Assessing Variable Levels of Platform Commonality Within a Product Family Using a Multiobjective Genetic Algorithm

Abstract

Many companies are using product families and platform-based product development to reduce development costs and lead-time while increasing product variety and customization. Multiobjective optimization is experiencing new found use in the field of product family design to facilitate product platform design and help resolve the inherent tradeoff between commonality and distinctiveness that exists within a product family. After discussing the uses of multiobjective optimization in product family design and the limitations of current approaches, we introduce a genetic algorithm-based approach for product family design that has been developed to overcome these challenges. The proposed genetic algorithm (GA) modifications enable it to simultaneously design the product platform and its corresponding family of products while considering varying levels of platform commonality within the product family. The effectiveness of the proposed approach is demonstrated through the design of a family of General Aviation Aircraft and comparison against previous results. The impact of seeding the proposed GA with two product families, one with all products common and one with all products unique, is studied and shown to yield a richer Pareto set in fewer generations.