Configuring products using NSGA-II: warranty profits, performance–price, and environmental emissions from the contractor perspective

Abstract

In the context of mass customization business activities, product configuration (PC) can assist companies in quickly occupying the market and improving their competitive advantage. In this paper, contractors are defined as outsourcing companies for producers and manufacturers that do not possess self-developed product module technology and who are more knowledgeable and discerning consumer representatives. This study focused on a PC approach that includes optional, redundant, and common modules. In this approach, three objective functions were considered and solved using NSGA-II: warranty profit, performance-price, and environmental emissions. Warranty profit is calculated by forcing the product failure probability to satisfy a power-law distribution and the user selection behavior to satisfy a multinomial logit (MNL) model. Kano’s model-based user satisfaction and the relative importance of the product module instance are used to calculate performance-price. The environmental emissions were determined from both production and assembly emissions of the module instance. Additionally, a chromosome encoding method and a chromosome crossover operation were designed for the PC problem. Finally, the feasibility and effectiveness of the proposed method were verified by taking an electric vehicle DC charging pile configuration project as an example, and discussing and explaining the practical significance of each parameter in the example.

KEYWORDS:

• NSGA-II
• product configuration
• warranty profit
• kano model
• electric vehicle charging pile

Acknowledgments

The authors would like to thank Keda Intelligent Technology Co., Ltd. (Hefei City, Anhui Province, China) for supporting some of the data in this study. We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work has been funded by the National Key R&D Program in China  (2019YFC1908005 ).