Exploring Practical AI Use Cases in Product Lifecycle Management

AI, ML, DX, artificial intelligence, PLM

Create a Roadmap for Building AI-Augmented PLM Capability

Building value with practical applications of AI is fundamental to digital transformation initiatives in 2023 – and will continue to be in 2024. There is enormous pressure in every organization to keep pace with practical AI innovation in order to stay competitive. While most of the recent buzz is on Generative AI and Large Language Models (LLMs) like ChatGPT, there is a much broader set of AI/ML technologies and workflow automation that are transforming the modern enterprise. Interestingly, adoption seems to have been slower in digital engineering and PLM use cases than in other enterprise business processes like customer support and marketing. While classic simulation and digital twins have been making a massive impact on the engineering space for years, finding practical applications of modern AI is still in its early days. Recent research from McKinsey estimated that 10x more companies are actively relying on classic simulation technologies vs. AI/ML. They estimated that only 5% of organizations are actively using AI/ML today.

We have seen growing interest in the topic from the Aras community and will be exploring the topic more frequently in our blog and monthly webinars. It will also be a topic at our upcoming community event, ACE 2024.  

While AI hype is rampant, we’ll strive to focus on practical applications and avoid AI-washing and conflating Generative AI with the broader set of AI/ML and data science technologies that have applications to digital engineering.  

Join us for an upcoming webinar with researchers from the Fraunhofer Institute for Mechatronic Systems Design and AI Marketplace to discuss the basics of applying Gen AI to PLM and demonstrate some of the “quick wins” for gaining value from the technology in your digital engineering programs. Here is a preview of and some background for our discussion.

The state of AI, Generative AI, and Large Language Models (LLMs) in PLM

Putting all the buzz aside, Generative AI holds the potential to transform digital engineering and PLM. Gartner predicts that Generative AI will play a role in 70% of text- and data-heavy tasks by 2025, up from less than 10% in 2023. They have also concluded that by 2026, Generative AI capabilities would be implemented in 50% of PLM vendor solutions instead of 5% now. There are many reasons digital engineering may be slower to adopt AI, and it makes for a good discussion. A few to consider include:

  1. Concern over security, IP protection, and regulatory compliance
  2. Data quality and reliability
  3. The complexity of integrating of LLMs into existing application infrastructure
  4. Identifying practical applications that augment existing business processes

Thinking through these topics and creating a proactive strategy for leveraging AI is the first step in building a roadmap for your organization.

The Aras perspective on AI and digital engineering

Aras Innovator® is an open platform for building collaborative digital engineering and PLM applications on a unified digital thread. Our customers and partners leverage the low code development capability within the platform to extend and adapt Aras applications to fit their specific business needs. The centralized architecture establishes a unified digital thread that connects critical product data, information, and process information across the full spectrum of supported business processes. The open design enables connectivity to the entire digital engineering and enterprise application ecosystem, including manufacturing, supply chain, maintenance, and asset management application ecosystems. This single source of truth for product data, combined with powerful query and search APIs, positions Aras Innovator as a platform on which to build AI-augmented PLM capabilities.  

Partners like AI Marketplace and Razorleaf are doing this today.

Exploring the full potential of AI to transform PLM

Aras CTO, Rob McAveney, discussed the subject of AI applications in PLM and digital engineering in this recent video interview. It’s a great discussion about the hype and potential reality of AI-augmented PLM. Rob covered the important subject of AI copilots. The use of this term in the context of digital engineering is on the rise, but typically without any specificity on the applications. Rob discussed the potential for AI-driving virtual assistants to make PLM users’ jobs easier – going beyond basic “auto-complete” or “are you trying to…” type utilities most commonly associated with the concept.  

The discussion went beyond the subject of Generative AI to cover the potential for incorporating predictive AI/ML into advanced simulation applications. AI holds the potential to not only transform engineering business process efficiency but also accelerate design cycles, improve product quality, and impact the actual design of organizations’ core product offerings.

Join the conversation on integrating AI and PLM

Let us help you kickstart the conversation about Generative AI in product lifecycle management with a conversation with researchers from Fraunhofer Institute and AI Marketplace. We will cover the basics of AI, Generative AI, and Large Language Models (LLMs) in a discussion focused on finding practical applications of the technology, including intelligent documentation, AI-augmented collaboration, and knowledge management. The webinar will include a live demonstration showcasing AI's practical, tangible implementation in a PLM system, providing experiential insight into the future of intelligent and interconnected product lifecycle management.

Piqued your curiosity? Register now: Evolution or Revolution? Exploring Applied Generative AI and LLMs for Product Lifecycle Management.