Bringing AI techniques to systems engineering

Complex systems—which often include computing capabilities, mechanical systems, and electronics—are particularly challenging to design. Artificial intelligence can be used to assist engineers throughout the design process, and less-critical design tasks can even be automated.

Artificial intelligence (AI) has a growing role to play in business processes, especially product design. When it comes to complex systems, specialists from a wide range of fields must work together, sharing information and providing input throughout the design and simulation processes. The researchers assigned to our INCA program are working on two key practical applications for AI techniques in the fields of software and systems engineering.

Automating certain design tasks

AI techniques can be used to automate a certain number of activities and tasks at different stages of the design process. In the earliest stages of project development, for example, AI can be used to help formalize a problem and, potentially, reuse solutions from previous projects and even from completely different industries. Learning algorithms—machine learning and deep learning—and expert systems can be used to build design automations companies can use to make their processes more efficient.

This approach is particularly helpful in software engineering, where open-source code repositories and other resources are readily available, serving as huge knowledge bases. Researchers can also extract knowledge from resources such as Wikipedia, scientific article repositories, and industry-specific ontologies to bring these learning algorithms to new engineering use cases.

Developing chatbots for engineering support

In addition to these automation tools, our INCA program is developing specialist chatbots for systems engineering. These virtual assistants support engineers throughout the product development process. Once the chatbot is launched, it stays open on the engineer’s computer, analyzing work in real time, making suggestions, and highlighting potential issues. The engineer can also ask the chatbot for advice or suggestions based on similar projects developed within the company or even in other industries.

Natural language processing (NLP) facilitates chatbot–user interactions. Users make requests—like describing the product they wish to design—in natural language; the chatbot analyzes the text, and then generates an architecture model corresponding to the user’s requirements. This model can then be used as a basis for further development by the engineering team.

CEA-List technologies

  • LIMA/CLIMA, linguistic analysis tool
  • Conversational agent based on rules and computation of semantic similarity

European programs

  • H2020 Decoder
  • ANR LabForSims2

See also

Research programs

Augmented digital engineering

Assisting engineers with the design of increasingly software-intensive complex systems.
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Research programs

Formal methods

The purpose of the INCA program is to make sophisticated formal verification methods accessible to all companies that develop code.
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Research programs

Open-source tools for engineering

CEA-List creates open-source engineering and design tools, a pragmatic approach designed to give industrial R&D professionals access to the latest advances coming out of our labs.
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Research programs

AI for systems engineering

CEA-List develops algorithms to help engineers face the challenges of designing complex systems.
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