In today's business environment, the trend towards more product variety and customization is unbroken. Due to this development, the need of agile and reconfigurable production systems emerged to cope with various products and product families. To design and optimize production systems as well as to choose the optimal product matches, product analysis methods are needed. Indeed, most of the known methods aim to analyze a product or one product family on the physical level. Different product

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... ies, however, may differ largely in terms of the number and nature of components. This fact impedes an efficient comparison and choice of appropriate product family combinations for the production system. A new methodology is proposed to analyze existing products in view of their functional and physical architecture. The aim is to cluster these products in new assembly oriented product families for the optimization of existing assembly lines and the creation of future reconfigurable assembly systems. Based on Datum Flow Chain, the physical structure of the products is analyzed. Functional subassemblies are identified, and a functional analysis is performed. Moreover, a hybrid functional and physical architecture graph (HyFPAG) is the output which depicts the similarity between product families by providing design support to both, production system planners and product designers. An illustrative example of a nail-clipper is used to explain the proposed methodology. An industrial case study on two product families of steering columns of thyssenkrupp Presta France is then carried out to give a first industrial evaluation of the proposed approach. Abstract Induction hardening has the potential to produce favorable surface integrity that can improve fatigue performance and extend the lifetime of a component. The localized superficial heating provided by induction is the main advantage of this process, as it allows the core to remain intact and, therefore, ductile, while the surface is hardened. Achieving favorable characteristics in the hardened case is of great importance, as this process is usually applied to load bearing and wear-susceptible metallic components. The simulation of the hardening process by induction heating is a complex and challenging task at which many efforts have been directed in the last years. Due to the numerous interactions of the many physics that take part in the process (electromagnetic, thermal, microstructural and mechanical), a highly coupled finite element model is required for its numerical simulation. In this work, a semi-analytical induction heating model is used to compute the induction hardening process, predicting the size and shape of the hardened layer and the distribution of the hardness. Using the semi-analytical model allows the computational time to be much faster compared to a fully coupled model using a commercial software, where the time consumption for the presented 2D case is reduced by 20 %. Experimental validation is presented for cylindrical 42CrMo4 billets heated by a short solenoidal inductor, which shows good agreement with the predicted results, reaching an average error of 3.2 % in temperature estimations. Abstract Induction hardening has the potential to produce favorable surface integrity that can improve fatigue performance and extend the lifetime of a component. The localized superficial heating provided by induction is the main advantage of this process, as it allows the core to remain intact and, therefore, ductile, while the surface is hardened. Achieving favorable characteristics in the hardened case is of great importance, as this process is usually applied to load bearing and wear-susceptible metallic components. The simulation of the hardening process by induction heating is a complex and challenging task at which many efforts have been directed in the last years. Due to the numerous interactions of the many physics that take part in the process (electromagnetic, thermal, microstructural and mechanical), a highly coupled finite element model is required for its numerical simulation. In this work, a semi-analytical induction heating model is used to compute the induction hardening process, predicting the size and shape of the hardened layer and the distribution of the hardness. Using the semi-analytical model allows the computational time to be much faster compared to a fully coupled model using a commercial software, where the time consumption for the presented 2D case is reduced by 20 %. Experimental validation is presented for cylindrical 42CrMo4 billets heated by a short solenoidal inductor, which shows good agreement with the predicted results, reaching an average error of 3.2 % in temperature estimations.