Product families are frequently used to provide consumers with a variety of appealing products and to help maintain reasonably low production costs for manufacturers. Three common objectives in the design of product families are used to balance the interests of both consumers and manufacturers. These objectives are to maximize (i) product performance, (ii) product distinctiveness as perceived by the consumer, and (iii) product commonality as seen by the manufacturer. In this thesis, three methods are introduced that use multiobjective optimization and Smart Pareto filtering to satisfy the three objectives of product family design. The methods are progressive in nature and begin with the selection of product family members using Smart filtering and develop through the establishment of scale- based product platforms to the design of combined scale- based and module-based product platforms. Each of the methods is demonstrated using a well-know universal electric motor example problem. The results of each method are then compared to a benchmark electric motor product family that was previously defined in the literature. Additionally, a pressure vessel example problem is used to further demonstrate the first of the three methods.

En adoptant un point de vue utilitariste du consommateur sur certains produits orientés service, nous avons d'abord contribué à la proposition d’un modèle de contextes d’usage que se doit de couvrir au mieux un produit. Le modèle conduit à une meilleure intégration des analyses de marketing et d’ingénierie de la conception amenant à une optimisation d'un produit paramétré plus orientée vers les besoins du marché ou à un meilleur étagement d'une famille de produits. Nous proposons une série d'indices qui révèlent l'adéquation entre les usages couverts par un produit de dimensions données ou une famille de produits donnée avec un espace d'usages cible qu’il s’agit de couvrir dans sa totalité ou en partie mais d'une manière suffisamment dominante par rapport à la concurrence. En premier lieu, l'indice de couverture d’usage (UCI) pour un produit unique est introduit par la cartographie du produit relativement à un ensemble d’utilisateurs représentatifs définis par des usages attendus. Sur cette base, l'UCI pour une famille de produits est construite pour évaluer la composition de la famille et la redondance des produits qui la composent. Les avantages par rapport à la traditionnelle estimation de la demande en marketing sont de réduire la complexité de l'enquête et de l'analyse des données et de pouvoir estimer le niveau de compétitivité d’une offre innovante sans nécessiter de retour d’expérience du marché. Nous expérimentons nos propositions sur un problème de reconception d’une famille de scies sauteuses. L'approche proposée permet d'évaluer l'adaptabilité, pour une famille de produits de tailles croissantes, à divers scénarios dans le contexte d'usage d'un marché cible. Les concepteurs peuvent s'appuyer sur les résultats pour éliminer les produits redondants au sein d'une famille. Des configurations de produits de tailles croissantes peuvent aussi être rapidement simulées et comparées de manière à aboutir à une famille minimale de produits idéalement étagée. / Adopting a utilitarian viewpoint of consumers on some service-oriented goods, we have first contributed to the proposal of a usage contexts model that a product should cover at most. The model leads to a higher integration of design engineering and marketing analyses which results in a more market-oriented optimization of a parameterized product or a better sampling of a product family. We propose a series of usage coverage indices that reveal the adequacy of a dimensioned product or a given product family to a targeted usage space to cover in its whole or for a part but sufficiently in a dominant way compared to competing products. First, the Usage Coverage Index (UCI) for single product is introduced by mapping the given product with a set of representative users defined by expected usages. On that basis, the UCI for a product family is constructed to evaluate the composition and redundancy of the family. The advantage compared to traditional demand estimation in marketing research is to reduce the complexity of survey and data analysis and to assess the competitiveness level of an innovative service offer without needing any return of experience from the market. We experiment our proposals on a jigsaw product family redesign problem. The proposed analysis approach helps to evaluate the adaptability, for a given scale-based product family, to diverse usage context scenarios in a target market. Designers can rely on the results to filter out redundant products within a family. Scale-based configurations of the products can also be rapidly simulated and compared to find out an appropriate sampled series of products.

Many companies are using platform-based product designs to fulfill the requirements of customers while maintaining low cost. However, research that integrates sustainability into platform-based product design is still limited. Considering sustainability during platform-based design process is a challenge because the total life-cycle from pre-manufacturing, manufacturing and use to post-use stages as well as economic, environmental and societal performance in these stages must be considered. In this research, an approach for quantifying sustainability is introduced and a mathematical model is developed for identifying a more sustainable platform. Data from life-cycle assessment is used to quantify environmental factors; criteria from the Product Sustainability Index (ProdSI) are used to quantify societal factors. The Analytic Hierarchical Process method is used to assess relative importance of societal factors and the weighted sum method is used in the objective function for overall multi-objective optimization. A bicycle platform configuration will be used as a case study to demonstrate the application of the model. The relationship between commonality of the platform and sustainability performance is analyzed.