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 Recent economic developments and the spread of technology are pushing companies toward the provision of complex and innovative Product-Service System (PSS). On the other side, information and communication technologies are enabling the identification of a plethora of PSSs characterized by different levels of integration among products, services and infrastructure. In this context, many companies are experimenting difficulties in selecting the proper PSS to be developed, that is the one that concurrently considers the needs of multiple stakeholders and a good engagement of them in the value creation and engineering process. This paper exploits the Engineering Value Assessment (EVA) method to support the evaluation and the assessment of PSS solutions in a B2C context where the management of multiple stakeholders' perspectives is of utmost relevance. To demonstrate the EVA method applicability, the airport context was selected as an example of system complexity since it involves manifold actors: passengers, airport and airlines. Four different PSSs for the self-drop bag were identified and further analyzed through the EVA method in order to identify which is the best one to be adopted in the studied airport in the north of Italy considering the preferences of the three actors: the passengers, the airport and the airlines. Abstract Recent economic developments and the spread of technology are pushing companies toward the provision of complex and innovative Product-Service System (PSS). On the other side, information and communication technologies are enabling the identification of a plethora of PSSs characterized by different levels of integration among products, services and infrastructure. In this context, many companies are experimenting difficulties in selecting the proper PSS to be developed, that is the one that concurrently considers the needs of multiple stakeholders and a good engagement of them in the value creation and engineering process. This paper exploits the Engineering Value Assessment (EVA) method to support the evaluation and the assessment of PSS solutions in a B2C context where the management of multiple stakeholders' perspectives is of utmost relevance. To demonstrate the EVA method applicability, the airport context was selected as an example of system complexity since it involves manifold actors: passengers, airport and airlines. Four different PSSs for the self-drop bag were identified and further analyzed through the EVA method in order to identify which is the best one to be adopted in the studied airport in the north of Italy considering the preferences of the three actors: the passengers, the airport and the airlines.