How far is 3DEXPERIENCE R&D from developing Artificial Intelligence in PLM?

How far is 3DEXPERIENCE R&D from developing Artificial Intelligence in PLM?

I continue posting my comments from 3DEXPERIENCE WORLD 2020 I attended earlier this week in Nashville, TN. Today, I want to talk about artificial intelligence. AI and Machine Learning made a long way from one of the very early introductions of checkers play.

Back in the 1950s, IBM 701 introduced the program for the first time pioneering AI and machine learning. Developed by Arthur Samuel, to play on the IBM 701 and it was demonstrated to the public on television.

In 1962, self-proclaimed checkers master Robert Nealey played the game on an IBM 7094 computer. The computer won. Other games resulted in losses for the Samuel Checkers program, but it is still considered a milestone for artificial intelligence and offered the public in the early 1960s an example of the capabilities of an electronic computer.

There are tons of predictions about the future of AI and Machine Learning. Earlier today, I captured a bunch of interesting facts about AI and Machine Learning in KommandoTech’s article. Here is my favorite:

According to Forbes, Global revenues from AI enterprise applications are expected to rise from $1.62 billion in 2018 to $31.2 billion in 2025. Forbes statistics on artificial intelligence also state that over the next seven years, revenues from AI enterprise applications will attain a compound annual growth rate of 52.59%.  AI IT operations statistics reveal that patient data processing, localization and mapping, predictive maintenance, and intelligent recruitment are the most common.

During the first day keynote, CEO of Solidworks Gian Paolo Bassi demonstrated some interesting functions using elements of AI and Machine learning.

As such, machine learning / AI is used to suggest fillet edge selection, propagate sketch patterns and mate components. These functions are part of the selection helper, sketch helper, and mate connector.

These new elements of functionality are adding a new level of productivity. The algorithm predicts and suggests what needs to be selected next time based on the work completed up to the current point. Also, it analyzes other edges when assisting you with edge selections and some others.

These functions made me think about what is the readiness of these technologies in a broader scope of PLM development. I can see several very interesting candidates to use predictive analytics such as change management assistant, cost prediction, supplier (sourcing) assistance, and many others (if you want to talk more about them, contact me at OpenBOM via oleg [at] openbom [dot] com). I’m happy to discuss more about this topic.

What is my conclusion?

Productivity and intelligence is the name of the game for AI and Machine Learning. I can see Dassault Systemes making a progress in applying predictive analytics and machine learning in 3DEXPERIENCE. It gives new functions and features to leapfrog from current Solidworks desktop capabilities. Leveraging cloud data management in design, engineering, and manufacturing can be a gamechanger in the domain of machine learning and AI in design and PLM. Data is everything when it comes to AI. Therefore, the biggest advantage for machine learning is to use multi-tenant data management technologies allowing develop intelligence by gleaning information from diverse customer data sets. Just my thought…

Best, Oleg

Disclaimer: I’m co-founder and CEO of OpenBOM developing cloud-based bill of materials and inventory management tool for manufacturing companies, hardware startups, and supply chain. My opinion can be unintentionally biased.


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