DIHNAMIC
Webinar Dihnamic #30 – AI and operations research: optimizing industrial production
AI and operations research: optimizing industrial production through data and decision-making
In an industrial context marked by pressure on costs, lead times, and quality, companies must continuously improve their operational performance. However, optimizing production remains complex: variability, multiple constraints, uncertainties… Decisions are often based on limited tools and heavily dependent on human expertise.
In this context, artificial intelligence and operations research are emerging as powerful levers to help industrial companies better manage their operations. Far from replacing human expertise, these approaches enable companies to structure decision-making and optimize complex systems based on data and mathematical modeling.
This Dihnamic webinar, held on July 2, 2026, explored how to combine AI and operations research to address real industrial production challenges. Through use cases from aeronautics and energy, speakers demonstrated how these tools can provide valuable decision support at multiple time horizons, from short-term operational management to strategic planning.
Hosted by Stéphanie Roussel (ONERA) and Théo Lecerf (Fieldbox), the session highlighted the complementarity between these two disciplines. While operations research focuses on modeling and optimizing under constraints, artificial intelligence brings the ability to learn from data and handle uncertainty.
The webinar addressed key questions for industrial companies:
- How to optimize production planning in the face of uncertainties (supplier delays, urgent requests, task variability)
- How to reduce operational costs (energy, resources, time) using optimization models
- How to build robust, explainable decision-support tools aligned with operational constraints
- Which key factors determine the success of a project (clearly defined problem, data availability, operational integration, user adoption)
Through a real-world case study on energy optimization in water networks, this replay highlights a key insight: the performance of a model does not solely depend on its algorithmic power, but on its ability to integrate into the company’s operational reality. The choice of the right approach (optimization, heuristics, learning, or hybrid) must therefore always be guided by real-world constraints.
Missed the live session? The replay is available below.
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In case you are interested in Dihnamic, you want to join it or you have any question, do not hesitate to contact us!
Want to contact the project coordinator? Contact :
Véronique DESBLEDS & Maria EL JAOUDI (ADI Nouvelle-Aquitaine)
contact@dihnamic.euTel. +33 (0)6 71 19 79 27
Are you a company ? Contact :
Véronique DESBLEDS & Maria EL JAOUDI (ADI Nouvelle-Aquitaine)
contact@dihnamic.euTel. +33 (0)6 71 19 79 27
Are you a journalist ? Contact :
Claire BOUCHAREISSAS (ADI Nouvelle-Aquitaine)
c.bouchareissas@adi-na.frTel. +33 (0)6 82 36 76 36