Dr. Fouad el Khaldi

Dr. Fouad el Khaldi, General Manager, ESI Group

Dr. Fouad el Khaldi joined ESI Group (ESI) in 1988 and is currently, General Manager of Industry Strategy and Innovation, with special focus on co-creation innovation projects. With over 35 years of experience in the CAE industry Dr. el Khaldi has undertaken several different roles of increasing responsibility at ESI including the role of Senior Consultant for a joint venture created by IBM Japan and ESI in Tokyo where he was in charge of developing a new solution for sheet metal forming simulation in collaboration with the Japanese Automotive Industry. After the conclusion of that project Dr. el Khaldi established PAM-STAMP as an industrial simulation software product and the Virtual Manufacturing Product line at ESI. In 2000 he was a key contributor to the success of ESI’;s initial public offering and its associated business transformation. In 2004 he was appointed Manager of the Virtual Prototyping Software Branch which included significant M&A activity. Dr. el Khaldi is the author or co-author of numerous technical papers about CAE innovation and industry application of Virtual Prototype testing in the engineering and manufacturing domains. He also holds several patents in the CAE and Virtual Prototyping field.

Evolve from Virtual Prototype Testing to Hybrid Twin : Challenges & Benefits

Modern industry has adapted simulation in their value chain, either for product design and validation, or for manufacturing process design and validation. There is a difference in maturity of application levels. It spans from better understanding the tests, better testing design, reducing the prototype test period, and cost. Some companies manage to develop and to master their Virtual Prototype Testing industrial process to the necessary level to reach the virtual pre-certification milestone. They displace the prototype testing, saving the related cost and delay. Indeed, this is a journey of building knowledge and competency, translated into method and processes, supported by the required capabilities: data, computing capacity, appropriate CAE solution.

The recent advances in digital technologies like IoT, Big Data, AI, and Digital Twin have brought new opportunities for the hybrid approach. By enriching the Predictive Virtual Protype with data reflecting real-life behaviour, resulting in a live, evolving Hybrid Twin, continually updated with the latter’s measured characteristics, due to operational changes, and health status (degradation, accident, maintenance, repair, upgrade ..). This leads to higher fidelity models, taking account of uncertainty (material changes, etc. ) and ignorance (unknown factors,…) , with the ability to predict future events, which have not yet occurred.

A Parametric Reduced Model enables the Hybrid Twin to answer the need for real-time response applications. It will allows for analyzing and understanding the cause and effect of early weak signals of potential problems, assessing possibilities, validating possible correction measures, and evaluating the improvement and necessary adjustments for optimal outcomes: Performance and Quality.

Early pilot projects are already demonstrating the feasibility of such a solution and showing manufacturers how the simulation capabilities will be adapted and streamlined to be implemented right at the heart of factories ─ with very encouraging outcomes.