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When I started working with SmarTeam Corp.  in 1999, the company had several product managers, who were responsible for the whole lifecycle of a component or technology. The Product Manager was the person to define the features for the new release and provide the justification for these new features internally inside R&D.  In addition the Product Manager had the external role to visit customers and understand their needs for future releases and building and explaining a coherent vision to the outside and internal world. The product manager had a central role, connecting all stakeholders.

In the ideal situation the Product Manager was THE person who could speak in R&D-language about the implementation of features, could talk with marketing and documentation teams to explain the value and expected behavior and could talk with the customer describing the vision, meanwhile verifying the product’s vision and roadmap based on their inputs.All these expected skills make the role of a product manager challenging. Is the person too “techy” than he/she will enjoy working with R&D but have a hard time understanding customer demands. From the other side if the Product Manager is excellent in picking-up customer and market feedback he/she might not be heard and get the expected priorities from R&D. For me, it has always been clear that in software world a “bi-directional” Product Manager is crucial to success.

Where are the Product Managers in the Manufacturing Industry?

Approximate four years ago new concepts related to digitalization for PLM became more evident. How could a digital continuity connect the various disciplines around the product lifecycle and therefore provide end-to-end visibility and traceability? When speaking of end-to-end visibility most of the time companies talked about the way they designed and delivered products, visibility of what is happening stopped most of the time after manufacturing. The diagram to the left, showing a typical Build To Order organization illustrates the classical way of thinking. There is an R&D team working on Innovation, typically a few engineers and most of the engineers are working in Sales Engineering and Manufacturing Preparation to define and deliver a customer specific order. In theory, once delivered none of the engineers will be further involved, and it is up to the Service Department to react to what is happening in the field.

A classical process in the PLM domain is the New Product Introduction process for companies that deliver products in large volumes to the market, most of the time configurable to be able to answer to various customer or pricing segments. This process is most of the time linear and is either described in one stream or two parallel streams. In the last case, the R&D department develops new concepts and prepares the full product for the market. However, the operational department starts in parallel, initially involved in strategic sourcing, and later scaling-up manufacturing disconnected from R&D.

I described these two processes because they both illustrate how disconnected the source (R&D/ Sales)  are from the final result in the field. In both cases managed by the service department. A typical story that I learned from many manufacturing companies is that at the end it is hard to get a full picture from what is happening across the whole lifecycle, How external feedback (market & customers) have the option to influence at any stage is undefined. I used the diagram below even  before companies were even talking about a customer-driven digital transformation. Just understanding end-to-end what is happening with a product along the lifecycle is already a challenge for a company.

Putting the customer at the center

Modern business is about having customer or market involvement in the whole lifecycle of the product. And as products become more and more a combination of hardware and software, it is the software that allows the manufacturer to provide incremental innovation to their products. However, to innovate in a manner that is matching or even exceeding customer demands, information from the outside world needs to travel as fast as possible through an organization. In case this is done in isolated systems and documents, the journey will be cumbersome and too slow to allow a company to act fast enough. Here digitization comes in, making information directly available as data elements instead of documents with their own file formats and systems to author them. The ultimate dream is a digital enterprise where date “flows”, advocated already by some manufacturing companies for several years.

In the previous paragraph I talked about the need to have an infrastructure in place for people in an organization to follow the product along the complete lifecycle, to be able to analyze and improve the customer experience. However, you also need to create a role in the organization for a person to be responsible for combining insights from the market and to lead various disciplines in the organization, R&D, Sales, Services. And this is precisely the role of a Product Manager.

Very common in the world of software development, not yet recognized in manufacturing companies. In case a product manager role exists already in your organization, he/she can tell you how complicated it currently is to get an overall view of the product and which benefits a digital infrastructure would bring for their job. Once the product manager is well-supported and recognized in the organization, the right skill set to prioritize or discover actions/features will make the products more attractive for consumers. Here the company will benefit.

Conclusion

If your company does not have the role of a product manager in place, your business is probably not yet well enough engaged in the customer journey.  There will be broken links and costly processes to get a fast response to the market.  Consider the role of a Product Manager, which will emerge as seen from the software business.

NOTE 1: Just before publishing this post I read an interesting post from Jan Bosch: Structure Eats Strategy. Well fitting in this context

NOTE 2: The existence of a Product Manager might be a digital maturity indicator for a company, like for classical PLM maturity, the handling of the MBOM (PDM/PLM/ERP) gives insight into PLM maturity of a company.

Related to the MBOM, please read: The Importance of a PLM data model – EBOM and MBOM

 

 

 

 

 

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This post is a rewrite of an article I wrote on LinkedIn two years ago and modified it to my current understanding. When you are following my blog, in particular, the posts related to the business change needed to transform a company towards a data-driven digital enterprise, one of the characteristics of digital is about the real-time availability of information. This has an impact on everyone working in such an organization. My conversations are in the context of PLM (Product Lifecycle Management) however I assume my observations are valid for other domains too.

Real-time visibility is going to be the big differentiator for future businesses, and in particular, in the PLM domain, this requires a change from document-centric processes towards data-driven processes.

Documents have a lot of disadvantages.  Documents lock information in a particular format and document handling results in sequential processes, where one person/one discipline at the time is modifying or adding content. I described the potential change in my blog post: From a linear world to fast and circular?

From a linear world to fast and circular

In that post, I described that a more agile and iterative approach to bring products and new enhancements to the market should have an impact on current organizations. A linear organization, where products are pushed to the market, from concept to delivery, is based on working in silos and will be too slow to compete against future, modern digital enterprises. This because departmental structures with their own hierarchy block fast moving of information, and often these silos perform filtering/deformation of the information.  It becomes hard to have a single version of the truth as every department, and its management will push for their measured truth.

A matching business model related to the digital enterprise is a matrix business model, where multi-disciplinary teams work together to achieve their mission. An approach that is known in the software industry, where parallel and iterative work is crucial to continuous deliver incremental benefits.

Image:  21stcenturypublicservant.wordpress.com/

In a few of my projects, I discovered this correlation with software methodology that I wanted to share. One of my clients was in the middle of moving from a document-centric approach toward a digital information backbone, connecting the RFQ phase and conceptual BOM through design, manufacturing definition, and production. The target was to have end-to-end data continuity as much as possible, meanwhile connecting the quality and project tasks combined with issues to this backbone.

The result was that each individual had a direct view of their current activities, which could be a significant quantity for some people engaged in multiple projects.  Just being able to measure these numbers already lead to more insight into an individual’s workload. At the time we discussed with the implementation team the conceptual dashboard for an individual, it lead to questions like: “Can the PLM system escalate tasks and issues to the relevant manager when needed?” and  “Can this escalation be done automatically? “

And here we started the discussion. “Why do you want to escalate to a manager?”  Escalation will only give more disruption and stress for the persons involved. Isn´t the person qualified enough to make a decision what is important?

One of the conclusions of the discussion was that currently, due to lack of visibility of what needs to be done and when and with which urgency, people accept things get overlooked. So the burning issues get most of the attention and the manager’s role is to make things burning to get it done.

When discussing further, it was clear that thanks to the visibility of data, real critical issues will appear at the top of an individual’s dashboard. The relevant person can immediately overlook what can be achieved and if not, take action. Of course, there is the opportunity to work on the easy tasks only and to ignore the tough ones (human behavior) however the dashboard reveals everything that needs to be done – visibility. Therefore if a person learns to manage their priorities, there is no need for a manager to push anymore, saving time and stress.

The ultimate conclusion of our discussion was: Implementing a modern PLM environment brings first of all almost 100 % visibility, the single version of the truth. This new capability breaks down silos, a department cannot hide activities behind their departmental wall anymore. Digital PLM allows horizontal multidisciplinary collaboration without the need going through the management hierarchy.

It would mean Power to People, in case they are stimulated to do so. And this was the message to the management: “ you have to change too, empower your people.”

What do you think – will this happen? This was my question in 2015.  Now two years later I can say some companies have seen the potential of the future and are changing their culture to empower their employees working in multidisciplinary teams. Other companies, most of the time with a long history in business, are keeping their organizational structure with levels of middle management and maintain a culture that consolidates the past.

Conclusion

A digital enterprise empowers individuals allowing companies to become more proactive and agile instead of working within optimized silos. In silos, it appears that middle management does not trust individuals to prioritize their work.  The culture of a company and its ability to change are crucial for the empowerment of individuals The last two years there is progress in understanding the value of empowered multidisciplinary teams.

Is your company already empowering people ? Let us know !

Note: After speaking with Simon, one of my readers who always gives feedback from reality, we agreed that multidisciplinary teams are very helpful for organizations. However you will still need a layer of strategic people securing standard ways of working and future ways of working as the project teams might be to busy doing their job. We agreed this is the role for modern middle management.
DO YOU AGREE ?

Last week I posted my first review of the PDT Europe conference. You can read the details here: The weekend after PDT Europe (part 1).  There were some questions related to the abbreviation PDT. Understanding the history of PDT, you will discover it stands for Product Data Technology. Yes, there are many TLA’s in this world.

Microsoft’s view on the digital twin

Now back to the conference. Day 2 started with a remote session from Simon Floyd. Simon is Microsoft’s Managing Director for Manufacturing Industry Architecture Enterprise Services and a frequent speaker at PDT. Simon shared with us Microsoft’s viewpoint of a Digital Twin, the strategy to implement a Digit Twin, the maturity status of several of their reference customers and areas these companies are focusing. From these customers it was clear most companies focused on retrieving data in relation to maintenance, providing analytics and historical data. Futuristic scenarios like using the digital twin for augmented reality or design validation. As I discussed in the earlier post, this relates to my observations, where creating a digital thread between products in operations is considered as a quick win. Establishing an end-to-end relationship between products in operation and their design requires many steps to fix. Read my post: Why PLM is the forgotten domain in digital transformation.

When discussing the digital twin architecture, Simon made a particular point for standards required to connect the results of products in the field. Connecting a digital twin in a vendor-specific framework will create a legacy, vendor lock-in, and less open environment to use digital twins. A point that I also raised in my presentation later that day.

Simon concluded with a great example of potential future Artificial Intelligence, where an asset based on its measurements predicts to have a failure before the scheduled maintenance stop and therefore requests to run with a lower performance so it can reach the maintenance stop without disruption.

Closing the lifecycle loop

Sustainability and the circular economy has been a theme at PDT for some years now too. In his keynote speech, Torbjörn Holm from Eurostep took us through the global megatrends (Hay group 2030) and the technology trends (Gartner 2018) and mapped out that technology would be a good enabler to discuss several of the global trends.

Next Torbjörn took us through the reasons and possibilities (methodologies and tools) for product lifecycle circularity developed through the ResCoM project in which Eurostep participated.

The ResCoM project (Resource Conservative Manufacturing) was a project co-funded by the European Commission and recently concluded. More info at www.rescom.eu

Torbjörn concluded discussing the necessary framework for Digital Twin and Digital Thread(s), which should be based on a Model-Based Definition, where ISO 10303 is the best candidate.

Later in the afternoon, there were three sessions in a separate track, related to design optimization for value, circular and re-used followed by a panel discussion. Unfortunate I participated in another track, so I have to digest the provided materials still. Speakers in that track were Ola Isaksson (Chalmers University), Ingrid de Pauw & Bram van der Grinten (IDEAL&CO) and Michael Lieder (KTH Sweden)

Connecting many stakeholders

Rebecca Ihrfors, CIO from the Swedish Defense Material Administration (FMV) shared her plans on transforming the IT landscape to harmonize the current existing environments and to become a broker between industry and the armed forces (FM). As now many of the assets come with their own data sets and PDM/PLM environments, the overhead to keep up all these proprietary environments is too expensive and fragmented. FWM wants to harmonize the data they retrieve from industry and the way they offer it to the armed forces in a secure way. There is a need for standards and interoperability.

The positive point from this presentation was that several companies in the audience and delivering products to Swedish Defense could start to share and adapt their viewpoints how they could contribute.

Later in the afternoon, there were three sessions in a separate track rented to standards for MBE inter-operability and openness that would fit very well in this context. Brian King (Koneksys), Adrian Murton (Airbus UK) and Magnus Färneland (Eurostep) provided various inputs, and as I did not attend these parallel sessions I will dive deeper in their presentations at a later time

PLM something has to change – bimodal and more

In my presentation, which you can download from SlideShare here: PLM – something has to change. My main points were related to the fact that apparently, companies seem to understand that something needs to happen to benefit really from a digital enterprise. The rigidness from large enterprise and their inhibitors to transform are more related to human and incompatibility issues with the future.

How to deal with this incompatibility was also the theme for Martin Eigner’s presentation (System Lifecycle Management as a bimodal IT approach) and Marc Halpern’s closing presentation (Navigating the Journey to Next Generation PLM).

Martin Eigner’s consistent story was about creating an extra layer on top of the existing (Mode 1) systems and infrastructure, which he illustrated by a concept developed based on Aras.

By providing a new digital layer on top of the existing enterprise, companies can start evolving to a modern environment, where, in the long-term, old Mode 1 systems will be replaced by new digital platforms (Mode 2). Oleg Shilovitsky wrote an excellent summary of this approach. Read it here: Aras PLM  platform “overlay” strategy explained.

Marc Halpern closed the conference describing his view on how companies could navigate to the Next Generation PLM by explaining in more detail what the Gartner bimodal approach implies. Marc’s story was woven around four principles.

Principle 1 The bimodal strategy as the image shows.

Principle 2 was about Mode 1 thinking in an evolutionary model. Every company has to go through maturity states in their organization, starting from ad-hoc, departmental, enterprise-based to harmonizing and fully digital integrated. These maturity steps also have to be taken into account when planning future steps.

Principle 3 was about organizational change management, a topic often neglected or underestimated by product vendors or service providers as it relates to a company culture, not easy to change and navigate in a particular direction.

Finally, Principle 4 was about Mode 2 activities. Here an organization should pilot (in a separate environment), certify (make sure it is a realistic future), adopt (integrate it in your business) and scale (enable this new approach to exists and grow for the future).

Conclusions

This post concludes my overview of PDT Europe 2017. Looking back there was a quiet aligned view of where we are all heading with PLM and related topics. There is the hype an there is reality, and I believe this conference was about reality, giving good feedback to all the attendees what is really happening and understood in the field. And of course, there is the human factor, which is hard to influence.

Share your experiences and best practices related to moving to the next generation of PLM (digital PLM ?) !

 

 

 

PDT Europe is over, and it was this year a surprising aligned conference, showing that ideas and concepts align more and more for modern PLM. Håkan Kårdén opened the conference mentioning the event was fully booked, about 160 attendees from over 19 countries. With a typical attendance of approx. 120 participants, this showed the theme of the conference: Continuous Transformation of PLM to support the Lifecycle Model-Based Enterprise was very attractive and real. You can find a history of tweets following the hashtag #pdte17

Setting the scene

Peter Bilello from CIMdata kicked-off by bringing some structure related to the various Model-Based areas and Digital Thread. Peter started by mentioning that technology is the least important issue as organization culture, changing processing and adapting people skills are more critical factors for a successful adoption of modern PLM. Something that would repeatedly be confirmed by other speakers during the conference.

Peter presented a nice slide bringing the Model-Based terminology together on one page. Next, Peter took us through various digital threads in the different stages of the product lifecycle. Peter concluded with the message that we are still in a learning process redefining optimal processes for PLM, using Model-Based approaches and Digital Threads and thanks (or due) to digitalization these changes will be rapid. Ending with an overall conclusion that we should keep in mind:


It isn’t about what we call digitalization; It is about delivering value to customers and all other stakeholders of the enterprise

Next Marc Halpern busted the Myth of Digital Twins (according to his session title) and looked into realistic planning them. I am not sure if Marc smashed some of the myths although it is sure Digital Twin is at the top of the hype cycle and we are all starting to look for practical implementations. A digital twin can have many appearances and depends on its usage. For sure it is not just a 3D Virtual model.

There are still many areas to consider when implementing a digital twin for your products. Depending on what and how you apply the connection between the virtual and the physical model, you have to consider where your vendor really is in maturity and avoid lock in on his approach. In particular, in these early stages, you are not sure which technology will last longer, and data ownership and confidentially will play an important role. And opposite to quick wins make sure your digital twin is open and use as much as possible open standards to stay open for the future, which also means keep aiming for working with multiple vendors.

Industry sessions

Next, we had industry-focused sessions related to a lifecycle Model-Based enterprise and later in the afternoon a session from Outotec with the title: Managing Installed Base to Unlock Service opportunities.

The first presentation from Väino Tarandi, professor in IT in Construction at KTH Sweden presented his findings related to BIM and GIS in the context of the lifecycle, a test bed where PLCS meets IFC. Interesting as I have been involved in BIM Level 3 discussions in the UK, which was already an operational challenge for stakeholders in the construction industry now extended with the concept of the lifecycle. So far these projects are at the academic level, and I am still waiting for companies to push and discover the full benefits of an integrated approach.

Concepts for the industrial approach could be learned from Outotec as you might understand later in this post. Of course the difference is that Outotec is aiming for data ownership along the lifecycle, where in case of the construction industries, each silo often is handled by a different contractor.

Fredrik Ekström from Swedish Transport Administration shared his challenges of managing assets for both road and railway transport – see image on the left. I have worked around this domain in the Netherlands, where asset management for infrastructure and asset management for the rail infrastructure are managed in two different organizations. I believe Fredrik (and similar organizations) could learn from the concepts in other industries. Again Outotec’s example is also about having relevant information to increase service capabilities, where the Swedish Transport Administration is aiming to have the right data for their services. When you look at the challenges reported by Fredrik, I assume he can find the answers in other industry concepts.

Outotec’s presentation related to managing installed base and unlock service opportunities explained by Sami Grönstrand and Helena Guiterrez was besides entertaining easy to digest content and well-paced. Without being academic, they explained somehow the challenges of a company with existing systems in place moving towards concepts of a digital twin and the related data management and quality issues. Their practical example illustrated that if you have a clear target, understanding better a customer specific environment to sell better services, can be achieved by rational thinking and doing, a typical Finish approach. This all including the “bi-modal approach” and people change management.

Future Automotive

Ivar Hammarstadt, Senior Analyst Technology Intelligence for Volvo Cars Corporation entertained us with a projection toward the future based on 160 years of automotive industry. Interesting as electrical did not seem to be the only way to go for a sustainable future depending on operational performance demands.

 

Next Jeanette Nilsson and Daniel Adin from Volvo Group Truck shared their findings related to an evaluation project for more than one year where they evaluated the major PLM Vendors (Dassault Systemes / PTC / Siemens) on their Out-of-the-box capabilities related to 3D product documentation and manufacturing.

They concluded that none of the vendors were able to support the full Volvo Truck complexity in a OOTB matter. Also, it was a good awareness project for Volvo Trucks organization to understand that a common system for 3D geometry reduces the need for data transfers and manual data validation. Cross-functional iterations can start earlier, and more iterations can be performed. This will support a shortening of lead time and improve product quality. Personally, I believe this was a rather expensive approach to create awareness for such a conclusion, pushing PLM vendors in a competitive pre-sales position for so much detail.

Future Aerospace

Kenny Swope from Boeing talked us through the potential Boeing journey towards a Model-Based Enterprise. Boeing has always been challenging themselves and their partners to deliver environments close to what is possible. Look at the Boeing journey and you can see that already in 2005 they were aiming for an approach that most of current manufacturing enterprises cannot meet. And now they are planning their future state.

To approach the future state Boeing aims to align their business with a single architecture for all aspects of the company. Starting with collecting capabilities (over 400 in 6 levels) and defining value streams (strategic/operational) the next step is mapping the capabilities to the value streams.  Part of the process would be to look at the components of a value stream if they could be fulfilled by a service. In this way you design your business for a service-oriented architecture, still independent from any system constraints. As Kenny states the aerospace and defense industry has a long history and therefore slow to change as its culture is rooted in the organization. It will be interesting to learn from Kenny next hear how much (mandatory) progress towards a model-based enterprise has been achieved and which values have been confirmed.

Gearing up for day 2

Martin Eigner took us in high-speed mode through his vision and experience working in a bi-modular approach with Aras to support legacy environments and a modern federated layer to support the complexity of a digital enterprise where the system architecture is leading. I will share more details on these concepts in my next post as during day 2 of PDT Europe both Marc Halpern and me were talking related to this topic, and I will combine it in a more extended story.

The last formal presentation for day one was from Nigel Shaw from Eurostep Ltd where he took us through the journey of challenges for a model-based enterprise. As there will not be a single model that defines all, it will be clear various models and derived models will exist for a product/system.  Interesting was Nigel’s slide showing the multiple models disciplines can have from an airplane (1948). Similar to the famous “swing” cartoon, used to illustrate that every single view can be entirely different from the purpose of the product.

Next are these models consistent and still describing the same initial specified system. On top of that, even the usage of various modeling techniques and tools will lead to differences in the system. And the last challenge on top is managing the change over the system’s lifecycle. From here Nigel stepped into the need for digital threads to govern relations between the various views per discipline and lifecycle stage, not only for the physical and the virtual twin.  When comparing the needs of a model-based enterprise through its lifecycle, Nigel concluded that using PLCS as a framework provides an excellent fit to manage such complexity.

Finally, after a panel discussion, which was more a collection of opinions as the target was not necessary to align in such a short time, it was time for the PDT dinner always an excellent way to share thoughts and verify them with your peers.

Conclusion

Day 1 was over before you knew it without any moment of boredom and so I hope is also this post. Next week I will close reviewing the PDT conference with some more details about my favorite topics.

 

As I am preparing my presentation for the upcoming PDT Europe 2017 conference in Gothenburg, I was reading relevant experiences to a data-driven approach. During PDT Europe conference we will share and discuss the continuous transformation of PLM to support the Lifecycle Model-Based Enterprise. 

One of the direct benefits is that a model-based enterprise allows information to be shared without the need to have documents to be converted to a particular format, therefore saving costs for resources and bringing unprecedented speed for information availability, like what we are used having in a modern digital society.

For me, a modern digital enterprise relies on data coming from different platforms/systems and the data needs to be managed in such a manner that it can serve as a foundation for any type of app based on federated data.

This statement implies some constraints. It means that data coming from various platforms or systems must be accessible through APIs / Microservices or interfaces in an almost real-time manner. See my post Microservices, APIs, Platforms and PLM Services. Also, the data needs to be reliable and understandable for machine interpretation. Understandable data can lead to insights and predictive analysis. Reliable and understandable data allows algorithms to execute on the data.

Classical ECO/ECR processes can become highly automated when the data is reliable, and the company’s strategy is captured in rules. In a data-driven environment, there will be much more granular data that requires some kind of approval status. We cannot do this manually anymore as it would kill the company, too expensive and too slow. Therefore, the need for algorithms.

What is understandable data?

I tried to avoid as long as possible academic language, but now we have to be more precise as we enter the domain of master data management. I was triggered by this recent post from Gartner: Gartner Reveals the 2017 Hype Cycle for Data Management. There are many topics in the hype cycle, and it was interesting to see Master Data Management is starting to be taken seriously after going through inflated expectations and disillusionment.

This was interesting as two years ago we had a one-day workshop preceding PDT Europe 2015, focusing on Master Data Management in the context of PLM. The attendees at that workshop coming from various companies agreed that there was no real MDM for the engineering/manufacturing side of the business. MDM was more or less hijacked by SAP and other ERP-driven organizations.

Looking back, it is clear to me why in the PLM space MDM was not a real topic at that time. We were still too much focusing and are again too much focusing on information stored in files and documents. The only area touched by MDM was the BOM, and Part definitions as these objects also touch the ERP- and After Sales-  domain.

Actually, there are various MDM concepts, and I found an excellent presentation from Christopher Bradley explaining the different architectures on SlideShare: How to identify the correct Master Data subject areas & tooling for your MDM initiative. In particular, I liked the slide below as it comes close to my experience in the process industry

Here we see two MDM architectures, the one of the left driven from ERP. The one on the right could be based on the ISO-15926 standard as the process industry has worked for over 25 years to define a global exchange standard and data dictionary. The process industry was able to reach such a maturity level due to the need to support assets for many years across the lifecycle and the relatively stable environment. Other sectors are less standardized or so much depending on new concepts that it would be hard to have an industry-specific master.

PLM as an Application Specific Master?

If you would currently start with an MDM initiative in your company and look for providers of MDM solution, you will discover that their values are based on technology capabilities, bringing data together from different enterprise systems in a way the customer thinks it should be organized. More a toolkit approach instead of an industry approach. And in cases, there is an industry approach it is sporadic that this approach is related to manufacturing companies. Remember my observation from 2015: manufacturing companies do not have MDM activities related to engineering/manufacturing because it is too complicated, too diverse, too many documents instead of data.

Now with modern digital PLM, there is a need for MDM to support the full digital enterprise. Therefore, when you combine the previous observations with a recent post on Engineering.com from Tom Gill: PLM Initiatives Take On Master Data Transformation I started to come to a new hypotheses:

For companies with a model-based approach that has no MDM in place, the implementation of their Product Innovation Platform (modern PLM) should be based on the industry-specific data definition for this industry.

Tom Gill explains in his post the business benefits and values of using the PLM as the source for an MDM approach. In particular, in modern PLM environments, the PLM data model is not only based on the BOM.  PLM now encompasses the full lifecycle of a product instead of initially more an engineering view. Modern PLM systems, or as CIMdata calls them Product Innovation Platforms, manage a complex data model, based on a model-driven approach. These entities are used across the whole lifecycle and therefore could be the best start for an industry-specific MDM approach. Now only the industries have to follow….

Once data is able to flow, there will be another discussion: Who is responsible for which attributes. Bjørn Fidjeland from plmPartner recently wrote: Who owns what data when …?  The content of his post is relevant, I only would change the title: Who is responsible for what data when as I believe in a modern digital enterprise there is no ownership anymore – it is about sharing and responsibilities

 

Conclusion

Where MDM in the past did not really focus on engineering data due to the classical document-driven approach, now in modern PLM implementations, the Master Data Model might be based on the industry-specific data elements, managed and controlled coming from the PLM data model

 

Do you follow my thoughts / agree ?

 

 

At this moment there are two approaches to implement PLM. The most common practice is item-centric and model-centric will be potentially the best practice for the future. Perhaps your company still using a method from the previous century called drawing-centric. In that case, you should read this post with even more attention as there are opportunities to improve.

 

The characteristics of item-centric

In an item-centric approach, the leading information carrier is an item also known as a part. The term part is sometimes confusing in an organization as it is associated with a 3D CAD part. In SAP terminology the item is called Material, which is sometimes confusing for engineering as they consider Material the raw material. Item-centric is an approach where items are managed and handled through the whole lifecycle. In theory, an item can be a conceptual item (for early estimates), a design item (describing the engineering intent), a manufacturing item (defining how an item is consumed) and potentially a service item.

The picture below illustrates the various stages of an item-centric approach. Don’t focus on the structure, it’s an impression.

It is clear these three structures are different and can contain different item types. To read more about the details for an EBOM/MBOM approach read these post on my blog:

Back to item-centric. This approach means that the item is the leading authority of the product /part. The id and revision describe the unique object in the database, and the status of the item tells you in the current lifecycle stage for the item. In some cases, where your company makes configurable products also the relation between two items can define effectivity characteristics, like data effectivity, serial number effectivity and more. From an item structure, you can find its related information in context. The item points to the correct CAD model, the assembly or related manufacturing drawings, the specifications. In case of an engineering item, it might point towards approved manufacturers or approved manufacturing items.

Releasing an item or a BOM means the related information in context needs to validated and frozen too. In case your company works with drawings for manufacturing, these drawings need to be created, correct and released, which sometimes can be an issue due to some last-minute changes that can happen. The above figure just gives an impression of the potential data related to an item. It is important to mention that reports, which are also considered documents, do not need an approval as they are more a snapshot of the characteristics at that moment of generation.

The advantages of an item-centric approach are:

  • End-to-end traceability of information
  • Can be implemented in an evolutionary approach after PDM-ERP without organizational changes
  • It enables companies to support sharing of information
  • Sharing of information forces companies to think about data governance
    (not sure if a company wants to invest on that topic)

The main disadvantages of an item-centric approach are:

  • Related information on the item is not in context and therefore requires its own management and governance to ensure consistency
  • Related information is contained in documents, where availability and access is not always guaranteed

Still, the item-centric approach brings big benefits to a company that was working in a classical drawing-driven PDM-ERP approach. An additional remark needs to be made that not every company will benefit from an item-centric approach as typically Engineering-to-Order companies might find this method creating too much overhead.

The characteristics of Model-Centric

A model-centric approach is considered the future approach for modern enterprises as it brings efficiency, speed, multidisciplinary collaboration and support for incremental innovation in an agile way. When talking about a model-centric approach, I do not mean a 3D CAD model-centric approach. Yes, in case the product is mature, there will be a 3D Model serving as a base for the physical realization of the product.

However, in the beginning, the model can be still a functional or logical model. In particular, for complex products, model-based systems engineering might be the base for defining the solution. Actually, when we talk about products that interact with the outside world through software, we tend to call them systems. This explains that model-based systems engineering is getting more and more a recommended approach to make sure the product works as expected, fulfills all the needs for the product and creates a foundation for incremental innovation without starting from scratch.

Where the model-based architecture provides a framework for all stakeholders, the 3D CAD model will be the base for a digital thread towards manufacturing. Linking parameters from the logical and functional model towards the physical model a connection is created without the need to create documents or input-files for other disciplines. Adding 3D Annotations to the 3D CAD model and manufacturing process steps related to the model provides a direct connection to the manufacturing process.

The primary challenge of this future approach is to have all these data elements (requirements, functions, components, 3D design instances, manufacturing processes & resources to be connected in a federated environment (the product innovation platform). Connecting, versioning and baselining are crucial for a model-centric approach. This is what initiatives like Industry 4.0 are now exploring through demonstrators, prototypes to get a coherent collection of managed data.

Once we are able to control this collection of managed data concepts of digital twin or even virtual twin can be exploited linking data to a single instance in the field.

Also, the model can serve as the foundation for introduction incremental innovation, bringing in new features.  As the model-based architecture provides direct visibility for change impact (there are no documents to study), it will be extremely lean and cost-efficient to innovate on an existing product.

Advantages of model-centric

  • End-to-end traceability of all data related to a product
  • Extremely efficient in data-handling – no overhead on data-conversions
  • Providing high-quality understanding of the product with reduced effort compared to drawing-centric or item-centric approaches
  • It is scalable to include external stakeholders directly (suppliers/customers) leading to potential different, more beneficial business models
  • Foundation for Artificial Intelligence at any lifecycle step.

Disadvantages of model-centric

  • It requires a fundamentally different way of working compared to past. Legacy departments, legacy people, and legacy data do not fit directly into the model-centric approach. A business transformation is required, not evolution.
  • It is all about sharing data, which requires an architecture that is built to share information across Not through a service bus but as a (federated) platform of information.
    A platform requires a strong data governance, both from the dictionary as well as authorizations which discipline is leading/following.
  • There is no qualified industrial solution from any vendor yet at this time. There is advanced technology, there are demos, but to my knowledge, there is no 100% model-centric enterprise yet. We are all learning. Trying to distinguish reality from the hype.

 

Conclusions

The item-centric approach is the current best practice for most PLM implementations. However, it has the disadvantage that it is not designed for a data-driven approach, the foundation of a digital enterprise. The model-centric approach is new. Some facets already exist. However, for the total solution companies, vendors, consultants, and implementers are all learning step-by-step how it all connects. The future of model-centric is promising and crucial for survival.

Do you want to learn where we are now related to a model-centric approach?
Come to PDT2017 in Gothenburg on 18-19th October and find out more from the experts and your peers.

PLM holiday thoughts

July and August are the months that privileged people go on holiday. Depending on where you live and work it can be a long weekend or a long month. I plan to give my PLM twisted brain a break for two weeks. I am not sure if it will happen as Greek beaches always have inspired for philosophers. What do you think about “PLM on the beach”?

There are two topics that keep me intrigued at this moment, and I hope to experience more about them the rest of the year.

Moving to Model-Based processes

I believe we all get immune for the term “Digital Transformation” (11.400.000 hits on Google today). I have talked about digital transformation in the context many times too. Change is happening. The classic ways of working were based on documents, a container of information, captured on paper (very classical) or captured in a file (still current).

As every stakeholder in a company (marketing, engineering, manufacturing, supplier, services, customers, and management) required a different set of information, many pieces of information all referring to the same product, have been parsed and modified into other documents.  It is costly and expensive to get a complete view of what is happening in the business. Meanwhile, all these information transformations (with Excel as the king) are creating an overhead for information management, both on IT-level and even more for non-value added resources who are manipulating information for the next silo/discipline.

What we have learned from innovative companies is that a data-driven approach, where more granular information is stored uniquely as data objects instead of document containers bring huge benefits. Information objects can be shared where relevant along the product lifecycle and without the overhead of people creating and converting documents, the stakeholders become empowered as they can retrieve all information objects they desire (if allowed). We call this the digital thread.

The way to provide a digital thread for manufacturing companies is to change the way they organize the product development and delivery processes. A model-based approach is required. I wrote about in a post: Digital PLM requires a Model-Based Enterprise a year ago. The term “Model-Based” also has many variations (67.800.00 hits on Google today). Some might consider the 3D MCAD Model at the center of information both for engineering and manufacturing.A good overview in the video below

Others might think about a behavior/simulation model of the product for simulating and delivering a digital twin often referred in the context of model-based design (MBD).

And ultimately a model-based approach integrated with systems engineering into Model-Based Systems Engineering (MBSE) allowing all stakeholders to collaborate in a data-driven manner around complex products based.

You can learn a lot about that during the upcoming PDT Europe conference on 18-19th October in Gothenburg. Concepts and experiences will be shared, and my contribution to the conference will be all about the challenges and lessons learned from the transformation process companies are embarking on becoming model-based.

PLM and ALM

A second topic that becomes more and more relevant for companies is how to combine the domains of product development and application software empowering these products. The challenge here is that we have no mature concepts yet for both domains. It reminds me of the early PDM implementations where companies implemented their PDM system for MCAD software and documents. All the electrical stuff was done disconnected in separate systems and somewhere in the product lifecycle information from MCAD and ECAD was merged in the bill of materials and documents. Mainly manually with a decent overhead for people consolidating the data.  Modern PLM systems have found best practices to manage a combination of mechanical and electronic components through an EBOM even connecting embedded software as an item in the BOM.

Now more and more the behavior and experience of products are driven by software. Sensors and connectivity of data are driving new capabilities and business models to the market. Customers are getting better connected, however also the companies delivering these solutions can act much faster now based on trends or issues experienced from the field.

The challenge, however, is that the data coming from the systems and the software defining the behavior of the products most of the time is managed in a separate environment, the ALM environment. In the ALM environment delivery of new solutions can be extremely fast and agile, creating a disconnect between the traditional product delivery processes and the software delivery processes.

Companies are learning now how to manage the dependencies between these two domains, as consistency of requirements and features of the products is required. Due to the fast pace of software changes, it is almost impossible to connect everything to the PLM product definition. PLM Vendors are working on concepts to connect PLM and ALM through different approaches. Other companies might believe that their software process is crucial and that the mechanical product becomes a commodity. Could you build a product innovation platform starting from the software platform which some of the old industry giants believe?

PLM combined with ALM concepts are the ones to follow, and I am looking forward to meeting the first company that has implemented a consistent flow between the world of hardware and software. So far there are many slide solutions, the reality and legacy at this moment are still inhibitors for the next step.

Conclusion

There is still a lot to discover and execute in the domain of PLM. Moving to a data-driven enterprise with all stakeholders connected is the challenging journey. Can we build robust concepts taking accuracy, security, and speed into account? I believe so, in particular when dreaming at the beach.

 

Bye for now

Potential digital transformation is everywhere. This time I want to share a personal story based on my IoT cycling device from Garmin. Several years ago I became an enthusiastic cyclist, mainly because it clears your mind and cycling keeps you in good shape after enjoying customer visits with great dinners and excellent breakfasts. As the Dutch lack real mountains, we challenge ourselves with through open fields with strong winds to suffer a little too.

 

Four years ago, started tracking my cycling performance, with a Garmin Edge 810. The story of my Garmin is a real IoT story. GPS trackers, in the beginning, did not communicate with the outside world. Now, this device connects to sensors registering my speed, my location, my heart rate, pedal cadence and produced power at any time, finally uploading it to the Garmin Connect platform.

The IoT platform

The Garmin Connect platform gives me insights on my performance, activities, and segments. The segment demonstrates the social part of the platform. Here you can see how you rank with others who have cycled the same track segment over time. And you can register your own preferred segment too, where you challenge yourself and others in your area. So the number of segments is growing continuously. Imagine all these cyclists around the world virtually sharing and taking the same track. I am curious to learn from Garmin how many people are connected to the platform.
I could not find these numbers. You?

The fun of segments

Digital Twin

Through the platform, Garmin collects huge amounts of data of connected users. Each data set of the connected user could be considered a simple digital twin. The Connect platform provides me insights about my overall performance through the years through various reports. Garmin could offer as a (paid) service to deliver insights of my performance compared to other users and propose predictive enhancements similar to the GE Predix platform. The difference of course that 1 % performance improvement for me in cycling does not bring the same value as 1 % performance improvement of a GE product (turbine, jet engine, train, …). However, the concept is the same and GE is promoting themselves as the next Digital Industrial Company, leading in digital transformation. Read more here.

Digital Twin performance

Connecting to the customer

Tthe change from moving from a document-driven approach towards a data-driven approach to collect and store information is not the main concept behind a digital transformation. The data-driven approach is an enabler to connect directly to the customer and change the current business model from delivering products into a business model delivering services or even more advanced delivering experiences. Services and experiences create a closer relation to the customer, more loyalty, but also the challenge that you need to connect to the customer in such a way that the customer sees value. Otherwise, the customer will switch to another service or experience. The Apple, Nespresso, Uber experiences are all known for their new ways of connecting to the customer, differentiating from traditional product sales. Garmin could also be on that list. However, I discovered they are not there yet, despite an IoT-platform and connected devices. What is missing?

Why Garmin is not a digital enterprise.

Two years ago my Garmin Edge started crashing in the middle of a ride. The system rebooted after some minutes, and the recordings were lost or at least unreadable.  When I contacted Garmin support their standard response was: “Please reset the device and update to the latest software.” Two years ago the software had still bug fixes. After two years you would expect a stable experience.

However, a year ago the problems started to become more frequent. I started to send log files illustrating where the error occurred. Still, the Garmin response was the same: “Please reset the device and update to the latest software.”
However as there were no new software updates, there must be another reason why the device failed more and more.

After pushing for a resolution, the service department concluded I needed a new device. There might be an issue with the hardware. A little bit skeptical I agreed on a hardware switch again, and as expected this did not solve the crashes. My guess is that due to the increasing amount of segments at some places, the software gets confused where the rider is exactly located and in which direction the rider is going. These are the moments when the crash happens, and this is probably a software issue.

Still, the Garmin help desk believes there is a hardware problem (preferably swap the device) where I kept on providing evidence data of crashes to support Garmin in their error-discovery. Till now there is no resolution. The good news is that Garmin support mentioned investigating further.

For me, the interaction with Garmin illustrates that the company internally is not yet digital transformed. The service desk probably has KPIs (Key Performance Indicators) related to their response time and problem resolution time. Although I can debate the response time, it is clear that the problem resolution approach: Update to the latest software and if this does not work swap to a new device is not increasing the knowledge from Garmin as a company what their customers are experiencing.

Apparently, their software management is disconnected from the service department and customers. Only clear bugs during the first launch are fixed. Next, it is a disconnected world again.

A must for a digital enterprise is to dive into customer issues and to connect them back to R&D, both for the hardware part and software part. Something a modern product manager would do. If a company is not able to understand the multidisciplinary dependencies and solve issues from the field (with some effort), they will keep on making the same mistakes again with new product launches and lose customers who are looking for a better experience.

My conclusion

PLM should be part of the digital enterprise too as this is the only way to deliver consistent customer value and positive experience. It requires companies to break down silos and create multidisciplinary teams that are capable of supporting the full customer journey. A digital device and a digital customer platform are just facades to the outside world – the inside needs to change too.

What do you think?
Does your company understand the challenges to transform across all disciplines?
Are you managing PLM, ALM, and IoT in context of the product and across the whole lifecycle?
I am curious !

Last week I published a dialogue I had with Flip van der Linden, a fellow Dutchman and millennial, eager to get a grip on current PLM. You can read the initial post here: A PLM dialogue.  In the comments, Flip continued the discussion (look here).  I will elaborate om some parts of his comments and hope some others will chime in. It made me realize that in the early days of blogging and LinkedIn, there were a lot of discussions in the comments. Now it seems we become more and more consumers or senders of information, instead of having a dialogue. Do you agree? Let me know.

Point 1

(Flip) PLM is changing – where lies the new effort for (a new generation of) PLM experts.  I believe a huge effort for PLM is successful change management towards ‘business Agility.’ Since a proper response to an ECR/ECO would evidently require design changes impacting manufacturing and even after-sales and/or legal.  And that’s just the tip of the iceberg.

 

You are right, the main challenge for future PLM experts is to explain and support more agile processes, mainly because software has become a major part of the solution. The classical, linear product delivery approach does not match the agile, iterative approach for software deliveries. The ECR/ECO process has been established to control hardware changes, in particular because there was a big impact on the costs. Software changes are extremely cheap and possible fast, leading to different change procedures. The future of PLM is about managing these two layers (hardware/software) together in an agile way. The solution for this approach is that people have to work in multi-disciplinary teams with direct (social) collaboration and to be efficient this collaboration should be done in a digital way.

A good article to read in this context is Peter Bilello’s article: Digitalisation enabled by product lifecycle management.

 

(Flip) What seems to be missing is an ‘Archetype’ of the ideal transformed organization. Where do PLM experts want to go with these businesses in practice? Personally, I imagine a business where DevOps is the standard, unique products have generic meta-data, personal growth is an embedded business process and supply chain related risks are anticipated on and mitigated through automated analytics. Do you know of such an evolved archetypal enterprise model?

I believe the ideal archetype does not exist yet. We are all learning, and we see examples from existing companies and startups pitching their story for a future enterprise. Some vendors sell a solution based on their own product innovation platform, others on existing platforms and many new vendors are addressing a piece of the puzzle, to be connected through APIs or Microservices. I wrote about these challenges in Microservices, APIs, Platforms and PLM Services.  Remember, it took us “old PLM experts” more than 10-15 years to evolve from PDM towards PLM, riding on an old linear trajectory, caught up by a new wave of iterative and agile processes. Now we need a new generation of PLM experts (or evolving experts) that can combine the new concepts and filter out the nonsense.

Point 2

(Flip) But then given point 2: ‘Model-based enterprise transformations,’ in my view, a key effort for a successful PLM expert would also be to embed this change mgt. as a business process in the actual Enterprise Architecture. So he/she would need to understand and work out a ‘business-ontology’ (Dietz, 2006) or similar construct which facilitates at least a. business processes, b. Change (mgt.) processes, c. emerging (Mfg.) technologies, d. Data structures- and flows, e. implementation trajectory and sourcing.

And then do this from the PLM domain throughout the organization per optimization.  After all a product-oriented enterprise revolves around the success of its products, so eventually, all subsystems are affected by the makeup of the product lifecycle. Good PLM is a journey, not a trip. Or, does a PLM expert merely facilitates/controls this enterprise re-design process? And, what other enterprise ontologism tools and methods do you know of?

Only this question could be a next future blog post. Yes, it is crucial to define a business ontology to support the modern flow of information through an enterprise. Products become systems, depending on direct feedback from the market. Only this last sentence already requires a redefinition of change processes, responsibilities. Next, the change towards data-granularity introduces new ways of automation, which we will address in the upcoming years. Initiatives like Industry 4.0 / Smart Manufacturing / IIoT all contribute to that. And then there is the need to communicate around a model instead of following the old documents path. Read more about it in Digital PLM requires a Model-Based Enterprise. To close this point:  I am not aware of anyone who has already worked and published experiences on this topic, in particular in the context of PLM.

 

Point 3

(Flip) Where to draw the PLM line in a digital enterprise? I personally think this barrier will vanish as Product Lifecycle Management (as a paradigm, not necessarily as a software) will provide companies with continuity, profitability and competitive advantage in the early 21st century. The PLM monolith might remain, but supported by an array of micro services inside and outside the company (next to IoT, hopefully also external data sets).

I believe there is no need to draw a PLM line. As Peter’s article: Digitalisation enabled by product lifecycle management already illustrated there is a need for a product information backbone along the whole (circular) lifecycle, where product information can interact with other enterprise platforms, like CRM, ERP and MES and BI services. Sometimes we will see overlapping functionality, sometimes we will see the need to bridge the information through Microservices. As long as these bridges are data-driven and do not need manual handling/transformation of data, they fit in the future, lean digital enterprise.

Conclusion:

This can be an ongoing dialogue, diving into detailed topics of a modern PLM approach. I am curious to learn from my readers, how engaged they are in this topic? Do you still take part in PLM dialogues or do you consume? Do you have “tips and tricks” for those who want to shape the future of PLM?


Let your voice be heard! (and give Flip a break)

 

GettyImages-157335388[1]Last week I shared my observation from day 1 of the PI Berlin 2017 conference. If you have not read this review look here: The weekend after PI Berlin 2017.

Day 1 was the most significant day for me. I used the second day more for networking and some selective sessions that I wanted to attend. The advantage for the reader, this post is not as long as the previous one. Some final observations from day 2

PLM: The Foundation for Enterprise Digitalization

Peter Bilello from CIMdata gave an educational speech about digitalization and the impact of digitalization on current businesses. Peter considers digitalization as a logic next step in the PLM evolution process. See picture below.

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Although it is an evolution process, the implementation of this next step requires a revolution. Digitalization will create a disruption in companies as the digital approach will reshape business models, internal business processes, roles and responsibilities. Peter further elaborated on the product innovation platform and its required characteristics. Similar to what I presented on the first day Peter concluded that we are in a learning stage how to build new methodology/infrastructure for PLM. For example, a concept of creating and maintaining a digital twin needs a solid foundation.
His conclusion: Digitalization requires PLM:

Boosting the value of PLM through
Advanced Analytics Assessment

autolivPaul Haesman from Autoliv introduced the challenges they have as a typical automotive company. Digitalization is reshaping the competitive landscape and the demands on more technology, still guaranteeing the highest safety levels of their products. In that context, they invited Tata Technologies to analyze their current PLM implementation and from there to provide feedback about their as-is readiness for the future.

Chris Hind from Tata Technologies presented their methodology where they provide benchmark information, a health check, impact and potential roadmap for PLM. A method that is providing great insights for both parties and I encourage companies that haven´t done such an assessment to investigate in such an activity. The major value of a PLM assessment is that it provides an agreed baseline for the company that allows management to connect the Why to the What and How. Often PLM implementations focus on What and How with not a real alignment to the Why, which results in unrealistic expectations or budgets due to the perceived value.

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An interesting point address by Chris (see picture above) is that Document Management is considered as a trending priority !!!

It illustrates that digitalization in PLM has not taken off yet and companies still focusing on previous century capabilities 😦

The second highlight rating Manufacturing Process Management as the most immature PLM pillar can be considered in the same context. PLM systems are still considered engineering systems and manufacturing process management is in the gray area between PLM systems and ERP systems.

The last two bullets are clear. The roots of PLM are in managing quality and compliance and improving time to market.

Overcoming integration challenges –
Outotec´s Digital Journey

Outotec_RGBHelena Gutiérrez and Sami Grönstand explained in an entertaining manner the Outotec (providing technologies and services for the metal and mineral processing industries) company and their digital journey. Outotec has been working already for several years on simplifying their IT-landscape meanwhile trying to standardize in a modern, data-driven manner the flow of information.

Sami provided with great detail how the plant process definition is managed in PLM. The process definition is driven by the customer´s needs and largely defines the costs of a plant to build. Crucial for the quotation phase but also important if you want to create a digital continuity. Next, the process definition is further detailed with detailed steps, defining the key parameters characteristics of the main equipment.

ElephantAndAnts

And then the challenge starts. In the context of the plant structure, the right equipment needs to be selected. Here it is where plant meets product or as the Outotec team said where the elephant and ants do the tango.

In the end, as much as possible standardized products need to match the customer specific solution. The dream of most of these companies: combining Engineering To Order and Configure To Order and remember this in the context of digital continuity.

So far, a typical EPC (Engineering Procurement Construction) project, however, Outotec wants to extend the digital continuity to support also their customer´s installed plant. I remembered one of their quotes for the past: “Buy one (plant) and get two (a real one and a virtual one). “This concept managed in a digital continuity is something that will come up in many other industries – the digital twin.

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Where companies like Outotec are learning to connect all data from the initiation of their customer specific solution through delivery and services, other product manufacturing companies are researching the same digital continuity for their product offerings to the field of consumers. Thanks to digitization these concepts become more and more similar. I wrote about this topic recently in my post PLM for Owner/Operators.

Final conclusion from PI Berlin 2017

It is evident participants and speakers are talking about the strategic value and role PLM can have an organization.

With digitalization, new possibilities arise where the need and value for end-to-end connectivity pop up in every industry.

We, the PLM community, are all learning and building new concepts. Keep sharing and meeting each other in blogs, forums, and conferences.

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