Rapid recOnfiguration of manufacturing systems: a model-baseD software engineering and human Interaction Coupled approach – RODIC
Rapid recOnfiguration of manufacturing systems: a model-baseD software engineering and human Interaction Coupled approach
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Challenges and objectives
Reconfigurable manufacturing systems (RMS) are currently considered one of the most promising avenues for business adaptability in the face of significant uncertainty. The underlying idea is to be able to modify both the physical structure and the structure of the RMS's control system to enable it to adapt to changes in its environment or objectives. To this end, RMSs are designed in a modular form, a configuration corresponding to an assembly of modules, software, or hardware. Choosing a configuration is not easy: there are multiple variants, numerous parameters to consider, and the context requires rapid decision-making. The RODIC project aims to develop a tool that allows an operator in charge of reconfiguration to more simply and quickly evaluate the configurations they wish to test. The main strength of the project is to successfully cross three distinct scientific disciplines: cognitive psychology for the analysis of the operator's activity and the definition of the interaction to be set up with the tool, industrial engineering for the contextualization of the work, the design of configurations and the definition of performance indicators with respect to the enterprise architecture, and software engineering for the verification, generation and evaluation phases of the proposed configurations. This tool will be tested on real industrial cases.
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Le résultat majeur attendu dans le projet RODIC est un logiciel, adaptable à la situation industrielle de reconfiguration, permettant à tout opérateur d’évaluer la performance d’une nouvelle configuration de l’outil de production. Ce résultat pourra être obtenu grâce à la levée de trois verrous scientifiques provenant de trois communautés scientifiques distinctes. Tout d’abord, une analyse d’activité en situation industrielle va permettre de spécifier et formaliser les processus cognitifs menant à la prise de décision des opérateurs de reconfiguration en précisant les données nécessaires ainsi que leur format d’affichage pour une meilleure interaction. Ensuite, l’outil s’appuiera sur une spécification générique des systèmes de production reconfigurables, modélisée sur la base de la théorie des langages, pour permettre à l’opérateur non-informaticien de caractériser la configuration à tester au plus près des besoins métiers. Enfin, à contre-pied des outils de simulation industrielle classiques, l’évaluation des indicateurs de performance de chaque configuration réalisée par l’outil RODIC le sera en utilisant des techniques éprouvées issues du génie logiciel, dans un objectif de rapidité et de simplicité de mise en œuvre.
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Aprilia Andari, S.; Cardin, O.; Berruet, P.; Ardi, R. Serious Game as Learning Media for Reconfigurable Manufacturing System: A Model Development. 10th IFAC Conference on Manufacturing Modelling, Management and Control MIM, Nantes. 2022, 1675–1680.
André, P.; Cardin, O. A Core Reference Model for Applicable Reconfigurable Manufacturing Systems. Service Oriented, Holonic and Multi–Agent Manufacturing Systems for Industry of the Future. Springer Nature. 2024, 507–519. Studies in Computational Intelligence.
Ajabri, H.; Mottu, J.-M.; Bousse, E. Defining KPIs for Executable DSLs: A Manufacturing System Case Study. 12th International Conference on Model–Based Software and Systems Engineering MODELSWARD, Rome. 2024, 169–178.
André, P.; Goepp, V. A Framework for Defining Customised KPI in Manufacturing Systems. Service Oriented, Holonic and Multi–Agent Manufacturing Systems for Industry of the Future. Springer Nature. 2024, 309–320. Studies in Computational Intelligence.
Reconfigurable Manufacturing Systems (RMS) are currently considered as one of the most promising ways to make companies more adaptable to strong uncertainties. The main idea of RMS is to modify both the physical structure and the structure of the control system of a manufacturing system in order to allow it to adapt to an evolution of its environment or its objectives. To achieve this result, manufacturing systems must be designed in a modular form, and a configuration therefore corresponds to an assembly of these modules, whether they are software or hardware. Several successive phases are carried out during a reconfiguration: (i) detection of the need for reconfiguration, (ii) design of alternative configurations, (iii) choice of the configuration to be applied, (iv)production stop, (v) reconfiguration, and finally (vi) production restart.
The RODIC project aims at improving this process by proposing a tool allowing an operator in charge of the reconfiguration to evaluate more simply and quickly the configurations he wants to test (phase iii). The main strength of the RODIC project is to succeed in crossing three distinct scientific disciplines: cognitive psychology for the cognitive analysis of the operator's activity and the definition of the interaction to be set up with the tool, industrial engineering for the contextualization of the work, the design of the configurations and the definition of the performance indicators with respect to the enterprise architecture, and software engineering for the phase of verification, generation and evaluation of the proposed configurations.
The originality of the RODIC project is multiple: to succeed in proposing an instantiable model of a production system configuration, to allow the generation of a frugal and intelligent control system (as opposed to the current monolithic systems restricting the performances of the system by limiting the perimeter of the authorized configurations), to propose a set of targeted evaluation tools (as opposed to the traditional omniscient flow simulation models, which are cumbersome and time-consuming to develop), and to adjust this cycle as closely as possible to the expectations of the users in production situations.
The tool proposed in the RODIC project can be decomposed in five sections globally successive: the operator, through a first interface, will be able to choose, associate and parameterize a set of predefined modules in order to create his configuration. A model of the configuration will then be processed by Model-Based Software Engineering (MBSE) techniques in order to verify the consistency of the configuration and its compliance with the constraints of the enterprise architecture. A set of evaluation models will then be generated and used in a validation phase of the configuration against the expected performance indicators. These results are then displayed on a second interface in a form that allows the results to be explained, in order to facilitate the operator's decision making. When the configuration is validated, the configuration control system software is generated and ready to be applied on the real system.
The RODIC project will develop two complementary application cases. First, a virtual industrial case will be proposed, dealing with mostly automated systems, allowing to demonstrate the qualities of the tool on industrially validated performance indicators. A second case will be developed within a Teaching Factory on a totally manual system. The developments will be permanently integrated in the Teaching Factory in order to make it a showcase of the project.
Project coordination
Olivier Cardin (Laboratoire des Sciences du Numérique de Nantes)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partnership
ICube Laboratoire des sciences de l'Ingénieur, de l'Informatique et de l'Imagerie (UMR 7357)
LS2N Laboratoire des Sciences du Numérique de Nantes
LAB-STICC Laboratoire des Sciences et Techniques de l'Information, de la Communication et de la Connaissance
Help of the ANR 497,195 euros
Beginning and duration of the scientific project:
February 2022
- 48 Months