CIMdata’s 2024 PLM Market & Industry Forum series theme is “Digital Twins: Enhancing Lifecycle Performance.” At this industry-leading Forum, CIMdata will frame digital twins in a series of presentations designed to brief the PLM Software and Service community (aka the PLM Economy) on the issues faced by industrial users. Sessions provide critical information to members of the PLM Economy, enabling them to respond to new and evolving requirements. Learn more about the 2024 PLM Market & Industry Forum here.

In March 2016, the world watched in awe as AlphaGo triumphed over Lee Sedol in a five-game Go match, marking the first time a computer Go program had defeated a 9-dan professional without a handicap. This monumental achievement resonated deeply in computer science and, more specifically, AI. Everyone took note within the realms of computer science and artificial intelligence (AI), sparking widespread interest and discussion. However, as time passed, the enthusiasm surrounding this event faded.

Fast forward to November 2022. The release of ChatGPT was all over the news, leading to a fascination with "Generative AI" that CIMdata believes will not die any time soon. It captures everyone's imagination, from quantum physicists to poets. Its most noteworthy feature is its versatility. For example, one of the demands of striking Hollywood writers was job protection against AI.

Like everyone else, engineering enterprises are also exploring possibilities with analytics, AI/ML technologies, and developing organizational and business strategies. AI/ML technologies are as significant in impact as the printing press, and few organizational functions will not be affected. AI/ML technology will impact innovation and product ideation, design and development, manufacturing, supply chain optimization, testing and quality control, sustainability, field monitoring and supervision, and regulatory compliance activities of the organization. AI/ML technologies will greatly impact cost-reduction efforts and the organization's profitability.

Generative AI is the most important among the many AI technologies that will find a place in organizational activities. Generative AI refers to a category of AI techniques and models designed to generate new content or data resembling human-generated content. These models are capable of authoring content indistinguishable from what a human might produce. Generative AI models rely on large datasets and advanced algorithms to understand patterns and relationships within the data, allowing them to generate novel outputs based on that understanding. Since the Generative AI models need a lot of data to train on, product lifecycle management (PLM) tools that manage the information flow across the enterprise are key to the successful deployment of Generative AI.

Initially, Generative AI may serve as an aid to human operators (as co-pilots or augmented intelligence). As these models get exposed to more and more data and workflow processes, they might start performing the lion's share of the work. Some of the challenges involved in achieving the end goal of autonomous operation are the continuous validation of AI models, resolution of hallucination issues associated with Generative AI technologies, and developing a sound regulatory framework to deal with risks arising from using these technologies.

CIMdata believes that Generative AI holds great potential to transform PLM across various industries. It offers a range of use cases that enhance design, efficiency, and sustainability throughout a product's lifecycle. AI-driven design optimization will allow engineers to explore multiple design alternatives, accelerating innovation while adhering to performance criteria.

Furthermore, AI-powered simulations and virtual prototyping have the potential to reduce the reliance on physical prototypes, saving time and resources. Supply chain optimization and material selection will benefit from AI's ability to analyze data, ensuring cost-effective procurement and eco-friendly material choices. Mass customization and personalization become feasible as AI tailors products to individual customer preferences. Quality control in manufacturing is already seeing the benefits of computer vision systems that detect defects and maintain high product standards. Predictive maintenance algorithms will prevent equipment failures by forecasting maintenance needs and reducing unplanned downtime. AI will also assist in regulatory compliance by tracking and automating updates, while lifecycle analytics will provide valuable insights for continuous improvement. Ultimately, integrating generative AI into PLM processes has huge potential to drive faster innovation, cost reduction, improved product quality, and a more sustainable approach to product development and management.

Key Takeaways:

• Analytics and AI/ML discussions are dominating boardrooms as well as street chat. Before long, most products and services offered and consumed by industrial companies will have a form of AI embedded in them.
• The commercial opportunities that analytics and AI/ML will unlock will be significant. They will be transformative, not just incremental. Human creativity will be augmented with a limitless ability to realize ideas (aided by AI). This will result in new products, services, and business models. Enterprise process and data management platforms will be key enablers in implementing AI technologies across the organization.
• The regulatory and legal framework around these technologies (especially access to learning data) will lag the development curve. Organizations must be mindful and develop a long-term strategy around using and sharing proprietary data.
• Upgrading the skill levels of human resources, educating customers on AI benefits, and dealing with the ethical and moral considerations associated with the significant productivity gains AI offers will be some of the biggest challenges facing business leaders in the "AI era."

The 2024 PLM Market & Industry Forum is a live event in Ann Arbor, MI, USA, - March 27, Frankfurt, Germany, - April 11, India - April 15, China - April 19, and Japan - April 23.

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Hope to see you at one of these live events!

Sandeepak