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Last week I wrote about the recent PLM Road Map & PDT Spring 2021 conference day 1, focusing mainly on technology. There were also interesting sessions related to exploring future methodologies for a digital enterprise. Now on Day 2, we started with two sessions related to people and methodology, indispensable when discussing PLM topics.
Designing and Keeping Great Teams
This keynote speech from Noshir Contractor, Professor of Behavioral Sciences in the McCormick School of Engineering & Applied Science, intrigued me as the subtitle states: Lessons from Preparing for Mars. What Can PLM Professionals Learn from This?
You might ask yourself, is a PLM implementation as difficult and as complex as a mission to Mars? I hoped, so I followed with great interest Noshir’s presentation.
Noshir started by mentioning that many disruptive technologies have emerged in recent years, like Teams, Slack, Yammer and many more.
The interesting question he asked in the context of PLM is:
As the domain of PLM is all about trying to optimize effective collaboration, this is a fair question
Structural Signatures
Noshir shared with us that it is not the most crucial point to look at people’s individual skills but more about who they know.
Measure who they work with is more important than who they are.
Based on this statement, Noshir showed some network patterns of different types of networks.
Click on the image to see the enlarged picture.
It is clear from these patterns how organizations communicate internally and/or externally. It would be an interesting exercise to perform in a company and to see if the analysis matches the perceived reality.
Noshir’s research was used by NASA to analyze and predict the right teams for a mission to Mars.
Noshir went further by proposing what PLM can learn from teams that are going into space. And here, I was not sure about the parallel. Is a PLM project comparable to a mission to Mars? I hope not! I have always advocated that a PLM implementation is a journey. Still, I never imagined that it could be a journey into the remote unknown.
Noshir explained that they had built tools based on their scientific model to describe and predict how teams could evolve over time. He believes that society can also benefit from these learnings. Many inventions from the past were driven by innovations coming from space programs.
I believe Noshir’s approach related to team analysis is much more critical for organizations with a mission. How do you build multidisciplinary teams?
The proposed methodology is probably best for a holocracy based organization. Holocrazy is an interesting concept for companies to get their employees committed, however, it also demands a type of involvement that not every person can deliver. For me, coming back to PLM, as a strategy to enable collaboration, the effectiveness of collaboration depends very much on the organizational culture and created structure.
DISRUPTION – EXTINCTION or still EVOLUTION?
We talk a lot about disruption because disruption is a painful process that you do not like to happen to yourself or your company. In the context of this conference’s theme, I discussed the awareness that disruptive technologies will be changing the PLM Value equation.
A disruption like the switch from mini-computers to PCs (killed DEC) or from Symbian to iOS (killed Nokia) is therefore not likely to happen that fast. Still, there is a need to take benefit from these new disruptive technologies.
My presentation was focusing on describing the path of evolution and focus areas for the PLM community. Doing nothing means extinction; experimenting and learning towards the future will provide an evolutionary way.
Starting from acknowledging that there is an incompatibility between data produced most of the time now and the data needed in the future, I explained my theme: From Coordinated to Connected. As a PLM community, we should spend more time together in focus groups, conferences on describing and verifying methodology and best practices.
Nigel Shaw (EuroStep) and Mark Williams (Boeing) hinted in this direction during this conference (see day 1). Erik Herzog (SAAB Aeronautics) brought this topic to last year’s conference (see day 3). Outside this conference, I have comparable touchpoints with Martijn Dullaert when discussing Configuration Management in the future in relation to PLM.
In addition, this decade will probably be the most disruptive decade we have known in humanity due to external forces that push companies to change. Sustainability regulations from governments (the Paris agreement), the implementation of circular economy concepts combined with the positive and high Total Share Holder return will push companies to adapt themselves more radical than before.
What is clear is that disruptive technologies and concepts, like Industry 4.0, Digital Thread and Digital Twin, can serve a purpose when implemented efficiently, ensuring the business becomes sustainable.
Due to the lack of end-to-end experience, we need focus groups and conferences to share progress and lessons learned. And we do not need to hear the isolated vendor success stories here as a reference, as often they are siloed again and leading to proprietary environments.
You can see my full presentation on SlideShare: DISRUPTION – EXTINCTION or still EVOLUTION?
Building a profitable Digital T(win) business
Beatrice Gasser, Technical, Innovation, and Sustainable Development Director from the Egis group, gave an exciting presentation related to the vision and implementation of digital twins in the construction industry.
The Egis group both serves as a consultancy firm as well as an asset management organization. You can see a wide variety of activities on their website or have a look at their perspectives
Historically the construction industry has been lagging behind having low productivity due to fragmentation, risk aversion and recently, more and more due to the lack of digital talent. In addition, some of the construction companies make their money from claims inside of having a smooth and profitable business model.
Without innovation in the construction industry, companies working the traditional way would lose market share and investor-focused attention, as we can see from the BCG diagram I discussed in my session.
The digital twin of construction is an ideal concept for the future. It can be built in the design phase to align all stakeholders, validate and integrate solutions and simulate the building operational scenarios at almost zero materials cost. Egis estimates that by using a digital twin during construction, the engineering and construction costs of a building can be reduced between 15 and 25 %
More importantly, the digital twin can also be used to first simulate operations and optimize energy consumption. The connected digital twin of an existing building can serve as a new common data environment for future building stakeholders. This could be the asset owner, service companies, and even the regulatory authorities needing to validate the building’s safety and environmental impact.
Beatrice ended with five principles essential to establish a digital twin, i.e
I think the construction industry has a vast potential to disrupt itself. Faster than the traditional manufacturing industries due to their current needs to work in a best-connected manner.
Next, there is almost no legacy data to deal with for these companies. Every new construction or building is a unique project on its own. The key differentiators will be experience and efficient ways of working.
It is about the belief, the guts and the skilled people that can make it work – all for a more efficient and sustainable future.
Leveraging PLM and Cloud Technology for Market Success
Stan Przybylinski, Vice President of CIMdata, reported their global survey related to the cloud, completed in early 2021. Also, Stan typified Industry 4.0 as a connected vision and cloud and digital thread as enablers to implementing this vision.
The companies interviewed showed a lot of goodwill to make progress – click on the image to see the details. CIMdata is also working with PLM Vendors to learn and describe better the areas of beneft. I remain curious about who comes with a realization and business case that is future-proof. This will define our new PLM Value Equation.
Conclusion
These were two exciting days with enough mentioning of disruptive technologies. Our challenge in the PLM domain will be to give them a purpose. A purpose is likely driven by external factors related to the need for a sustainable future. Efficiency and effectiveness must come from learning to work in connected environments (digital twin, digital thread, industry 4.0, Model-Based (Systems) Engineering.
Note: You might have seen the image below already – a nice link between sustainability and the mission to Mars
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.
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