You are currently browsing the tag archive for the ‘Artificial Intelligence’ tag.

Happy New Year to all of you, and may this year be a year of progress in understanding and addressing the challenges ahead of us.

To help us focus, I selected three major domains I will explore further this year. These domains are connected – of course – as nothing is isolated in a world of System Thinking. Also, I wrote about these domains in the past, as usually, noting happens out of the blue.

Meanwhile, there are a lot of discussions related to Artificial Intelligence (AI), in particular ChatGPT (openAI). But can AI provide the answers? I believe not, as AI is mainly about explicit knowledge, the knowledge you can define by (learning) algorithms.

Expert knowledge, often called Tacit knowledge, is the knowledge of the expert, combining information from different domains into innovative solutions.

I started my company, TacIT, in 1999 because I thought (and still think) that Tacit knowledge is the holy grail for companies.

Let’s see with openAI how far we get ……

 

Digitization of the PLM domain

The PLM domain is suffering from its legacy data (documents), legacy processes (linear – mechanical focus) and legacy people (siloed). The statement is a generalization.

More details can be found in my blog series: The road to model-based and connected PLM.

So why should companies move to a model-based and connected approach for their PLM infrastructure?

There are several reasons why companies may want to move to a model-based and connected approach for their Product Lifecycle Management (PLM) infrastructure:

  • Increased efficiency: A model-based approach allows for creating a digital twin of the product, which can be used to simulate and test various design scenarios, reducing the need for physical prototypes and testing. This can lead to faster and more efficient product development.
  • Improved collaboration: A connected PLM infrastructure allows for better collaboration between different teams and departments, as all product-related information is stored in a central location and can be accessed by authorized personnel. This can improve communication and decision-making within the organization.
  • Enhanced visibility: A model-based PLM system provides a single source of truth for all product-related data, giving management a clear and comprehensive view of the product development process. This can help identify bottlenecks and areas for improvement.
  • Reduced risk: By keeping all product-related information in a centralized location, the risk of data loss or inconsistencies is reduced. This can help ensure that the product is developed in accordance with regulatory requirements and company standards.
  • Increased competitiveness: A model-based and connected PLM infrastructure can help companies bring new products to market faster and with fewer errors, giving them a competitive advantage in their industry.

The text in italics was created by ChatGPT. After three learning cycles, this was the best answer I got. What we are missing in this answer is the innovative and transformative part that modern PLM can bring. Where is the concept of different ways of working, and new business models, both drivers for digitalization in many businesses?

Expert knowledge related to Federated PLM (or Killing the PLM Monolith) are topics you will not find through AI. This is, for me, the most interesting part to explore.

We see the need but lack a common understanding of the HOW.

Algorithms will not innovate; for that, you need Tacit intelligence & Curiosity instead of Artificial Intelligence. More exploration of Federated PLM this year.

 

PLM and Sustainability

Last year as part of the PLM Global Green Alliance, we spoke with six different PLM solution providers to understand their sustainability goals, targets, and planned support for Sustainability. All of them confirmed Sustainability has become an important issue for their customers in 2022. Sustainability is on everyone’s agenda.

Why is PLM important for Sustainability?

PLM is important for Sustainability because a PLM helps organizations manage the entire lifecycle of a product, from its conception and design to its manufacture, distribution, use, and disposal. PLM can be important for Sustainability because it can help organizations make more informed decisions about the environmental impacts of their products and take steps to minimize those impacts throughout the product’s lifecycle.

For example, using PLM, an organization can consider the environmental impacts of the materials that are used in a product, the energy consumption of the manufacturing process, the product’s end-of-life disposal, and other factors that may affect its overall Sustainability. By considering these factors early in the design process, organizations can make more sustainable choices that reduce the environmental impact of their products over their lifecycle.

In addition, PLM can help organizations track and measure the Sustainability of their products over time, allowing them to continuously improve and optimize their products for Sustainability. This can be particularly important for organizations that are looking to meet regulatory requirements or consumer demand for more sustainable products.

Again not a wrong answer, but there is no mention of supporting the concepts of the circular economy, the potential of using digital twins at the various lifecycle stages of the products to perform trade-off studies in the virtual world, or to analyze the product behavior from the physical world in the virtual world for optimization.

This is (again), for me, the most interesting part to explore.

We see the need but lack the sense of urgency on the NOW.

More on Sustainability this year.

 

PLM Education at all levels

Historically PLM was framed as an “engineering thing” or a system needed for R&D/Engineering. Modern PLM is much broader and, unfortunately, more hard to grasp. I support the CIMdata definition:

CIMdata defines PLM as:

  • A strategic business approach that applies a consistent set of business solutions that support the collaborative creation, management, dissemination, and use of product definition information

  • Supporting the extended enterprise (customers, design and supply partners, etc.)

  • Spanning from concept to end of life of a product or plant

  • Integrating people, processes, business systems, and information

And even here, I would say this definition is challenging as the scope is extensive and could touch a lot of activities inside an enterprise. As I wrote last year in my series of posts related to PLM and Education, there is:

Strategy education (what are the trends/potential of digital transformation in the business domain related to the company’s products)

Methodology/ Academic Education (independent from tools, what are the best practices, where they reside, potential lessons learned and pitfalls to avoid)

Organisational Change Management (the Education and support needed to enable a business transformation – modern PLM is a transformation enabler)

By asking ChatGPT for their opinion, we learn the following:

Product Lifecycle Management (PLM) education refers to training and development programs that focus on teaching individuals how to effectively manage the lifecycle of a product within an organization. This can include a wide range of topics, such as product design, development, and engineering; supply chain management; quality control and assurance; and product retirement and disposal.

Some specific types of PLM education that a company may need to provide to its employees include:

  1. Introduction to PLM: This type of training is designed to provide a general overview of PLM concepts and practices and may be suitable for employees who are new to the field or who have limited experience with PLM.
  2. PLM software training: Many companies use specialized PLM software to manage their product lifecycle processes. Employees who will be using this software will need training on how to use it effectively.
  3. Industry-specific PLM training: Depending on the industry in which a company operates, there may be specific PLM practices and regulations that employees need to be familiar with. For example, a company in the aerospace industry may need to provide training on PLM practices that are specific to the aerospace industry.
  4. Leadership and management training: For employees who are responsible for leading and managing PLM projects or teams, additional training in leadership and project management may be necessary.

Overall, the types of PLM education that a company needs will depend on the specific needs and goals of the organization, as well as the roles and responsibilities of its employees.

In general, we see from the answer that strategy and organizational change management beyond the tool are not considered.

This is precisely the area where a PLM Expert can help.

We see the need for Education, but we lack the willingness to invest in it.

 

Conclusion

It was an exciting exercise to combine my blogging thoughts with the answers from OpenAI. I am impressed by the given answers, knowing that the topics discussed about PLM are not obvious. On the other hand, I am not worried that AI will take over the job of the PLM consultant. As I mentioned before, the difference between Explicit Knowledge and Tacit Knowledge is clear, and business transformations will largely depend on the usage of Tacit knowledge.

I am curious about your experiences and will follow the topics mentioned in this post and write about them with great interest.

 

 

 

Translate

Categories

  1. Jos, one could take the approach that there is an engineering transformation strategy that can be realized by implementing PLM…

  2. Jos, I agree we should break out from the monolithic approach as this typically means lock-in, risk and frustration. The…

  3. Jos, Thanks for these insights. I believe that the mature capabilities provided by advanced toolsets can also be of benefit…

%d bloggers like this: