A joint optimization strategy for scale-based product family positioning

Abstract

With the development of modern technologies and global manufacturing, it becomes more difficult for companies to distinguish themselves from their competitors. In order to keep their competitive advantages, companies must properly position their product families by offering a right product portfolio to each target market. To evaluate competitive advantages for a scale-based product family, this paper takes product family competitive advantage (PFCA) as a measure metric which is consisted of customer choice probability, sales, and profit. Meanwhile, to keep lower manufacturing costs, a commonality index of scale-based product family is proposed based on product design technology parameters in a product family. A multi-objective joint optimization model that balances the competitive advantages and the commonality is proposed. Based on a case study of motor product family positioning, Pareto frontier solutions are generated by genetic algorithm, and the results show that the joint optimization model excels in supporting product family positioning.

Keywords

• Scale-based product family
• product portfolio
• product family positioning
• joint optimization