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PLM Trends


In this edition let’s look at the hottest technology in town, The AI. Let’s understand the impact of AI in PLM. What are AI benefits, Issues it will lead to, what is the BEST way out for us and finally what will rule in the new PLM world with AI in it.

1) Trend Related to AI in PLM : LLMs to LDMs

As they say Drawing is the language of an engineer. 

In the new PLM world with AI, Large Language Models (LLMs) will become the Large Drawing Models (LDMs). Natural Language Processing (NLP) will evolve into Natural Drawing Processing. 

This metamorphosis heralds a transformative era where AI, will visualize the way we engineers do!

This HUGE transformation will lead to many benefits.

2) Benefits of AI in PLM
  • Increasing Efficiency:AI in PLM is a game-changer, promising to enhance efficiency across industrial engineering functions. From design conceptualization to manufacturing processes, AI can automate repetitive tasks, allowing engineers to focus on more strategic and creative aspects of product development. The application of AI algorithms in simulation and analysis can expedite decision-making processes, reducing time-to-market for new products.
  • Improving Effectiveness:The integration of AI in PLM enables predictive analytics and data-driven decision-making. This ensures that product development and lifecycle management are aligned with market demands and customer expectations. Enhanced effectiveness is observed in areas like supply chain management, where AI algorithms optimize logistics and inventory, reducing costs and minimizing errors.

But all will not be hunky-dory. As like any new technology, AI will also have its issues. In fact, AI can have BIGGER ISSUES.

3) Issues with the Use of AI in PLM
  • Data Privacy/IP Issues:AI in PLM will have to rely heavily on vast datasets, including proprietary design information. Ensuring data privacy and protecting intellectual property (IP) become critical concerns. Striking a balance between leveraging AI’s potential and safeguarding sensitive information is a challenge that companies will have to navigate.
  • Customized LDMs for Big Corporations:While product companies might start with shared Large Drawing Models (LDMs), big corporations will demand customization due to IP concerns. In fact they might have to design their own dedicated LDMs. In addition to HUGE COST of this, it will also come up with its own challenges of industry standardization, issues of interoperability and collaboration.
  • Safety Concerns:An hallucination of AI (Hallucination is a kind of an error where the algorithm sleeps for some time leading to wrong results/output) in a marketing write up is acceptable. But it can’t be accepted in an automobile part especially if that part is a critical component saving the lives of the people inside. 

Ensuring the safety and reliability of AI-generated designs will be paramount, prompting concerns about regulations and standards to guarantee product integrity.

These are some Known Unknowns but what about the Unknown Unknowns that are about to come in future? 

What will be the BEST way out to go ahead with AI in PLM? Let’s find out here :

4) The BEST Way Out : How AI Will Be Implemented in PLM
  • Trial on Non-Critical Parts:Initiating AI implementation on non-critical components allows organizations to gauge its impact and refine processes without risking critical functionalities. This iterative approach helps build confidence and familiarity with AI capabilities.
  • Peripheral Function Integration:Implementing AI in peripheral functions, such as planning in design, manufacturing, customer support, and maintenance, offers a gradual introduction. These areas can benefit from enhanced automation and decision support, showcasing the broader potential of AI.
  • Quick ROI with Part Search and Reuse:A swift return on investment (ROI) is achievable by employing AI in the search and reuse of different part numbers and their corresponding drawings. This streamlines the design process, promotes knowledge sharing, and optimizes resource utilization.
  • Automation of Change Management for Non-Critical Components:Automating change management processes for non-critical components reduces manual intervention, accelerates decision-making, and minimizes errors. This iterative approach allows organizations to fine-tune AI applications before extending them to critical workflows.
  • Enhancing User Experience (UI/UX):Improving the User Interface (UI) and User Experience (UX) of PLM software through AI-driven enhancements enhances user adoption. Intuitive interfaces powered by machine learning algorithms contribute to a more seamless and productive user experience.So with the AI in PLM, what will be change in your life. Let’s find that out briefly here :
5) What Will Rule in the Future (with AI in PLM)
  • Just like Content is KING, “Data will be the NEW KING”AI is useless without data. Big corporations are sitting on a huge pile of data. In PLM context, data is getting generated from Design files, Bill of Materials (BOM), maintenance reports, drawings, and enterprise databases etc. Absolutely everything on the shop floor is virtually emitting data all the time. Acquiring, cleaning, and effectively utilizing this data will become imperative for successful AI activities in PLM.
  • Rise of the Data Scientist Role:As data takes the center stage, the role of a Data Scientist becomes pivotal in the PLM world. These experts will be tasked with extracting insights, developing algorithms, and ensuring the quality of data inputs. The demand for skilled Data Scientists is expected to soar as organizations increasingly recognize the indispensable role of data in driving AI initiatives.

Conclusion : 

The integration of AI into PLM signifies a transformative journey with remarkable benefits, accompanied by challenges that demand strategic solutions. The future promises a convergence of engineering language aka Drawing with AI capabilities, where Natural Drawing Processing (NDP) will revolutionize the way products are designed, developed, and managed. 

While addressing privacy concerns, customization needs, and safety considerations, organizations can unlock the true potential of AI in PLM by adopting a phased and strategic implementation approach. As the industry embraces this technological evolution, the reign of data and the ascent of the Data Scientist will define the next chapter in the PLM narrative.

While the story of AI has just started, and still will be written in years to come, it will be great to have your views on the topic. What do you think will be the pros and cons of AI in PLM World? 

Feel free to comment below and we all will see a bit clearly through this fog of the BIGGEST TECHNOLOGY TRANSFORMATION of our lives.

With MechiSpike, you can leverage your PLM to the fullest. 

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To your PLM success!

Warm regards,

Chandu Namuduri

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