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ManufacturingJune 4, 2019

Artificial Intelligence and Machine Learning at Dassault Systèmes – Part 7/7

This is the conclusion to our seven-part Industrial Artificial Intelligence (AI) blog…
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Avatar Karin

This is the conclusion to our seven-part Industrial Artificial Intelligence (AI) blog series, In the last installment we explored the value of AI in industrial sectors. Now let’s look at how AI and machine learning (ML) technologies are integrated into EXALEAD and NETVIBES Information Intelligence on the 3DEXPERIENCE platform.

EXALEAD and NETVIBES are the Dassault Systèmes Information Intelligence brands on the 3DEXPERIENCE platform. They enable organizations to gather, align and enrich big data – whether internal or external, structured or unstructured, simple or complex, real-time or archived – and to deliver that information to users within high-value applications. The portfolio includes:

  • Sourcing & Standardization Intelligence
  • V+R Business Intelligence
  • Industry Intelligence

The solutions have incorporated big data management technologies and advanced analytics, including ML tools and techniques, since the company’s inception. Specifically, EXALEAD’s first product was a Web-scale search platform designed for enterprise use. It used ML to enrich data by surfacing hidden information and relationships, and successfully integrated advanced analytics into its sub-second query processing framework. As such, it provided an ideal foundation for the development of EXALEAD’s current ML technologies on the 3DEXPERIENCE platform, and its big data processing framework remains the core engine powering the brand’s suite of enterprise applications.

Sourcing & Standardization Intelligence

The Sourcing & Standardization Intelligence solution addresses four common and costly problems about how to: define product part standards and share them across projects; choose whether to create a new part, reuse an existing one from a previous project, or buy it from a supplier; equip purchasing departments with the right level of knowledge to improve cost efficiency; and eventually, drive reuse in engineering in accordance with the company’s sourcing and standardization policy.

These problems are solved by AI and ML techniques that automatically group parts together based on their shape similarity and semantic characteristics, as well as aggregating technological and business information to break down the silos between engineering and procurement. The result is a pre-identified classification of parts that complexity and sourcing managers can review and use to launch appropriate actions to either de-duplicate the part references or renegotiate with suppliers.

In addition, the PartSupply service on the 3DEXPERIENCE Marketplace makes comparative data available on tens of millions of catalogued parts from more than 700 suppliers. Users can search to evaluate technical characteristics, performance and quality, and quickly secure vendors in their area able to deliver.

Part 2: Industrial applications of Artificial Intelligence and Machine Learning

Part 3: Differentiating Between Artificial Intelligence, Machine Learning and Deep Learning

Part 4: Benefits of Machine Learning in Industrial Contexts

Part 5: Key Challenges of Artificial Intelligence in Industrial Sectors

Part 6: Realizing the Value of Artificial Intelligence in Industrial Sectors

Part 7: Artificial Intelligence and Machine Learning at Dassault Systèmes

to stay on top of the latest industry news, ask questions and collaborate with peers:

Learn more about EXALEAD on the 3DEXPERIENCE platform.

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