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Obsolescence and shortages have a strong impact on all value chains today. They can be found in all areas. They have an impact on both consumers and manufacturers. They can affect all components, products, systems, etc. Facing these two phenomena, ABMI, a multi-specialty engineering company, proposes despecialization as a solution. It allows components to be remanufactured and upgraded without the original supplier's specifications in case of obsolescence or shortage. This despecialization generally makes the system more resilient and robust. However, when despecialization is carried out to address obsolescence and shortages, different sets of consequences may arise. The improvements made to one component may, for example, degrade the performance of certain functions, or they may change the behavior of other components, or even change the properties of the system, i.e. reliability, maintainability, and availability. All these changes are the result of the propagation of the consequences of obsolescence and shortages. It is therefore essential to study the dependencies, especially between components, in any despecialization action to ensure the proper functioning of the system and its sustainability over time. In this paper, certain dependencies are studied in a case study of a mechanical system. We use Bayesian network theory to explore the modeled dependencies. The objective is to show the propagation of the effects of architectural changes on the resilience of the redesigned or despecialized product. The paper concluded with conclusions and perspectives on future research undertaken. [ABSTRACT FROM AUTHOR]

Throughout its life cycle, systems undergo several modifications in their architecture. These changes target at remaining competitive and responding quickly to new customer requirements. However, any entity change (i.e. component, function or functionality) can produce unexpected consequences, propagated throughout the whole system architecture. It is then necessary to model, predict and control them. System engineering tools and techniques allow dealing with complex systems design. That is why we have developed a novel methodology to analyze changes using a system engineering methodology called ARCADIA, developed by Thales and its associated software Capella. The obtained models allow mapping various kinds of dependencies within a system architecture. The method, presented in this paper, shows how these models are used to integrate change propagation and transform them into Bayesian networks. A set of experiments allows then to obtain insightful pieces of knowledge about the changes propagation. An illustrative case is developed with a focus of particular changes caused by obsolescence of component, function or functionality. [ABSTRACT FROM AUTHOR]

Engineering Changes (EC) are often the answers the designers think of while dealing with new performance targets or customers needs and expectations, regarding functionality, aesthetics, security, etc. Engineering change management (ECM) techniques look to predict or control these consequences within an existing system or product, to limit the generated cost and required efforts to integrate such changes. Engineering change management (ECM) techniques look to predict or control these consequences within an existing system or product, to limit the generated cost and required efforts to integrate such changes. This paper addresses the issue of enhancing the ability of the ”change evaluation” through the suggested technique. We propose a methodology that covers change analysis and evaluation from change’s objective initialization to formulation of recommendation based on system engineering framework (ANSI/EIA-649 1998). We use a modeling technique based on influence diagrams able to integrate different uncertainty levels (on dependencies) in a unique model. It will be shown that the models offer the ability to analyze change impacts but also allow to synthesize the system. Finally, these results can be obtained in a very efficient way which gives the possibility of their use during a design meeting in a practical way at the very beginning of a change project and mainly to support go/no-go decision. [ABSTRACT FROM AUTHOR]