was one of my favorite presentations,  as it links tightly to what we want to achieve with the PLM Green Alliance.

The subtitle of the presentation says it all: “How PLM can support Supply chain transparency, Circular economy, and System oriented product development”.

In a relaxed and entertaining manner, he explained the concepts and the needs of a circular economy, combined with examples from reality. In particular, I liked his closing statement linking the potential of digitization, modern PLM, and the circular economy. We have to learn to think and act circular. Highly recommended to watch!

Leading PLM Trends & Potential Disruptors

A PLM conference would not be a PLM-conference if Peter Bilello from CIMdata would not be speaking. We share a lot of insights related to digital transformation and the understanding it requires the involvement of PLM. However, it is not the traditional PLM that is needed.

PLM needs to be rethought, think about the concept of a Product Innovation Platform. A digital platform is required if we want end-to-end digitalization; otherwise, we keep working in optimized silos.

Peter shared some survey results (see below) from early this year. It illustrates that most companies currently invest in traditional PDM aspects. Restating the need for our PLM communities to learn and educate and rethink aspects of PLM and learn to communicate them.

Remarkably similar to some of the aspects I explained in my: From Coordinated to Connected presentations. Changing to data, changing workforce, changing processes meaning systems thinking. Another plea for everyone to invest in learning. See his concluding remarks:

The closing Q&A session was interesting, addressing additive manufacturing, the graph database, and potential PLM disruptors coming from outside the traditional PLM space.

I recommend, pay attention to the closing questions – so many good points to put PLM in perspective.

From Coordinated to Connected & Sustainable

Of course, I recommend you watch my presentation. It is one of the few opportunities to hear in a short time all the thoughts and concepts that I developed over the past 5 – 6 years. It saves you reading all my blog posts, which are less structured than this presentation.

I recommend you to watch this presentation in the context of Peter Bilello’s presentation as there are a lot of similarities, told in different words.

After my presentation, I appreciated the Q&A part, as it allowed me to point to some more of the related topics: Legacy CAD-issues – the incompatibility of the past and future data, Management vision and the Perception of ROI.

 

Professional PLM
Raise your standards and your horizons

An interesting presentation to watch, after seeing Peter Bilello’s presentation and my presentation,  is the one given by Roger Tempest. Roger is another veteran in the PLM-world and co-founder of the PLM Interest group. For many years Roger is striving to get the PLM professional recognized and certified. We both share the experience that being a PLM consultant is not a profession to become wealthy.

One of the reasons might be that the scope of PLM and what is the required skill level is not precise. PLM considered as an engineering tool and PLM having so many diverse definitions.

The challenge of Roger’s approach is that it tries to capture people within a standardized PLM framework, which becomes apparent in the Q&A session. Currently, he is in the stage of building a steering group, “looking for companies that are fairly committed to PLM”. So which companies are the ones interested in PLM to commit time and resources to build a professional PLM body? This can be only academic people and PLM Vendors/Implementers. The last group will probably not likely agree on standardization.

Also related to the question about the different industries and maturity levels for companies came with an unsatisfactory answer. He talks about “absolute” PLM and no need to compare PLM with other industries. Here I believe there is such a fundamental difference in the meaning of PLM when talking to the traditional manufacturing companies as compared to high-tech/software-driven industries. I inserted here Marc Halpern’s maturity/technology diagram that I have been referencing in my presentation too.

The final question about vendors joining the PLM standardization group seems to be a utopia. As I expressed in my presentation, referring to Marc Halpern’s business maturity diagram, the vendors show us the vision of various business aspects related to PLM.

Marc already indicated this is the phase of the Product Innovation Platform.

As long as the professional PLM organization is focusing on defining the standard, I foresee the outside world will move faster and be more diverse than a single PLM expert can handle. A typical issue with many other standards as you can see below.

What’s Next

I hope to see and participate more in virtual PLM conferences as it allows much larger audiences to connect compared to traditional conferences. However, there are things to improve, and therefore I want to propose some enhancements:

Make sure during the “live” sessions, there is the experience of “being live and connected”. Even when streaming a pre-recorded lecture, always follow-up immediately with a live Q&A session. I found the Q&A sessions very educative as they clarify or put the presentation in a broader context.

The current virtual booth as only a chat room is too primitive – it reminded me of the early days of internet communication – discussion groups in ASCII-terminal mode through Compuserve (remember). A booth could become a virtual meeting space on its own – all, of course, depending on the amount of bandwidth available. The feeling of “The Doctor is in”

It is great that the content is available for 30 days, and I agree there is a need for a time limit on the content; otherwise, the conference becomes more a library. What I would like to see after the “live” days to still have a kind of place for sharing. What are your favorite presentations, and why should others look at it?

 

Conclusion

A great event and learning experience for me. Virtual conferences are the future for sure, and I encourage others to develop this type of conferences related to PLM further. It is a way to share knowledge and discuss topics in a sustainable manner. In the upcoming 30 days, I will come back to the conference one more time, based on interesting topics discovered or discussion related to the content. 

Meanwhile, I encourage you too – if you are still in lockdown and if there is time to study – this is one of these unique opportunities.

 

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