Integrating optimal process and supplier selection in personalised product architecture design

Abstract

A key enabler for personalised product design is an open product architecture that allows the integration of personalised modules to create unique products. Decisions regarding product variety, module combinations, and configurations for personalised modules need to be coordinated with the decisions of manufacturing process and supplier selection when developing personalised product architectures. Conventionally, product architecture, processes, and suppliers are independently determined at different product development stages. However, this sequential design process lacks connection between product architecture, process, and supplier, and may lead to suboptimal or even infeasible design solutions with compromised performance. In this study, a concurrent optimisation approach is proposed to integrate manufacturing process and supplier selection into personalised product architecture design. A cost model is developed as a nexus of product architecture, process, and supplier. Then, a mixed-integer optimisation model is established to maximise the potential profit of a product family based on a profit formulation that incorporates customer preference, process resource, supplier, and manufacturing cost. A genetic algorithm is utilised to solve this optimisation problem. The method is demonstrated on the architecture design for a family of personalised bicycles. The result shows that concurrent optimisation can achieve design solutions with higher profitability compared to sequential design strategies.

KEYWORDS:

• Personalisation
• product architecture
• concurrent engineering
• process planning
• supply chain coordination
• customer preference

Disclosure statement

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

Additional information

Funding

This work was financially supported by the National Science Foundation [grant number CMMI-1547091].

Notes on contributors

Changbai Tan

Changbai Tan received the D.Eng. degree in manufacturing engineering in 2020 from the University of Michigan at Ann Arbor, MI, USA. He also received the B.Eng. degree in mechanical engineering, and M.Eng. and D.Eng. degrees in aerospace engineering from the Nanjing University of Aeronautics and Astronautics at Nanjing, Jiangsu, China, where he had worked as a faculty member in the area of digital design and manufacturing for eight years. As a research assistant at the University of Michigan, Changbai’s current research interests include product personalisation, cyber-physical systems, and machine learning applications in design and manufacturing.

Kira Barton

Kira Barton is an Associate Professor in the Department of Mechanical Engineering and a core faculty member in the Robotics Institute at the University of Michigan. She received her B.Sc. in Mechanical Engineering from the University of Colorado at Boulder in 2001. She continued her education in mechanical engineering at the University of Illinois at Urbana-Champaign and completed her MSc and PhD degrees in 2006 and 2010, respectively. In 2011, she joined the Mechanical Engineering Department at the University of Michigan at Ann Arbor. Kira conducts research in modelling, sensing, and control for applications in advanced manufacturing and robotics, with a specialisation in learning control and additive manufacturing.

S. Jack Hu

S. Jack Hu is the UGA Foundation Distinguished Professor of Engineering at the University of Georgia. Prior to his current appointment, he was the J. Reid and Polly Anderson Professor of Manufacturing, Professor of Mechanical Engineering, and Professor of Industrial and Operations Engineering at the University of Michigan. Dr. Hu has authored or co-authored nearly 200 peer-reviewed journal articles related to his research in manufacturing systems, assembly, and materials joining. He is a Fellow of the American Society of Mechanical Engineers, the Society of Manufacturing Engineers, and the International Academy for Production Engineering (CIRP).

Theodor Freiheit

Theodor Freiheit is a Research Associate Professor in the Department of Mechanical Engineering at the University of Michigan. He received his MBA in 1995 and his PhD in 2003 from the University of Michigan. Prior to his current appointment, he was an Associate Professor at the Department of Mechanical and Manufacturing Engineering at the University of Calgary. His expertise is in product and manufacturing system design, design theory and methodology, scheduling and control of management and service systems, engineering management, and testing.