ISAE-Supméca (permanents) :

Jean-Yves CHOLEY jean-yves.choley@isae-supmeca.fr Jean-Yves Choley obtained a Master degree in Mechanics and Automation and a Master of Advanced Studies in automated manufacturing from ENS Cachan, France (recently renamed ENS Paris-Saclay). He obtained a Ph.D. degree of Industrial Engineering in 2005 from Ecole Centrale Paris, France (recently renamed CentraleSupélec), related to ISO GPS mechanical tolerancing and 3D metrology. He gained industry operational experience (1986-1988) in systems engineering and quality & reliability at Arianespace company, Kourou (French Guyana), France, working both on ground facilities and satellites launchers Ariane 1 to 4. Professor at ISAE-Supméca, France, responsible of IS2M (Ingénierie des Systèmes Mécatroniques et Multiphysiques) research team of Quartz laboratory, he is in charge of research and teaching activities focusing mainly on tools, languages and methodologies for the collaborative design of complex systems such as mechatronic systems, CPS (Cyber-Physical Systems) and CPPS (Cyber-Physical Production Systems). In the past 10 years, he mainly focused on Model-Based Systems Engineering (MBSE), Model-Based Safety Assessment (MBSA) and the digital twin concept, together with multiphysics modeling for the collaborative design of safety critical mechatronic systems, such as autonomous vehicle and factory of the future production systems (4.0 and 5.0).

Thierno DIALLO thierno.diallo@isae-supmeca.fr Conception et pilotage des systèmes cyberphysiques de production Ordonnancement, Diagnostic à base de données Supervision et Reconfiguration des systèmes de production

Moncef HAMMADI moncef.hammadi@isae-supmeca.fr Associate Professor – HDR ISAE-Supmeca, Saint-Ouen sur Seine, France Laboratoire Quartz/ Mechatronics and Multiphysics Systems Engineering (IS2M) research team

Faïda MHENNI faida.mhenni@isae-supmeca.fr Ingénierie Système basée sur les modèles (MBSE), Sûreté de fonctionnement (MBSA) Intégration et cohérence MBSE-MBSA Collaboration et partage des données de conception

Dr. Ing. HDR (accreditation to supervise research) Olivia PENAS olivia.penas@isae-supmeca.fr Research engineer, Research Deputy Director ISAE-Supmeca, Saint-Ouen sur Seine, France Laboratoire Quartz/ Mechatronics and Multiphysics Systems Engineering (IS2M) research team

Régis PLATEAUX regis.plateaux@isae-supmeca.fr Ingénierie Système basée sur les modèles (MBSE), Conception Agile Modélisation et simulation de Systèmes complexes, mécatroniques et cyber et leurs jumeaux numériques Traçabilité des conceptions et simulations, Cohérence des Topologies et des Interactions

ISAE-Supméca PhD (2023) :

Imane BOUHALI imane.bouhali@isae-supmeca.fr xxx

Grégoire GALISSON gregoire.galisson@isae-supmeca.fr xxx

Dipl.-Ing. Romain DELABEYE romain.delabeye@isae-supmeca.fr PhD student ISAE-Supmeca, Saint-Ouen sur Seine, France Laboratoire Quartz/ VAST-FM & IS2M teams

Imane BOUHALI PhD Research

Abstract

The use of simulation from the beginning of a complex system design project becomes essential to ensure the quality of the proposed solution. However, it is necessary to be able to take into account and couple a heterogeneity of models often associated to different views of a solution in order to verify the performances of the system. The subject of this thesis is to realize a digital twin of the experimental test bench of an aircraft passenger seat developed by Safran Seats. This digital twin must be correlated to the functional and dysfunctional behaviors of the test bench to be able to make improvements of this test bench thanks to the emulation of its environment and the simulation of the digital twin which must remain faithful during the tests on the test bench, under real conditions of use and this by integrating an adaptive model in the digital twin.

Key words 

# Digital twin

# Testbench

# MBSE

# Multiphysics

# Development Cycle

Grégoire Galisson PhD Student 

Abstract

The design of electronic equipment involves different stages of development, from the macroscopic definition of elementary functions to the final qualification test. At these different stages, many critical decisions have to be made. They must be based on an in-depth analysis of all the physical phenomena that govern the operation and life of the product. Simulation allows us to study these phenomena in greater or lesser detail and to improve the designs in relation to them. The numerical models must provide a system and multiphysics vision of the equipment as early as possible in the course of our developments in order to better orientate the design of our products. The objective of the thesis is to set up a methodology for the construction of multiphysics simulations. The objective of the thesis is to set up a methodology for the construction of multiphysics simulations. To answer this problem, two main axes must be treated.  The organisational axis, from the specifications of the system to be modelled and the needs of analysis, a specification of the models are declined (inputs/outputs of the model, functional and environmental fields of application, physics in play, exchange formats between physics, temporal aspects and tools). The modelling axis, the notion of multiphysics modelling implies the coupling between different domains, the coupling of reduced models within a system modelling opens the possibility of a multiphysics system platform.

Keywords

# Multiphysics

# MBSE

#Simulation

# Methodology

# System Engineering

QUARTZ – ISAE-Supméca (FRANCE) 

Suniswell contribution : Scalable Identification, Verification and Validation of Scientific Approaches on Heterogeneous Systems in a Sustainable Manufacturing Context

Abstract

With the ever-increasing complexity of Industry 4.0 systems and factory energy management requirements, energy management systems (EnMS) have drawn much attention in recent years. A trend reinforced by the recent energy crisis. In this context, the EU-funded EnerMan project develops an antonomous and holistic EnMS, or « Energy Digital Twin », extensible to the whole manufacturing industry. This EnMS suffers from the lack of models for the cyber-physical production systems (CPPS) factory pilots operate within their plants. The contribution of this thesis is thus twofold: (i) learning interpretable multiphysics energy models from sensor data, and (ii) develop a methodology to ensure the applicability, extensibility, verification and validation of scientific approaches from laboratory systems to industrial use cases.

Focusing on the latter aspect, an MBSE analysis made it possible to specify and position this research in the context of the project. With 22 academic and industrial project partners spread over 10 countries, this approach allowed to identify interactions between research teams, research topics and techniques, as well as technological building blocks to develop.

Furthermore, verification and validation (V&V) should be thought – from the earliest design phases – as applicable to all targeted use cases (beyond the ones that are the most accessible) and similar applications. In practice, V&V activities encounter multiple difficulties: wide domain of application, low availability of the industrial systems, cost of experiments, time required to implement reliable V&V processes. With a view to cope with these limitations, an automated and scalable V&V process for heterogeneous systems and applications was developed. An ontology was designed to formally represent the use cases and scientific approaches to be validated. This methodology leverages reasoning to assess the extent to which such a scientific approach can be verified on a laboratory system (selected using semantic similarity with respect to the industrial use cases) different from the industrial scenarios on which it must finally be validated. A recommendation system (pinpointing missing components or interactions) was designed to augment the systems so as to increase the degree of validation of the studied scientific approach and its ability to scale to other use cases.  This methodology was extended to assess the applicability of an EnerMan component to an industrial use case. This approach, coined WONKA, has been implemented and tested upon a laboratory system (instrumented automatic coffee machine) and industrial use cases (a vehicle testbed’s heating, ventilation and air conditioning system, and a chocolate production line).

Keywords

# Verification & Validation

# MBSE

# Ontology

# Scalability

# Energy Sustainability

# Heterogeneous Systems

# Knowledge Representation and Reasoning

University of Naples Federico II, Department of Industrial Engineering, Fraunhofer Joint Laboratory IDEAS (Interactive DEsign And Simulation), P.le Tecchio 80, 80125 Naples, Italy

Abstract

The main goal of the PhD research activity is to develop a methodology for the integrated design of on-board hybrid or electric aircraft systems. The methodology will be applied and tested for the design of a Liquid Hydrogen Storage System (LHSS) and its integration in a new regional civil aircraft of 90 seats. The methodology will include processes, methods and tools based on Model Based Systems Engineering (MBSE) approach. In particular, the research activity will focus on the usage of Requirements, Functional, Logical and Physical approach to support the design of the LHSS. Finally, the research activity will integrate the Digital Twin key features into the developed methodology aiming to combine physical systems with digital models through advanced sensors and communication networks.

Keywords

# Model Based Systems Engineering

# Hydrogen Aircraft

# Requirements Traceability

# Integration

# Digital-Twin

University of Naples Federico II, Department of Industrial Engineering, Fraunhofer Joint Laboratory IDEAS (Interactive DEsign And Simulation), P.le Tecchio 80, 80125 Naples, Italy

Abstract

The main goal of the PHD research activity is to investigate the use of data-driven models for energy consumption forecasting in industrial contexts and, at the same time, to find alternative ways of visualising this information that would allow the operator, on the one hand, to be more aware of the energetic aspects, while, on the other hand, to remain in contact with the surrounding environment. In terms of forecasting models, this study focuses on the AI-based approaches, an increasingly common solution, especially for its potential in terms of modelling non-linear problems. It also tries to find a solution to the main problem of black box models, which is the physical interpretation. For the visualization, instead, Augmented reality represents a particularly suitable approach, and the aim is to investigate its potential and limitations both from a functional point of view, such as real-time data visualisation or interactivity, and from an ergonomic point of view, such as cognitive load.

Keywords

# Artificial Intelligence

# Extended Reality

# Energy sustainability 

University of Applied Sciences Upper Austria, Wels, Austria

Abstract

Main Research Questions :

• How strong is the influence of different life cycle phases on the product carbon footprint when alternative powertrain concepts are used?
• What data is required for the carbon footprint calculation of powertrains?
• What possible data sources are available in companies? 

Keywords

# Life Cycle Assessment

# Conceptual Design

# Product development