You are currently browsing the tag archive for the ‘Digital PLM’ tag.

After two reposts, I have finally the ability to write with full speed, and my fingers were aching, having read some postings in the past four weeks.  It started with Verdi Ogewell’ s article on Engineering.com Telecom Giant Ericsson Halts Its PLM Project with Dassault’s 3DEXPERIENCE followed by an Aras blog post Don’t Be a Dinosaur from Mark Reisig, and of course, I would say Oleg Shilovitsky’s post: What to learn from Ericsson PLM failure?

Setting the scene

Verdi’s article is quite tendentious based on outside observations and insinuations. I let you guess who sponsored this article.  If I had to write an article about this situation,

I would state: Ericsson and Dassault failed to migrate the old legacy landscape into a new environment – an end-to-end migration appeared to be impossible.

The other topics mentioned are not relevant to the current situation.

Mark is chiming in on Verdi’s truth and non-relevant points to data migration, suggesting PLM is chosen over dinner. Of course, decisions are not that simple. It is not clear from Mark’s statement, who are the Dinosaurs:

Finally, don’t bet your future on a buzzword. Before making a huge PLM investment, take the time to make sure your PLM vendor has an actual platform. Have them show you their spider chart.  And here’s the hard reality: they won’t do it, because they can’t.

Don’t be a dinosaur—be prepared for the unexpected with a truly resilient digital platform.

I would state, “Don’t bet your future on a spider chart” if you do not know what the real problem is.

 

Oleg’s post finally is more holistic, acknowledging that a full migration might not be the right target, and I like his conclusion:

Flexibility Vs. Out of the box products – which one do you prefer? Over-customize a new PLM to follow old processes? To use a new system as an opportunity to clean existing processes? To move 25,000 people from one database to another is not a simple job. It is time to think about no upgrade PLM systems. While a cloud environment is not an option for mega-size OEMs like Ericsson, there is an opportunity for OEM IT together with the PLM vendor to run a migration path. The last one is a costly step. But… without this step, the current database oriented single-version of truth PLM paradigm is doomed.

The Migration Problem

I believe migration of data – and sometimes the impossibility of data migration – is the biggest elephant in the room when dealing with PLM projects. In 2015 during the PI PLM conference in Dusseldorf, I addressed this topic for the first time: The Challenge of PLM Upgrades.
You can find the presentation on SlideShare here.

I shared a similar example to the Ericsson case from almost 10 years ago. At that time, one of the companies I was working with wanted to replace their mainframe application, which was managing the configuration of certain airplanes. The application managed the aircraft configuration structures in tables and where needed pointing to specifications in a document repository. The two systems were not connected; integrity was guaranteed through manual verification procedures.

The application was considered as the single version of the truth, and has been treated like that for decades. The reason for migration was that all the knowledge of the application disappeared, tables were documented, but the logic was not. And besides this issue, the maintenance costs for the mainframe was also high – also at that time vendor lock-in existed.

The idea was to implement SmarTeam – flexible data model – rapid deployment based on windows technology  -to catch two birds with one stone, i.e., latest microsoft technology and meanwhile direct link to the controlled documents. As they were using CATIA V5, the SmarTeam-integration was a huge potential benefit. For the migration of data, the estimate was two months. What could go wrong?

Well, technically, almost nothing went wrong. The challenge was to map the relational tables to the objects in the SmarTeam data model. And as the relational tables contained a mix of document and item attributes, splitting these tables was not always easy. Sometimes the same properties were with different values in the original table – which one was the truth? The migration took almost two years also due to limited availability of the last knowledgeable resource who could explain the logic.

After the conversion, the question still remained if the migrated data was accurate? Perhaps 99 %?
But what if it was critical? For this company, it was significant, but not mission critical like in Ericsson, where a lot of automation and rules are linked together between loads of systems.

So my point: Dassault has failed at Ericsson and so will Siemens or Aras or any other PLM vendor as the migration issue is not in the technology – we should stop thinking about this kind of migrations.

Who are the dinosaurs?

Mark is in a way suggesting that when you use PLM software from the “old” PLM vendors, you are a dinosaur. Of course, this is a great marketing message, but the truth is that it is not the PLM vendor to blame. Yes, some have more friction than the other in some instances, but in my opinion, there is no ultimate single PLM vendor.

Have a look at the well-known Daimler case from some years ago, which made the news because Daimler decided to replace CATIA by NX. Not because NX was superior – it was about maintaining the PLM backbone Smaragd which would be hard to replace. Even in 2010, there was already the notion that the existing data management infrastructure is hard to replace. See a more neutral article about this topic from Monica Schnitger if you want: Update: Daimler chooses NX for Smaragd.  Also here in the end, it became a complete Siemens account for compatibility reasons.

When you look at the significant wins Aras is mentioning in their customer base, GM, Schaeffler or Airbus, you will probably discover Aras is more the connection layer between legacy systems, old PLM or PDM systems. They are not the new PLM replacing old PLM.  A connection layer creates a digital thread, connecting various data sources for traceability but does not provide digital continuity as the data in the legacy systems is untouched. Still it is an intermediate step towards a hybrid environment.

For me the real dinosaurs are these large enterprises that have been implementing their proprietary PLM environments in the previous century and have built a fully automated infrastructure based on custom data models with a lot of proprietary rules. This was the case in Ericsson, but most traditional automotive and aerospace companies share this problem, as they were the early PLM adopters. And they are not the only ones. Many industrial manufacturing companies suffer from the past, opposite to their Asian competitors who can start with less legacy.

What’s next?

It would be great if the PLM community focused more on the current incompatibility of data between current/past concepts and future digital needs and discuss solution paths (for sure standards will pop-up)

Incompatibility means: Do not talk about migration but probably focus on a hybrid landscape with legacy data, managed in a coordinated manner, and modern, growing digital PLM processes based on a connected approach.

This is the discussion I would like to see, instead of vendors claiming that their technology is the best. None of the vendors will talk about this topic – like the old “Rip-and-Replace” approach is what brings the most software revenue combined with the simplification that there is only OnePLM. It is interesting to see how many companies have a kind of OnePLM or OneXXX statement.

The challenge, of course, is to implement a hybrid approach. To have the two different PLM-concepts work together, there is a need to create a reliable overlap. The reliable overlap can come from an enterprise data governance approach if possible based on a normalized PLM data model. So far all PLM vendors that I know have proprietary data models, only ShareAspace from Eurostep is based on the PLCS standard, but their solutions are most of the time part of a larger PLM-infrastructure (the future !)

To conclude: I look forward to discussing this topic with other PLM peers that are really in the field, discovering and understanding the chasm between the past and the future. Contact me directly or join us as the PLM Roadmap and PDT Europe 13-14 November in Paris. Let’s remain fact-based!
(as a matter of fact you can still contribute – call for papers still open)

 

 

 

Image: waitbutwhy.com

Two weeks ago I wrote about the simplification discussion around PLM – Why PLM never will be simple.  There I focused on the fact that even sharing information in a consistent, future proof way of working, is already challenging, despite easy to use communication tools like email or social communities.

I mentioned that sharing PLM data is even more challenging due to their potential revision, version, status, and context.  This brings us to the topic of configuration management, needed to manage the consistency of information, a challenge with the increasingly sophisticated products or systems. Simple tools will never fix this complexity.

To manage the consistency of a product,  configuration management (CM) is required. Two weeks ago I read the following interesting post from CMstat: A Brief History of Configuration Management Software.

An excellent introduction if you want to know more about the roots of CM, be it that the post at the end starts to flush out all the disadvantages and reasons why you should not think about CM using PLM systems.

The following part amused me:

 The Reality of Enterprise PLM

It is no secret that PLM solutions were often sold based in good part on their promise to provide full-lifecycle change control and systems-level configuration management across all functions of the enterprise for the OEM as well as their supply and service chain partners. The appeal of this sales stick was financial; the cost and liability to the corporation from product failures or disasters due to a lack of effective change control was already a chief concern of the executive suite. The sales carrot was the imaginary ROI projected once full-lifecycle, system-level configuration control was in effect for the OEM and supply chain.

Less widely known is that for many PLM deployments, millions of budget dollars and months of calendar time were exhausted before reaching the point in the deployment road map where CM could be implemented. It was not uncommon that before the CM stage gate was reached in the schedule, customer requirements, budget allocations, management priorities, or executive sponsors would change. Or if not these disruptions within the customer’s organization, then the PLM solution provider, their software products or system integrators had been changed, acquired, merged, replaced, or obsoleted. Worse yet for users who just had a job to do was when solutions were “reimagined” halfway through a deployment with the promise (or threat) of “transforming” their workflow processes.

Many project managers were silently thankful for all this as it avoided anyone being blamed for enterprise PLM deployment failures that were over budget, over schedule, overweight, and woefully underwhelming. Regrettably, users once again had to settle for basic change control instead of comprehensive configuration management.

I believe the CMstat-writer is generalizing too much and preaches for their parish. Although my focus lies on PLM, I also learned the importance of CM and for that reason I will share a view on CM from the PLM side:

Configuration Management is not a target for every company

The origins of Configuration Management come from the Aerospace and Defense (A&D) industries. These industries have high quality, reliability and traceability constraints. In simple words, you need to prove your product works correctly specified in all described circumstances and keep this consistent along the lifecycle of the product.

Moreover, imagine you delivered the perfect product, next implementing changes require a full understanding of the impact of the change. What is the impact of the change on the behavior or performance? In A&D is the question is it still safe and reliable?

Somehow PLM and CM are enemies. The main reason why PLM-systems are used is Time to Market — bringing a product as fast as possible to the market with acceptable quality. Being first is sometimes more important than high quality. CM is considered as a process that slows down Time to Market as managing consistency, and continuous validating takes time and effort.

Configuration Management in Aviation is crucial as everyone understands that you cannot afford to discover a severe problem during a flight. All the required verification and validation efforts make CM a costly process along the product lifecycle. Airplane parts are 2 – 3 times more expensive than potential the same parts used in other industries. The main reason: airplane parts are tested and validated for all expected conditions along their lifecycle.  Other industries do not spend so much time on validation. They validate only where issues can hurt the company, either for liability or for costs.

Time to Market even impacts the aviation industry  as we can see from the commercial aircraft battle(s) between Boeing and Airbus. Who delivers the best airplane (size/performance) at the right moment in the global economy? The Airbus 380 seemed to miss its targets in the future – too big – not flexible enough. The Boeing 737 MAX appears to target a market sweet spot (fuel economy) however the recent tragic accidents with this plane seemed to be caused by Time to Market pressure to certify the aircraft too early. Or is the complexity of a modern airplane unmanageable?

CM based on PLM-systems

Most companies had their configuration management practices long before they started to implement PLM. These practices were most of the time documented in procedures, leading to all kind of coding systems for these documents. Drawing numbers (the specification of a part/product), Specifications, Parts Lists, all had a meaningful identifier combined with a version/revision and status. For example, the Philips 12NC coding system is famous in the Netherlands and is still used among spin-offs of Philips and their supplier as it offers a consistent framework to manage configurations.

Storing these documents into a PDM/PLM-system to provide centralized access was not a big problem; however, companies also expected the PLM-system to support automation and functionality to support their configuration management procedures.

A challenge for many implementers for several reasons:

  • PLM-systems do not offer a standard way of working – if they would do so, they could only serve a small niche market – so it needs to be “configured/customized.”
  • Company configuration management rules sometimes cannot be mapped to the provided PLM data-model and their internal business logic. This has led to costly customizations where, in the best case, implementer and company agreed somewhere in the middle. Worst case as the writer from the CM blog is mentioning it becomes an expensive, painful project
  • Companies do not have a consistent configuration management framework as Time to Market is leading – we will fix CM later is the idea, and they let their PLM –implementer configure the PLM-system as good a possible. Still, at the management level, the value of CM is not recognized.
    (see also: PLM-CM-ALM – not sexy ?)

In companies that I worked with, those who were interested in a standardized configuration management approach were trained in CMII. CMII (or CM2) is a framework supported by most PLM-systems, sometimes even as a pre-configured template to speed-up the implementation. Still, as PLM-systems serve multiple industries, I would not expect any generic PLM-vendor to offer Commercial Off-The-Shelf (COTS) CM-capabilities – there are too many legacy approaches. You can find a good and more in-depth article related to CMII here: Towards Integrated Configuration Change Management (CMII) from Lionel Grealou.

 

What’s next?

Current configuration management practices are very much based on the concepts of managing document. However, products are more and more described in a data-driven, model-based approach. You can find all the reasons why we are moving to a model-based approach in my last year’s blog post. Important to realize is that current CM practices in PLM were designed with mechanical products and lifecycles as a base. With the combination of hardware and software, integrated and with different lifecycles, CM has to be reconsidered with a new holistic concept. The Institute of Process Excellence provides CM2 training but is also active in developing concepts for the digital enterprise.

Martijn Dullaart, Lead Architect Configuration Management @ ASML & Chair @ IPE/CM2 Global Congress has published several posts related to CM and a Model-Based approach – you find them here related to his LinkedIn profile. As you can read from his articles organizations are trying to find a new consistent approach.

Perhaps CM as a service to a Product Innovation Platform, as the CMstat blog post suggests? (quote from the post below)

In Part 2 of this CMsights series on the future of CM software we will examine the emerging strategy of “Platform PLM” where functional services like CM are delivered via an open, federated architecture comprised of rapidly-deployable industry-configured applications.

I am looking forward to Part2 of CMsights . An approach that makes sense to me as system boundaries will disappear in a digital enterprise. It will be more critical in the future to create consistent data flows in the right context and based on data with the right quality.

Conclusion

Simple tools and complexity need to be addressed in the right order. Aligning people and processes efficiently to support a profitable enterprise remains the primary challenge for every enterprise. Complex products, more dependent on software than hardware, are requiring new ways of working to stay competitive. Digitization can help to implement these new ways of working. Experienced PLM/CM experts know the document-driven past. Now it is time for a new generation of PLM and CM experts to start from a digital concept and build consistent and workable frameworks. Then the simple tools can follow.

 

In this post, I will explain the story behind my presentation at PI PLMx London. You can read my review of the event here: “The weekend after ……” and you can find my slides on SlideShare: HERE.

For me, this presentation is a conclusion of a thought process and collection of built-up experiences in the past three to  five years, related to the challenges digital transformation is creating for PLM and what makes it hard to go through compared to other enterprise business domains.  So here we go:

Digital transformation or disruption?

Slide 2 (top image) until 5 are dealing with the common challenges of business transformation. In nature, the transformation from a Caterpillar (old linear business) to a Butterfly (modern, agile, flexible) has the cocoon stage, where the transformation happens. In business unfortunate companies cannot afford a cocoon phase, it needs to be a parallel change.

Human beings are not good at change (slide 3 & 4), and the risk is that a new technology or a new business model will disrupt your business if you are too confident – see examples from the past. The disruption theory introduced by Clayton Christensen in his book, the Innovators Dilemma is an excellent example of how this can happen.  Some of my thoughts are in The Innovator’s dilemma and generation change (2015)

Although I know some PLM vendors consider themselves as disruptor, I give them no chance in the PLM domain. The main reason: The existing PLM systems are so closely tied to the data they manage, that switching from one PLM system to a more modern PLM system does not pay off.  The data models are so diverse that it is better to stay with the existing environment.

What is clear for modern digital businesses is that if you could start from scratch or with almost no legacy you can move faster forward than the rest. But only if supported by a strong leadership , a(understandable) vision and relentless execution.

The impression of evolution

Marc Halpern’s slide presented at PDT 2015 is one of my favorite slides, as it maps business maturity to various characteristics of an organization, including the technologies used.

 

Slide 7 till 18 are zooming in on the terms Coordinated and Connected and the implications it has for data, people and business. I have written about Coordinated and Connected recently: Coordinated or Connected (2018)

A coordinated approach: Delivering the right information at the right moment in the proper context is what current PLM implementations try to achieve. Allowing people to use their own tools/systems as long as they deliver at the right moment their information (documents/files) as part of the lifecycle/delivery process. Very linear and not too complicated to implement you would expect. However it is difficult ! Here we already see the challenge of just aligning a company to implement a horizontal flow of data. Usability of the PLM backbone and optimized silo thinking are the main inhibitors.

In a connected approach: Providing actual information for anyone connected in any context the slide on the left shows the mental picture we need to have for a digital enterprise. Information coming from various platforms needs to be shareable and connected in real-time, leading, in particular for PLM, to a switch from document-based deliverables to models and parameters that are connected.

Slide 15 has examples of some models.  A data-driven approach creates different responsibilities as it is not about ownership anymore but about accountability.

The image above gives my PLM-twisted vision of which are the five core platforms for an enterprise.  The number FIVE is interesting as David Sherburne just published his Five Platforms that Enable Digital Transformation and in 2016 Gartner identified Five domains for the digital platform .- more IT-twisted ? But remember the purpose of digital transformation is: FIVE!

From Coordinated to Connected is Digital Transformation

Slide 19 till 27 further elaborate on the fact that for PLM there is no evolutionary approach possible, going from a Coordinated technology towards a Connected technology.

For three reasons:  different type of data (document vs. database elements), different people (working in a connected environment requires modern digital skills) and different processes (the standard methods for mechanical-oriented PLM practices do not match processes needed to deliver systems (hardware & software) with an incremental delivery process).

Due to the incompatibility of the data, more and more companies discover that a single PLM-instance cannot support both modes – staying with your existing document-oriented PLM-system does not give the capabilities needed for a model-driven approach. Migrating the data from a traditional PLM-environment towards a modern data-driven environment does not bring any value. The majority of the coordinated data is not complete and with the right quality to use a data-driven environment. Note: in  a data-driven environment you do not have people interpreting the data – the data should be correct for automation / algorithms.

The overlay approach, mentioned several times in various PLM-blogs, is an intermediate solution. It provides traceability and visibility between different data sources (PLM, ALM, ERP, SCM, …). However it does not make the information in these systems better accessible.

So the ultimate conclusion is: You need both approaches, and you need to learn to work in a hybrid environment !

What can various stakeholders do?

For the management of your company, it is crucial they understand the full impact of digital transformation. It is not about a sexy customer website, a service platform or Virtual Reality/Augmented Reality case for the shop floor or services. When these capabilities are created disconnected from the source (PLM), they will deliver inconsistencies in the long-term. The new digital baby becomes another silo in the organization. Real digital transformation comes from an end-to-end vision and implementation.  The result of this end-to-end vision will be the understanding that there is a duality in data, in particular for the PLM domain.

Besides the technicalities, when going through a digital transformation, it is crucial for the management to share their vision in a way it becomes a motivational story, a myth, for all employees. As Yuval Harari, writer of the book Sapiens,  suggested, we (Home Sapiens) need an abstract story, a myth to align a larger group of people to achieve a common abstract goal. I discussed this topic in my posts: PLM as a myth? (2017)  and PLM – measurable or a myth?

Finally, the beauty of new digital businesses is that they are connected and can be monitored in real-time. That implies you can check the results continuously and adjust – scale of fail!

Consultants and strategists in a company should also take the responsibility, to educate the management and when advising on less transformational steps, like efficiency improvements: Make sure you learn and understand model-based approaches and push for data governance initiatives. This will at least narrow the gap between coordinated and connected environments.

This was about strategy – now about execution:

For PLM vendors and implementers, understanding the incompatibility of data between current PLM practices – coordinated and connected – it will lead to different business models. Where traditionally the new PLM vendor started first with a rip-and-replace of the earlier environment – no added value – now it is about starting a new parallel environment.  This implies no more big replacement deals, but more a long-term. strategic and parallel journey.  For PLM vendors it is crucial that being able to offer to these modes in parallel will allow them to keep up their customer base and grow. If they would choose for coordinated or connected only it is for sure a competitor will work in parallel.

For PLM users, an organization should understand that they are the most valuable resources, realizing these people cannot make a drastic change in their behavior. People will adapt within their capabilities but do not expect a person who grew up in the traditional ways of working (linear / analogue) to become a successful worker in the new mode (agile / digital). Their value lies in transferring their skills and coaching new employees but do not let them work in two modes. And when it comes to education: permanent education is crucial and should be scheduled – it is not about one or two trainings per year – if the perfect training would exist, why do students go to school for several years ? Why not give them the perfect PowerPoint twice a year?

Conclusions

I believe after three years of blogging about this theme I have made my point. Let’s observe and learn from what is happening in the field – I remain curious and focused about proof points and new insights. This year I hope to share with you new ideas related to digital practices in all industries, of course all associated with the human side of what we once started to call PLM.

Note: Oleg Shilovitsky just published an interesting post this weekend: Why complexity is killing PLM and what are future trajectories and opportunities? Enough food for discussion. One point: The fact that consumers want simplicity does not mean PLM will become simple – working in the context of other information is the challenge – it is human behavior – team players are good in anticipating – big egos are not. To be continued…….

 

 

 

 

 

 

 

 

 

I was happy to take part at the PI PLMx London event last week. It was here and in the same hotel that this conference saw the light in 2011  – you can see my blog post from that event here: PLM and Innovation @ PLMINNOVATION 2011.

At that time the first vendor-independent PLM conference after a long time and it brought a lot of new people together to discuss their experience with PLM. Looking at the audience that time, many of the companies that were there, came back during the years, confirming the value this conference has brought to their PLM journey.

Similar to the PDT conference(s) – just announced for this year last week – here – the number of participants is diminishing.

Main hypotheses:

  1. the PLM-definition has become too vague. Going to a PLM conference does not guarantee it is your type of PLM discussions you expect to see?
  2. the average person is now much better informed related to PLM thanks to the internet and social media (blogs/webinars/ etc.) Therefore, the value retrieved from the PLM conference is not big enough any more?
  3. Digital Transformation is absorbing all the budget and attention downstream the organization not creating the need and awareness of modern PLM to the attention of the management anymore. g., a digital twin is sexier to discuss than PLM?

What do you think about the above three hypotheses – 1,2 and/or 3?

Back to the conference. The discussion related to PLM has changed over the past nine years. As I presented at PI from the beginning in 2011, here are the nine titles from my sessions:

2011       PLM – The missing link
2012       Making the case for PLM
2013       PLM loves Innovation
2014       PLM is changing
2015       The challenge of PLM upgrades
2016       The PLM identity crisis
2017       Digital Transformation affects PLM
2018       PLM transformation alongside Digitization
2019       The challenges of a connected Ecosystem for PLM

Where the focus started with justifying PLM, as well as a supporting infrastructure, to bring Innovation to the market, the first changes became visible in 2014. PLM was changing as more data-driven vendors appeared with new and modern (metadata) concepts and cloud, creating the discussion about what would be the next upgrade challenge.

The identity crisis reflected the introduction of software development / management combined with traditional (mechanical) PLM – how to deal with systems? Where are the best practices?

Then from 2017 on until now Digital Transformation and the impact on PLM and an organization became the themes to discuss – and we are not ready yet!

Now some of the highlights from the conference. As there were parallel sessions, I had to divide my attention – you can see the full agenda here:

How to Build Critical Architecture Models for the New Digital Economy

The conference started with a refreshing presentation from David Sherburne (Carestream) explaining their journey towards a digital economy.  According to David, the main reason behind digitization is to save time, as he quoted Harvey Mackay an American Businessman and Journalist,

Time is free, but it is priceless. You cannot own it, but you can use it. You can’t keep it, but you can spend it. Once you have lost it, you never can get it back

I tend to agree with this simplification as it makes the story easy to explain to everyone in your company. Probably I would add to that story that saving time also means less money spent on intermediate resources in a company, therefore, creating a two-sided competitive advantage.

David stated that today’s digital transformation is more about business change than technology and here I wholeheartedly agree. Once you can master the flow of data in your company, you can change and adapt your company’s business processes to be better connected to the customer and therefore deliver the value they expect (increases your competitive advantage).

Having new technology in place does not help you unless you change the way you work.

David introduced a new acronym ILM (Integrated Lifecycle Management) and I am sure some people will jump on this acronym.

David’s presentation contained an interesting view from the business-architectural point of view. An excellent start for the conference where various dimensions of digital transformation and PLM were explored.

Integrated PLM in the Chemical industry

Another interesting session was from Susanna Mäentausta  (Kemira oy)  with the title: “Increased speed to market, decreased risk of non-compliance through integrated PLM in Chemical industry.” I selected her session as from my past involvement with the process industry, I noticed that PLM adoption is very low in the process industry. Understanding Why and How they implemented PLM was interesting for me. Her PLM vision slide says it all:

There were two points that I liked a lot from her presentation, as I can confirm they are crucial.

  • Although there was a justification for the implementation of PLM, there was no ROI calculation done upfront. I think this is crucial, you know as a company you need to invest in PLM to stay competitive. Making an ROI-story is just consoling the people with artificial number – success and numbers depend on the implementation and Susanna confirmed that step 1 delivered enough value to be confident.
  • There were an end-to-end governance and a communication plan in place. Compared to PLM projects I know, this was done very extensive – full engagement of key users and on-going feedback – communicate, communicate, communicate. How often do we forget this in PLM projects?

Extracting More Value of PLM in an Engineer-to-Order Business

Sami Grönstrand & Helena Gutierrez presented as an experienced duo (they were active in PI P PLMx Hamburg/Berlin before) – their current status and mission for PLM @ Outotec. As the title suggests, it was about how to extract more value from PL M, in an Engineering to Order Business.

What I liked is how they simplified their PLM targets from a complex landscape into three story-lines.

If you jump into all the details where PLM is contributing to your business, it might get too complicated for the audience involved. Therefore, they aligned their work around three value messages:

  • Boosting sales, by focusing on modularization and encouraging the use of a product configurator. This instead of developing every time a customer-specific solution
  • Accelerating project deliverables, again reaping the benefits of modularization, creating libraries and training the workforce in using this new environment (otherwise no use of new capabilities). The results in reducing engineering hours was quite significant.
  • Creating New Business Models, by connecting all data using a joint plant structure with related equipment. By linking these data elements, an end-to-end digital continuity was established to support advanced service and support business models.

My conclusion from this session was again that if you want to motivate people on a PLM-journey it is not about the technical details, it is about the business benefits that drive these new ways of working.

Managing Product Variation in a Configure-To-Order Business

In the context of the previous session from Outotec, Björn Wilhemsson’s session was also addressing somehow the same topic of How to create as much as possible variation in your customer offering, while internally keep the number of variants and parts manageable.

Björn, Alfa Laval’s OnePLM Programme Director, explained in detail the strategy they implemented to address these challenges. His presentation was very educational and could serve as a lesson for many of us related to product portfolio management and modularization.

Björn explained in detail the six measures to control variation, starting from a model-strategy / roadmap (thinking first) followed by building a modularized product architecture, controlling and limiting the number of variants during your New Product Development process. Next as Alfa Laval is in a Configure-To-Order business, Björn the implementation of order-based and automated addition of pre-approved variants (not every variant needs to exist in detail before selling it), followed by the controlled introduction of additional variants and continuous analysis of quoted and sold variant (the power of a digital portfolio) as his summary slides shows below:

Day 1 closed with an inspirational keynote; Lessons-Learnt from the Mountaineering Experience 8848 Meter above sea level  – a mission to climb the highest mountain on each of the continents in 107 days – 9 hours – setting a new world record by Jonathan Gupta.

There are some analogies to discover between his mission and a PLM implementation. It is all about having the total picture in mind. Plan and plan, prepare step-by-step in detail and rely on teamwork – it is not a solo journey – and it is about reaching a top (deliverable phase) in the most efficient way.

The differences: PLM does not need world records, you need to go with the pace an organization can digest and understand. Although the initial PLM climate during implementation might be chilling too, I do not believe you have to suffer temperatures below 50 degrees Celsius.

During the morning, I was involved in several meetings, therefore unfortunate unable to see some of the interesting sessions at that time. Hopefully later available on PI.TV for review as slides-only do not tell the full story. Although there are experts that can conclude and comment after seeing a single slide. You can read it here from my blog buddy Oleg Shilovitsky’s post : PLM Buzzword Detox. I think oversimplification is exactly creating the current problem we have in this world – people without knowledge become louder and sure about their opinion compared to knowledgeable people who have spent time to understand the matter.

Have a look at the Dunning-Kruger effect here (if you take the time to understand).

 

PLM: Enabling the Future of a Smart and Connected Ecosystem

Peter Bilello from CIMdata shared his observations and guidance related to the current ongoing digital business revolution that is taking place thanks to internet and IoT technologies. It will fundamentally transform how people will work and interact between themselves and with machines. Survival in business will depend on how companies create Smart and Connected Ecosystems. Peter showed a slide from the 2015 World Economic Forum (below) which is still relevant:

Probably depending on your business some of these waves might have touched your organization already. What is clear that the market leaders here will benefit the most – the ones owning a smart and connected ecosystem will be the winners shortly.

Next, Peter explained why PLM, and in particular the Product Innovation Platform, is crucial for a smart and connected enterprise.  Shiny capabilities like a digital twin, the link between virtual and real, or virtual & augmented reality can only be achieved affordably and competitively if you invest in making the source digital connected. The scope of a product innovation platform is much broader than traditional PLM. Also, the way information is stored differs – moving from documents (files) towards data (elements in a database).  I fully agree with Peter’s opinion here that PLM is conceptually the Killer App for a Smart & Connected Ecosystem and this notion is spreading.

A recent article from Forbes in the category Leadership: Is Your Company Ready For Digital Product Life Cycle Management? shows there is awareness.  Still very basic and people are still confused to understand what is the difference with an electronic file (digital too ?) and a digital definition of information.

The main point to remember here: Digital information can be accessed directly through a programming interface (API/Service) without the need to open a container (document) and search for this piece of information.

Peter then zoomed in on some topics that companies need to investigate to reach a smart & connected ecosystem. Security (still a question hardly addressed in IoT/Digital Twin demos), Standards and Interoperability ( you cannot connect in all proprietary formats economically and sustainably) A lot of points to consider and I want to close with Peter’s slide illustrating where most companies are in reality

The Challenges of a Connected Ecosystem for PLM

I was happy to present after Peter Bilello and David Sherburne (on day 1) as they both gave a perspective on digital transformation complementary to what I submitted. My presentation was focusing on the incompatibility of current coordinated business systems and the concept of a connected ecosystem.

You can already download my slides from SlideShare here: The Challenges of a Connected Ecosystem for PLM . I will explain my presentation in an upcoming blog post as slides without a story might lead to the wrong interpretation, and we already reached 2000 words. Few words to come.

How to Run a PLM Project Using the Agile Manifesto

Andrew Lodge, head of Engineering Systems at JCB explained how applying the agile mindset towards a PLM project can lead to faster and accurate results needed by the business. I am a full supporter for this approach as having worked in long and waterfall-type of PLM implementations there was always the big crash and user dissatisfaction at the final delivery. Keeping the business involved every step seems to be the solution. The issue I discovered here is that agile implementation requires a lot of people, in particular, business, to be involved heavily. Some companies do not understand this need and dropped /reduced business contribution to the least, killing the value of an agile approach

 

Concluding

For me coming back to London for the PI PLMx event was very motivational. Where the past two, three conferences before in Germany might have led to little progress per year, this year, thanks to new attendees and inspiration, it became for me a vivid event, hopefully growing shortly. Networking and listening to your peers in business remains crucial to digest it all.

 

According to LinkedIn, there are over a 7500 PLM consultants in my network.  It is quite an elite group of people as I have over 100.000 CEOs in my network according to LinkedIn. Being a CEO is a commodity.

PLM consultants share a common definition, the words Product Lifecycle Management. However, what we all mean by PLM is one of the topics that has evolved over the past 19 years in a significant way.

PLM or cPDM (collaborative PDM)?

In the early days, PLM was considered as an engineering tool for collaboration, either between global subsidiaries or suppliers. The main focus of PLM was to bring engineering information to manufacturing in a controlled way. PLM and cPDM, often seen as solving the same business needs as the implementation of a PLM system most of the time got stuck at the cPDM level.

Main players at that time were Dassault Systemes, UGS (later Siemens PLM) and PTC – their solutions were MCAD-driven with limited scope – bringing engineering information towards manufacturing in a coordinated way.

PLM was not really an approach that created visibility at the management level of a company. How do you value and measure collaboration? Because connectivity was expensive in the early days of PLM, combined with the idea that PLM systems needed to be customized, PLM was framed as costly and hard to deliver value.

Systems Engineering and New Product Introduction

Then, 2005 and beyond, thanks to better connectivity and newcomers in the PLM market, the solution landscape from PLM became broader.  CAD integrations were not a necessary part of the PLM scope according to these newcomers as they focused on governance (New Product Introduction), Bill of Materials or at the front-end of the product design cycle, connecting systems engineering by adding requirements management to their PLM suite.

New players in this domain where SAP, Aras, followed by Autodesk – their focus was more metadata-driven, connection and creating an end-to-end data flow for the product. Autodesk started the PLM and cloud path.

These new capabilities brought a broader scope for PLM indeed. However, they also strengthened the idea that PLM is there for engineers. For the management too complicated, unless they understood the value of coordinated collaboration. Large enterprises saw the benefits of having common processes for PLM as an essential reason to invest in PLM. The graph below showed the potential of PLM, where the shaded area indicates the potential revenue benefits.

Still, this graph does not create “hard numbers,” and it requires visionaries to get a PLM implementation explained and justified across the board.  PLM is framed as expensive even if the budgets spent on PLM are twenty percent or less compared to ERP implementations. As PLM is not about transactional data, the effects of PLM are hard to benchmark. Success has many fathers, and in case of difficulties, the newcomer is to blame.

PLM = IoT?

With the future possibilities, connectivity to the machine-level (IoT or IIoT), a new paradigm related to PLM was created by PTC.  PLM equals IoT – read more here.

Through IoT, it became possible to connect to products/assets in the field, and the simplified message from PTC was that now thanks to IoT (read ThingWorx) PLM was now really possible, releasing traditional PLM out of its engineering boundaries. The connected sensors created the possibility to build and implement more advanced and flexible manufacturing processes, often called Smart Manufacturing or Industrie 4.0.

None of the traditional PLM vendors is talking about PLM solely anymore. Digital transformation is a topic discussed at the board level, where GE played a visionary role with their strong message for change, driven by their CEO Jeff Immelt at that time – have a look at one of his energizing talks here.

However is PLM part of this discussion?

Digital Transformation opened a new world for everyone. Existing product lifecycle concepts could be changed, products are becoming systems, interacting with the environment realized through software features. Systems can be updated/upgraded relatively fast, in particular when you are able to watch and analyze the performance of your assets in almost real-time.

All consultants (me included) like to talk about digital transformation as it creates a positive mood towards the future, imagining everything that is possible. And with the elite of PLM consultants we are discovering the new roles of PLM – see picture below:

Is PLM equal to IoT or Digital Transformation?

I firmly believe the whole Digital Transformation and IoT hypes are unfortunately obfuscating the maximum needs for a digital enterprise. The IoT focus only exposes the last part of the lifecycle, disconnected from the concept and engineering cycles – yes on PowerPoint slides there might be a link. Re-framing PLM as Digital Transformation makes is even vaguer as we discussed during the CIMdata / PDT Europe conference last October. My main argument: Companies fail to have a link with their digital operations and dreams because current engineering processes and data, hardware (mechanical and electronics) combined with software are still operating in an analog, document-driven mode.

PLM = MBSE?

However what we also discussed during this conference was the fact that actually there is a need for an end-to-end model-based systems engineering infrastructure to support the full product lifecycle. Don Farr’s (Boeing) new way to depict the classical systems engineering “V” also hinted into that direction. See the image below – a connected environment between the virtual modeled word and the physical world at any time of the product lifecycle

So could MBSE be the new naming for PLM?

The problem is as Peter Bilello also mentioned during the CIMdata/PDT conference is that the word “ENGINEERING” is in Model-Based Systems Engineering. Therefore keeping the work what the PLM “elite” is doing again in the engineering box.

So perhaps Model-Based Enterprise as the new name?

Unfortunate MBE has already two current definitions – look here and here. Already too much confusion, and there a lot of people who like confusion. See Model-Based – The confusion. So any abbreviation with Model-Based terminology in it will not get attention at the board level. Even if it is crucial the words, Model-Based create less excitement as compared to Digital Twin, although the Digital Twin depends on a model-based approach.

Conclusion

Creating and maintaining unique products and experiences for their customers is the primary target of almost every company. However, no easy acronym that frames these aspects to value at the board level. Perhaps PID – the Product Innovation Diamond approach will be noticed? Your say ….

 

Last week I attended the long-awaited joined conference from CIMdata and Eurostep in Stuttgart. As I mentioned in earlier blog posts. I like this conference because it is a relatively small conference with a focused audience related to a chosen theme.

Instead of parallel sessions, all attendees follow the same tracks and after two days there is a common understanding for all. This time there were about 70 people discussing the themes:  Digitalizing Reality—PLM’s role in enabling the digital revolution (CIMdata) and Collaboration in the Engineering and Manufacturing Supply Chain –the Extended Digital Thread and Smart Manufacturing (EuroStep)

As you can see all about Digital. Here are my comments:

The State of the PLM Industry:
The Digital Revolution

Peter Bilello kicked off with providing an overview of the PLM industry. The PLM market showed an overall growth of 7.3 % toward 43.6 Billion dollars. Zooming in into the details cPDM grew with 2.9 %. The significant growth came from the PLM tools (7.7 %). The Digital Manufacturing sector grew at 6.2 %. These numbers show to my opinion that in particular, managing collaborating remains the challenging part for PLM. It is easier to buy tools than invest in cPDM.

Peter mentioned that at the board level you cannot sell PLM as this acronym is too much framed as an engineering tool. Also, people at the board have been trained to interpret transactional data and build strategies on that. They might embrace Digital Transformation. However, the Product innovation related domain is hard to define in numbers. What is the value of collaboration? How do you measure and value innovation coming from R&D? Recently we have seen more simplified approaches how to get more value from PLM. I agree with Peter, we need to avoid the PLM-framing and find better consumable value statements.

Nothing to add to Peter’s closing remarks:

 

An Alternative View of the Systems Engineering “V”

For me, the most interesting presentation of Day 1 was Don Farr’s presentation. Don and his Boeing team worked on depicting the Systems Engineering process for a Model-Based environment. The original “V” looks like a linear process and does not reflect the multi-dimensional iterations at various stages, the concept of a virtual twin and the various business domains that need to be supported.

The result was the diamond symbol above. Don and his team have created a consistent story related to the depicted diamond which goes too far for this blog post. Current the diamond concept is copyrighted by Boeing, but I expect we will see more of this in the future as the classical systems engineering “V” was not design for our model-based view of the virtual and physical products to design AND maintain.

 

Sponsor vignette sessions

The vignette sponsors of the conference, Aras, ESI,-group, Granta Design, HCL, Oracle and TCS all got a ten minutes’ slot to introduce themselves, and the topics they believed were relevant for the audience. These slots served as a teaser to come to their booth during a break. Interesting for me was Granta Design who are bringing a complementary data service related to materials along the product lifecycle, providing a digital continuity for material information. See below.

 

The PLM – CLM Axis vital for Digitalization of Product Process

Mikko Jokela, Head of Engineering Applications CoE, from ABB, completed the morning sessions and left me with a lot of questions. Mikko’s mission is to provide the ABB companies with an information infrastructure that is providing end-to-end digital services for the future, based on apps and platform thinking.

Apparently, the digital continuity will be provided by all kind of BOM-structures as you can see below.In my post, Coordinated or Connected, related to a model-based enterprise I call this approach a coordinated approach, which is a current best practice, not an approach for the future. There we want a model-based enterprise instead of a BOM-centric approach to ensure a digital thread. See also Don Farr’s diamond. When I asked Mikko which data standard(s) ABB will use to implement their enterprise data model it became clear there was no concept yet in place. Perhaps an excellent opportunity to look at PLCS for the product related schema.

A general comment: Many companies are thinking about building their own platform. Not all will build their platform from scratch. For those starting from scratch have a look at existing standards for your industry. And to manage the quality of data, you will need to implement Master Data Management, where for the product part the PLM system can play a significant role. See Master Data Management and PLM.

 

Systems of Systems Approach to Product Design

Professor Martin Eigner keynote presentation was about the concepts how new products and markets need a Systems of Systems approach combined with Model-Based Systems Engineering (MBSE) and Product Line Engineering (PLE) where the PLM system can be the backbone to support the MBSE artifacts in context. All these concepts require new ways of working as stated below:

And this is a challenge. A quick survey in the room (and coherent with my observations from the field) is the fact that most companies (95 %) haven’t even achieved to work integrated for mechatronics products. You can imagine the challenge to incorporate also Software, Simulation, and other business disciplines. Martin’s presentations are always an excellent conceptual framework for those who want to dive deeper a start point for discussion and learning.

Additive Manufacturing (Enabled Supply) at Moog

Moog Inc, a manufacturer of precision motion controls for various industries have made a strategic move towards Additive Manufacturing. Peter Kerl, Moog’s Engineering Systems Manager, gave a good introduction what is meant by Additive Manufacturing and how Moog is introducing Additive Manufacturing in their organization to create more value for their customer base and attract new customers in a less commodity domain. As you can image delivering products through Additive Manufacturing requires new skills (Design / Materials), new processes and a new organizational structure. And of course a new PLM infrastructure.

Jim van Oss, Moog’s PLM Architect and Strategist, explained how they have been involved in a technology solution for digital-enabled parts leveraging blockchain technology.  Have a look at their VeriPart trademark. It was interesting to learn from Peter and Jim that they are actively working in a space that according to the Gartner’s hype curve is in the early transform phase.  Peter and Jim’s presentation were very educational for the audience.

For me, it was also interesting to learn from Jim that at Moog they were really practicing the modes for PLM in their company. Two PLM implementations, one with the legacy data and the wrong data for the future and one with the new data model for the future. Both implementations build on the same PLM vendor’s release. A great illustration showing the past and the future data for PLM are not compatible

Value Creation through Synergies between PLM & Digital Transformation

Daniel Dubreuil, Safran’s CDO for Products and Services gave an entertaining lecture related to Safran’s PLM journey and the introduction of new digital capabilities, moving from an inward PLM system towards a digital infrastructure supporting internal (model-based systems engineering / multiple BOMs) and external collaboration with their customers and suppliers introducing new business capabilities. Daniel gave a very precise walk-through with examples from the real world. The concluding slide: KEY SUCCESS FACTORS was a slide that we have seen so many times at PLM events.

Apparently, the key success factors are known. However, most of the time one or more of these points are not possible to address due to various reasons. Then the question is: How to mitigate this risk as there will be issues ahead?

 

Bringing all the digital trends together. What’s next?

The day ended with a virtual Fire Place session between Peter Bilello and Martin Eigner, the audience did not see a fireplace however my augmented twitter feed did it for me:

Some interesting observations from this dialogue:

Peter: “Having studied physics is a good base for understanding PLM as you have to model things you cannot see” – As I studied physics I can agree.

Martin: “Germany is the center of knowledge for Mechanical, the US for Electronics and now China becoming the center for Electronics and Software” Interesting observation illustrating where the innovation will come from.

Both Peter and Martin spent serious time on the importance of multidisciplinary education. We are teaching people in silos, faculties work in silos. We all believe these silos must be broken down. It is hard to learn and experiment skills for the future. Where to start and lead?

Conclusion:

The PLM roadmap had some exciting presentations combined with CIMdata’s PLM update an excellent opportunity to learn and discuss reality. In particular for new methodologies and technologies beyond the hype. I want to thank CIMdata for the superb organization and allowing me to take part. Next week I will follow-up with a review of the PDT Europe conference part (Day 2)

 

 

 

Earth GIF - Find & Share on GIPHY

At this moment we are in the middle of the year. Usually for me a quiet time and a good time to reflect on what has happened so far and to look forward.

Three themes triggered me to write this half-year:

  • The changing roles of (PLM) consultancy
  • The disruptive effect of digital transformation on legacy PLM
  • The Model-driven approaches

A short summary per theme here with links to the original posts for those who haven’t followed the sequence.

The changing roles of (PLM) consultancy

Triggered by Oleg Shilovitsky’s post Why traditional PLM ranking is dead. PLM ranking 2.0 a discussion started related to the changing roles of PLM choice and the roles of a consultant.  Oleg and I agreed that using the word dead in a post title is a way to catch extra attention. And as many people do not read more than the introduction, this is a way to frame ideas (not invented by us, look at your newspaper and social media posts).  Please take your time and read this post till the end.

Oleg and I concluded that the traditional PLM status reports provided by consultancy firms are no longer is relevant. They focus on the big vendors, in a status-quo and most of them are 80 % the same on their core PLM capabilities. The challenge comes in how to select a PLM approach for your company.

Here Oleg and I differ in opinion. I am more looking at PLM from a business transformation point of view, how to improve your business with new ways of working. The role of a consultant is crucial here as the consultant can help to formalize the company’s vision and areas to focus on for PLM. The value of the PLM consultant is to bring experience from other companies instead of inventing new strategies per company. And yes, a consultant should get paid for this added value.

Oleg believes more in the bottom-up approach where new technology will enable users to work differently and empower themselves to improve their business (without calling it PLM). More or less concluding there is no need for a PLM consultant as the users will decide themselves about the value of the selected technology. In the context of Oleg’s position as CEO/Co-founder of OpenBOM, it is a logical statement, fighting for the same budget.

The discussion ended during the PLMx conference in Hamburg, where Oleg and I met with an audience recorded by MarketKey. You can find the recording Panel Discussion: Digital Transformation and the Future of PLM Consulting here.
Unfortunate, like many discussions, no conclusion. My conclusion remains the same – companies need PLM coaching !

The related post to this topic are:

 

The disruptive effect of digital transformation on legacy PLM

A topic that I have discussed the past two years is that current PLM is not compatible with a modern data-driven PLM. Note: data-driven PLM is still “under-development”. Where in most companies the definition of the products is stored in documents / files, I believe that in order to manage the complexity of products, hardware and software in the future, there is a need to organize data related to models not to files. See also: From Item-centric to model-centric ?

For a company it is extremely difficult to have two approaches in parallel as the first reaction is: “let’s convert the old data to the new environment”.

This statement has been proven impossible in most of the engagements I am involved in and here I introduced the bimodal approach as a way to keep the legacy going (mode 1) and scale-up for the new environment (mode 2).

A bimodal approach is sometimes acceptable when the PLM software comes from two different vendors. Sometimes this is also called the overlay approach – the old system remains in place and a new overlay is created to connect the legacy PLM system and potentially other systems like ALM or MBSE environments. For example some of the success stories for Aras complementing Siemens PLM.

Like the bimodal approach the overlay approach creates the illusion that in the near future the old legacy PLM will disappear. I partly share that illusion when you consider the near future a period of 5 – 10+ years depending on the company’s active products. Faster is not realistic.

And related to bimodal, I now prefer to use the terminology used by McKinsey: our insights/toward an integrated technology operating model in the context of PLM.

The challenge is that PLM vendors are reluctant to support a bimodal approach for their own legacy PLM as then suddenly this vendor becomes responsible for all connectivity between mode 1 and mode 2 data – every vendors wants to sell only the latest.

I will elaborate on this topic during the PDT Europe conference in Stuttgart – Oct 25th . No posts on this topic this year (yet) as I am discussing, learning and collecting examples from the field. What kept me relative busy was the next topic:

The Model-driven approaches

Most of my blogging time I spent on explaining the meaning behind a modern model-driven approach and its three main aspects: Model-Based Systems Engineering, Model-Based Definition and Digital Twins. As some of these aspects are still in the hype phase, it was interesting to see the two different opinions are popping up. On one side people claiming the world is still flat (2D), considering model-based approaches just another hype, caused by the vendors. There is apparently no need for digital continuity. If you look into the reactions from certain people, you might come to the conclusion it is impossible to have a dialogue, throwing opinions is not a discussion..

One of the reasons might be that people reacting strongly have never experienced model-based efforts in their life and just chime in or they might have a business reason not to agree to model-based approached as it does not align with their business? It is like the people benefiting from the climate change theory – will the vote against it when facts are known ? Just my thoughts.

There is also another group, to which I am connected, that is quite active in learning and formalizing model-based approaches. This in order to move forward towards a digital enterprise where information is connected and flowing related to various models (behavior models, simulation models, software models, 3D Models, operational models, etc., etc.) . This group of people is discussing standards and how to use and enhance them. They discuss and analyze with arguments and share lessons learned. One of the best upcoming events in that context is the joined CIMdata PLM Road Map EMEA and the PDT Europe 2018 – look at the agenda following the image link and you should get involved too – if you really care.

 

And if you are looking into your agenda for a wider, less geeky type of conference, consider the PI PLMx CHICAGO 2018 conference on Nov 5 and 6. The agenda provides a wider range of sessions, however I am sure you can find the people interested in discussing model-based learnings there too, in particular in this context Stream 2: Supporting the Digital Value Chain

My related posts to model-based this year were:

Conclusion

I spent a lot of time demystifying some of PLM-related themes. The challenge remains, like in the non-PLM world, that it is hard to get educated by blog posts as you might get over-informed by (vendor-related) posts all surfing somewhere on the hype curve. Do not look at the catchy title – investigate and take time to understand HOW things will this work for you or your company. There are enough people explaining WHAT they do, but HOW it fit in a current organization needs to be solved first. Therefore the above three themes.

This is my concluding post related to the various aspects of the model-driven enterprise. We went through Model-Based Systems Engineering (MBSE) where the focus was on using models (functional / logical / physical / simulations) to define complex product (systems). Next we discussed Model Based Definition / Model-Based Enterprise (MBD/MBE), where the focus was on data continuity between engineering and manufacturing by using the 3D Model as a master for design, manufacturing and eventually service information.

And last time we looked at the Digital Twin from its operational side, where the Digital Twin was applied for collecting and tuning physical assets in operation, which is not a typical PLM domain to my opinion.

Now we will focus on two areas where the Digital Twin touches aspects of PLM – the most challenging one and the most over-hyped areas I believe. These two areas are:

  • The Digital Twin used to virtually define and optimize a new product/system or even a system of systems. For example, defining a new production line.
  • The Digital Twin used to be the virtual replica of an asset in operation. For example, a turbine or engine.

Digital Twin to define a new Product/System

There might be some conceptual overlap if you compare the MBSE approach and the Digital Twin concept to define a new product or system to deliver. For me the differentiation would be that MBSE is used to master and define a complex system from the R&D point of view – unknown solution concepts – use hardware or software?  Unknown constraints to be refined and optimized in an iterative manner.

In the Digital Twin concept, it is more about a defining a system that should work in the field. How to combine various systems into a working solution and each of the systems has already a pre-defined set of behavioral / operational parameters, which could be 3D related but also performance related.

You would define and analyze the new solution virtual to discover the ideal solution for performance, costs, feasibility and maintenance. Working in the context of a virtual model might take more time than traditional ways of working, however once the models are in place analyzing the solution and optimizing it takes hours instead of weeks, assuming the virtual model is based on a digital thread, not a sequential process of creating and passing documents/files. Virtual solutions allow a company to optimize the solution upfront instead of costly fixing during delivery, commissioning and maintenance.

Why aren’t we doing this already? It takes more skilled engineers instead of cheaper fixers downstream. The fact that we are used to fixing it later is also an inhibitor for change. Management needs to trust and understand the economic value instead of trying to reduce the number of engineers as they are expensive and hard to plan.

In the construction industry, companies are discovering the power of BIM (Building Information Model) , introduced to enhance the efficiency and productivity of all stakeholders involved. Massive benefits can be achieved if the construction of the building and its future behavior and maintenance can be optimized virtually compared to fixing it in an expensive way in reality when issues pop up.

The same concept applies to process plants or manufacturing plants where you could virtually run the (manufacturing) process. If the design is done with all the behavior defined (hardware-in-the-loop simulation and software-in-the-loop) a solution has been virtually tested and rapidly delivered with no late discoveries and costly fixes.

Of course it requires new ways of working. Working with digital connected models is not what engineering learn during their education time – we have just started this journey. Therefore organizations should explore on a smaller scale how to create a full Digital Twin based on connected data – this is the ultimate base for the next purpose.

Digital Twin to match a product/system in the field

When you are after the topic of a Digital Twin through the materials provided by the various software vendors, you see all kinds of previews what is possible. Augmented Reality, Virtual Reality and more. All these presentations show that clicking somewhere in a 3D Model Space relevant information pops-up. Where does this relevant information come from?

Most of the time information is re-entered in a new environment, sometimes derived from CAD but all the metadata comes from people collecting and validating data. Not the type of work we promote for a modern digital enterprise. These inefficiencies are good for learning and demos but in a final stage a company cannot afford silos where data is collected and entered again disconnected from the source.

The main problem: Legacy PLM information is stored in documents (drawings / excels) and not intended to be shared downstream with full quality.
Read also: Why PLM is the forgotten domain in digital transformation.

If a company has already implemented an end-to-end Digital Twin to deliver the solution as described in the previous section, we can understand the data has been entered somewhere during the design and delivery process and thanks to a digital continuity it is there.

How many companies have done this already? For sure not the companies that are already a long time in business as their current silos and legacy processes do not cater for digital continuity. By appointing a Chief Digital Officer, the journey might start, the biggest risk the Chief Digital Officer will be running another silo in the organization.

So where does PLM support the concept of the Digital Twin operating in the field?

For me, the IoT part of the Digital Twin is not the core of a PLM. Defining the right sensors, controls and software are the first areas where IoT is used to define the measurable/controllable behavior of a Digital Twin. This topic has been discussed in the previous section.

The second part where PLM gets involved is twofold:

  • Processing data from an individual twin
  • Processing data from a collection of similar twins

Processing data from an individual twin

Data collected from an individual twin or collection of twins can be analyzed to extract or discover failure opportunities. An R&D organization is interested in learning what is happening in the field with their products. These analyses lead to better and more competitive solutions.

Predictive maintenance is not necessarily a part of that.  When you know that certain parts will fail between 10.000 and 20.000 operating hours, you want to optimize the moment of providing service to reduce downtime of the process and you do not want to replace parts way too early.


The R&D part related to predictive maintenance could be that R&D develops sensors inside this serviceable part that signal the need for maintenance in a much smaller time from – maintenance needed within 100 hours instead of a bandwidth of 10.000 hours. Or R&D could develop new parts that need less service and guarantee a longer up-time.

For an R&D department the information from an individual Digital Twin might be only relevant if the Physical Twin is complex to repair and downtime for each individual too high. Imagine a jet engine, a turbine in a power plant or similar. Here a Digital Twin will allow service and R&D to prepare maintenance and simulate and optimize the actions for the physical world before.

The five potential platforms of a digital enterprise

The second part where R&D will be interested in, is in the behavior of similar products/systems in the field combined with their environmental conditions. In this way, R&D can discover improvement points for the whole range and give incremental innovation. The challenge for this R&D organization is to find a logical placeholder in their PLM environment to collect commonalities related to the individual modules or components. This is not an ERP or MES domain.

Concepts of a logical product structure are already known in the oil & gas, process or nuclear industry and in 2017 I wrote about PLM for Owners/Operators mentioning Bjorn Fidjeland has always been active in this domain, you can find his concepts at plmPartner here  or as an eLearning course at SharePLM.

To conclude:

  • This post is way too long (sorry)
  • PLM is not dead – it evolves into one of the crucial platforms for the future – The Product Innovation Platform
  • Current BOM-centric approach within PLM is blocking progress to a full digital thread

More to come after the holidays (a European habit) with additional topics related to the digital enterprise

 

A month ago I announced to write a series of posts related to the various facets of Model-Based. As I do not want to write a book for a limited audience, I still believe blog posts are an excellent way to share knowledge and experience to a wider audience. Remember PLM is about sharing!

There are three downsides to this approach:

  • you have to chunk the information into pieces; my aim is not to exceed 1000 words per post
  • Isolated posts can be taken out of context (in a positive or negative way)
  • you do not become rich and famous for selling your book

Model-Based ways of working are a hot topic and crucial for a modern digital enterprise.  The modern digital enterprise does not exist yet to my knowledge, but the vision is there. Strategic consultancy firms are all active exploring and explaining the potential benefits – I have mentioned McKinsey / Accenture / Capgemini before.

In the domain of PLM, there is a bigger challenge as here we are suffering from the fact that the word “Model” immediately gets associated with a 3D Model. In addition to the 3D CAD Model, there is still a lot of useful legacy data that does not match with the concepts of a digital enterprise. I wrote and spoke about this topic a year ago. Among others at PI 2017 Berlin and you can  check this presentation on SlideShare: How digital transformation affects PLM

Back to the various aspects of Model-Based

My first post: Model-Based – an introduction described my intentions what I wanted to explain.  I got some interesting feedback and insights from my readers . Some of the people who responded understood that the crucial characteristic of the model-based enterprise is to use models to master a complex environment. Business Models, Mathematical Models, System Models are all part of a model-based enterprise, and none of them have a necessary relation to the 3D CAD model.

Why Model-Based?

Because this is an approach to master complex environments ! If you are studying the concepts for a digital enterprise model, it is complex. Artificial intelligence, predictive actions all need a model to deliver. The interaction and response related to my first blog post did not show any problems – only a positive mindset to further explore. For example, if you read this blog post from Contact, you will see the message came across very well: Model-Based in  Model-Based Systems Engineering – what’s up ?

Where the confusion started

My second post: Why Model-Based? The 3D CAD Model  was related to model-based, focusing on the various aspects related to the 3D CAD model, without going into all the details. In particular, in the PLM world, there is a lot of discussion around Model-Based Design or Model-Based Definition, where new concepts are discussed to connect engineering and manufacturing in an efficient and modern data-driven way. Lifecycle Insights, Action Engineering, Engineering.com, PTC,   Tech-Clarity and many more companies are publishing information related to the model-based engineering phase.

Here is was surprised by Oleg’s blog with his post Model-Based Confusion in 3D CAD and PLM.

If you read his post, you get the impression that the model-based approach is just a marketing issue instead of a significant change towards a digital enterprise. I quote:

Here is the thing… I don’t see much difference between saying PLM-CAD integration sharing data and information for downstream processes and “model-driven” data sharing. It might be a terminology thing, but data is managed by CAD-PLM tools today and accessed by people and other services. This is how things are working today. If model-driven is an approach to replace 2D drawings, I can see it. However, 2D replacement is something that I’ve heard 20 years ago. However, 2D drawings are still massively used by manufacturing companies despite some promises made by CAD vendors long time ago.

I was surprised by the simplicity of this quote. As if CAD vendors are responsible for new ways of working. In particular, automotive and aerospace companies are pushing for a model-based connection between engineering and manufacturing to increase quality, time to market and reduced handling costs. The model-based definition is not just a marketing issue as you can read from benefits reported by Jennifer Herron (Re-use your CAD – the model-based CAD handbook – describing practices and benefits already in 2013) or Tech-Clarity (The How-To Guide for adopting model-based definition – describing practices and benefits – sponsored by SolidWorks)

Oleg’s post unleashed several reactions of people who shared his opinion (read the comments here). They are all confused, t is all about marketing / let’s not change / too complex. Responses you usually hear from a generation that does not feel and understand the new approaches of a digital enterprise. If you are in the field working with multiple customers trying to understand the benefits of model-based definition, you would not worry about terminology – you would try to understand it and make it work.

Model-Based – just marketing?

In his post, Oleg refers to CIMdata’ s explanation of the various aspects of model-based in the context of PLM. Instead of referring to the meaning of the various acronyms, Peter Bilello (CIMdata) presented at the latest PDT conference (Oct 2017 – Gothenburg) an excellent story related to the various aspects of the model-based aspects, actually the whole conference was dedicated to the various aspects of a Model-Based Enterprise illustrates that it is not a vendor marketing issue. You can read my comments from the vendor-neutral conference here: The weekend after PDT Europe 2017 Part 1 and Part 2.

There were some dialogues on LinkedIn this weekend, and I promised to publish this post first before continuing on the other aspects of a model-based enterprise.  Just today Oleg published a secondary post related to this topic: Model-Based marketing in CAD and PLM, where again the tone and blame is to the PLM/CAD vendors, as you can see from his conclusion:

I can see “mode-based” as a new and very interesting wave of marketing in 3D CAD and PLM.  However, it is not pure marketing and it has some rational. The rational part of model-based approach is to have information model combined from 3D design and all connected data element. Such model can be used as a foundation for design, engineering, manufacturing, support, maintenance. Pretty much everything we do. It is hard to create such model and it is hard to combine a functional solution from existing packages and products. You should think how to combine multiple CAD systems, PLM platforms and many other things together. It requires standards. It requires from people to change. And it requires changing of status quo. New approaches in data management can change siloed world of 3D CAD and PLM. It is hard, but nothing to do with slides that will bring shiny words “model-base”. Without changing of technology and people, it will remain as a history of marketing

Again it shows the narrow mindset on the future of a model-based enterprise. When it comes to standards I recommend you to register and watch CIMdata’s educational webinar called: Model-Based Enterprise and Standards – you need to register. John MacKrell CIMdata’s chairman gives an excellent overview and status of model-based enterprise initiative.  After having studied and digested all the links in this post, I challenge you to make your mind up. The picture below comes from John’s presentation, an illustration where we are with model-based definition currently

 

Conclusion

The challenge of modern businesses is that too often we conclude too fast on complex issues or we frame new developments because they do not fit our purpose. You know it from politics. Be aware it is also valid in the world of PLM. Innovation and a path to a modern digital enterprise do not come easy – you need to invest and learn all the aspects. To be continued (and I do not have all the answers either)

The recent years I have been mentioning several times addressing the term model-based in the context of a modern, digital enterprise. Posts like: Digital PLM requires a model-based enterprise (Sept 2016) or Item-Centric or Model-Centric (Sept 2017) describe some of the aspects of a model-based approach. And if you follow the PLM vendors in their marketing messages, everyone seems to be looking for a model-based environment.

This is however in big contrast with reality in the field. In February this year I moderated a focus group related to PLM and the Model-Based approach and the main conclusion from the audience was that everyone was looking at it, and only a few started practicing. Therefore, I promised to provide some step-by-step education related to model-based as like PLM we need to get a grip on what it means and how it impacts your company. As I am not an academic person, it will be a little bit like model-based for dummies, however as model-based in all aspects is not yet a wide-spread common practice, we are all learning.

What is a Model?

The word Model has various meanings and this is often the first confusion when people speak about Model-Based. The two main interpretations in the context of PLM are:

  • A Model represents a 3D CAD Model – a virtual definition of a physical product
  • A Model represents a scientific / mathematical model

And although these are the two main interpretations there are more aspects to look at model-based in the context of a digital enterprise. Let’s explore the 3D CAD Model first

The role of the 3D CAD Model in a digital enterprise

Just designing a product in 3D and then generating 2D drawings for manufacturing is not really game-changing and bringing big benefits. 3D Models provide a better understanding of the product, mechanical simulations allow the engineer to discover clashes and/or conflicts and this approach will contribute to a better understanding of the form & fit of a product. Old generations of designers know how to read a 2D drawing and in their mind understand the 3D Model.

Modern generations of designers are no longer trained to start from 2D, so their way of thinking is related 3D modeling. Unfortunate businesses, in particular when acting in Eco-systems with suppliers, still rely on the 2D definition as the legal document.  The 3D Model has brought some quality improvements and these benefits already justify most of the companies to design in 3D, still it is not the revolution a model-based enterprise can bring.

A model-based enterprise has to rely on data, so the 3D Model should rely on parameters that allow other applications to read them. These parameters can contribute to simulation analysis and product optimization or they can contribute to manufacturing. In both cases the parameters provide data continuity between the various disciplines, eliminating the need to create new representations in different formats. I will come back in a future post to the requirements for the 3D CAD model in the context of the model-based enterprise, where I will zoom in on Model-Based Definition and the concepts of Industry 4.0.

The role of mathematical models in a digital enterprise

The mathematical model of a product allows companies to analyze and optimize the behavior of a product. When companies design a product they often start from a conceptual model and by running simulations they can optimize the product and define low-level requirements within a range that optimizes the product performance. The relation between design and simulation in a virtual model is crucial to be as efficient as possible. In the current ways of working, often design and simulation are not integrated and therefore the amount of simulations is relative low, as time-to-market is the key driver to introduce a new product.

In a digital enterprise, design and simulations are linked through parameters, allowing companies to iterate and select the optimal solution for the market quickly. This part is closely related to model-based systems engineering (MBSE) , where the focus is on defining complex systems. In the context of MBSE I will also zoom in on the relation between hardware and software, which at the end will deliver the desired functionality for the customer. Again in this part we will zoom in on the importance of having a parameter model, to ensure digital continuity.

Digital Twin

There is still a debate if the Digital Twin is part of PLM or should be connected to PLM. A digital twin can be based on a set of parameters that represent the product performance in the field. There is no need to have a 3D representation, despite the fact that many marketing videos always show a virtual image to visualize the twin.

Depending on the business desire, there can be various digital twins for the same products in the field, all depending on the parameters that you want to monitor. Again it is about passing parameters, in this case from the field back to R&D and these parameters should be passed in a digital manner. In a future post I will zoom in on the targets and benefits of the digital twin.

Conclusion

There are various aspects to consider related to “model-based”.  The common thread for each of the aspects is related to PARAMETERS.  The more you can work with parameters to connect the various usages of a product/system, the closer you are related to the digital enterprise. The real advantages of a digital enterprise are speed (information available in real-time), end-to-end visibility (as data is not locked in files / closed systems).

PARAMETERS the objects to create digital continuity

 

 

 

 

%d bloggers like this: