https://sam.ensam.eu:443 The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material. Thu, 12 Mar 2026 23:23:39 GMT 2026-03-12T23:23:39Z http://hdl.handle.net/10985/23884 Development and analysis of a holistic function-driven adaptive assembly strategy applied to micro gears KHEZRI, Amirhossein; SCHILLER, Vivian; HOMRI, Lazhar; ETIENNE, Alain; DANTAN, Jean-Yves; LANZA, Gisela The precision and functionality of an assembly heavily depend on the dimensions of its components, which can often lead to quality issues. However, increasing precision can be expensive and impractical. Alternative methods, such as adaptive assembly and optimization, can help achieve high-precision assemblies using less precise components. Adaptive assembly involves adjusting the assembly process to account for component variations, which can improve accuracy and reduce errors. Optimization techniques can be used to identify the most efficient and effective assembly strategy for a given set of components, taking into consideration factors such as complexity, volume, cost, and quality. This paper proposes an exclusive adaptive assembly strategy for micro gear pairing by evaluating and comparing different assembly strategies. Manufacturers can determine the best fit for their specific needs and enhance the precision and functionality of their assemblies. Tue, 01 Aug 2023 00:00:00 GMT http://hdl.handle.net/10985/23884 2023-08-01T00:00:00Z KHEZRI, Amirhossein SCHILLER, Vivian HOMRI, Lazhar ETIENNE, Alain DANTAN, Jean-Yves LANZA, Gisela The precision and functionality of an assembly heavily depend on the dimensions of its components, which can often lead to quality issues. However, increasing precision can be expensive and impractical. Alternative methods, such as adaptive assembly and optimization, can help achieve high-precision assemblies using less precise components. Adaptive assembly involves adjusting the assembly process to account for component variations, which can improve accuracy and reduce errors. Optimization techniques can be used to identify the most efficient and effective assembly strategy for a given set of components, taking into consideration factors such as complexity, volume, cost, and quality. This paper proposes an exclusive adaptive assembly strategy for micro gear pairing by evaluating and comparing different assembly strategies. Manufacturers can determine the best fit for their specific needs and enhance the precision and functionality of their assemblies. http://hdl.handle.net/10985/23885 Evolutionary Cost-Tolerance Optimization for Complex Assembly Mechanisms Via Simulation and Surrogate Modeling Approaches: Application on Micro Gears KHEZRI, Amirhossein; SCHILLER, Vivian; GOKA, Edoh; HOMRI, Lazhar; ETIENNE, Alain; STAMER, Florian; DANTAN, Jean-Yves; LANZA, Gisela With the introduction of new technologies, the scope of miniaturization has broadened. The conditions under which complicated products are designed, manufactured, and assembled ultimately influence how well they perform. The intricacy and crucial functionality of products are frequently only fulfilled through the use of high-precision components such as micro gears. In power transmission systems, gears are used in a variety of industries. Micro gears or gears with micro features, with tolerances of less than 5 m, are pushing manufacturing processes to their technological limits. Monte-Carlo simulation methods enable an accurate forecast of inaccuracies in compliance. The complexity of the micro gear's design, on the other hand, increases the simulation computation and runtime. An alternative method for simulation is to create a surrogate model to predict the behavior. This paper proposes a statistical surrogate model to predict the conformity of a pair of micro gears. Afterward, the advantage of the surrogate model enables the optimal tolerances assignment while taking gear functionality, and production cost into account. Sun, 01 Jan 2023 00:00:00 GMT http://hdl.handle.net/10985/23885 2023-01-01T00:00:00Z KHEZRI, Amirhossein SCHILLER, Vivian GOKA, Edoh HOMRI, Lazhar ETIENNE, Alain STAMER, Florian DANTAN, Jean-Yves LANZA, Gisela With the introduction of new technologies, the scope of miniaturization has broadened. The conditions under which complicated products are designed, manufactured, and assembled ultimately influence how well they perform. The intricacy and crucial functionality of products are frequently only fulfilled through the use of high-precision components such as micro gears. In power transmission systems, gears are used in a variety of industries. Micro gears or gears with micro features, with tolerances of less than 5 m, are pushing manufacturing processes to their technological limits. Monte-Carlo simulation methods enable an accurate forecast of inaccuracies in compliance. The complexity of the micro gear's design, on the other hand, increases the simulation computation and runtime. An alternative method for simulation is to create a surrogate model to predict the behavior. This paper proposes a statistical surrogate model to predict the conformity of a pair of micro gears. Afterward, the advantage of the surrogate model enables the optimal tolerances assignment while taking gear functionality, and production cost into account. http://hdl.handle.net/10985/23863 A Framework for Integration of Resource Allocation and Reworking Concept into Design Optimisation Problem KHEZRI, Amirhossein; HOMRI, Lazhar; ETIENNE, Alain; DANTAN, Jean-Yves; LANZA, Gisela The life cycle of an assembled product faces various uncertainties considering the current state of the manufacturing line. Varied of activities are integrated with the manufacturing line including processing, inspection, reworking, assembly, etc. Therefore, any decision taken concerning each activity, will affect the end-product of the manufacturing line. In an early stage, designers define tolerances on parts to ensure the functionality of the end-product. In this regard, this paper integrates resource allocation (as a decision to assign practical resources to parts) and reworking decision (as a decision to improve parts conformity rate) into the tolerance allocation problem. A modular-based cost modelling approach is proposed objecting to minimisation of manufacturing cost concerning resource allocation and reworking decisions. Eventually, a genetic algorithm and Monte-Carlo simulation are adapted to analyse the applicability of the model. Sat, 01 Jan 2022 00:00:00 GMT http://hdl.handle.net/10985/23863 2022-01-01T00:00:00Z KHEZRI, Amirhossein HOMRI, Lazhar ETIENNE, Alain DANTAN, Jean-Yves LANZA, Gisela The life cycle of an assembled product faces various uncertainties considering the current state of the manufacturing line. Varied of activities are integrated with the manufacturing line including processing, inspection, reworking, assembly, etc. Therefore, any decision taken concerning each activity, will affect the end-product of the manufacturing line. In an early stage, designers define tolerances on parts to ensure the functionality of the end-product. In this regard, this paper integrates resource allocation (as a decision to assign practical resources to parts) and reworking decision (as a decision to improve parts conformity rate) into the tolerance allocation problem. A modular-based cost modelling approach is proposed objecting to minimisation of manufacturing cost concerning resource allocation and reworking decisions. Eventually, a genetic algorithm and Monte-Carlo simulation are adapted to analyse the applicability of the model.