Lean six sigma applied to process performance and improvement model for the development of electric scooter water-cooling green motor assembly

Wang, C.; Chen, K.; Tan, Kim

Abstract

In response to the environmental issues triggered by global warming, worldwide companies gradually put the factor of carbon emission into the process of product life cycle, developing green technology or adopting cleaner production aimed at sustainable development. Lean Six Sigma has advantages of cutting waste and facilitating process improvements as well as system analysis, helping enterprises create the overall business benefits in the value chain. Used in the renewable energy industry, it can promote the Triple Bottom Line (TBL), the performance of sustainable production for corporate profit, social responsibility, and environmental responsibility. Therefore, this study took the process performance of the electric scooter water-cooling green motor manufactured in Taiwan with the world’s highest density of scooters as a case study. The developed performance evaluation and improvement model for manufacturing scheduling and process quality achieved the goal of economic benefits of enhancing process quality performance by shortening manufacturing scheduling and reducing process variations with Lean Six Sigma. 2 Besides, they could respond to the policy of energy saving and carbon reduction - replacing the traditional scooters of high carbon emissions with the electric scooters of low emissions. Furthermore, they could bring enterprises into harmony with economic benefits, ecological benefits, and social benefits.

Citation

Wang, C., Chen, K., & Tan, K. (2019). Lean six sigma applied to process performance and improvement model for the development of electric scooter water-cooling green motor assembly. Production Planning and Control, 30(5-6), 400-412. https://doi.org/10.1080/09537287.2018.1501810

• Journal Article Type: Article
• Acceptance Date: Jul 7, 2018
• Online Publication Date: May 10, 2019
• Publication Date: May 10, 2019
• Deposit Date: Sep 26, 2018
• Publicly Available Date: May 11, 2020
• Journal: Production Planning & Control
• Print ISSN: 0953-7287
• Electronic ISSN: 1366-5871
• Publisher: Taylor and Francis
• Peer Reviewed: Peer Reviewed
• Volume: 30
• Issue: 5-6
• Pages: 400-412
• DOI: https://doi.org/10.1080/09537287.2018.1501810
• Keywords: Management Science and Operations Research; Strategy and Management; Industrial and Manufacturing Engineering; Computer Science Applications
• Public URL: https://nottingham-repository.worktribe.com/output/1133493
• Publisher URL: https://www.tandfonline.com/doi/abs/10.1080/09537287.2018.1501810
• Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in Production & Planning Control on 09.05.2019, available online: http://www.tandfonline.com/10.1080/09537287.2018.1501810
• Contract Date: Sep 26, 2018