An improved multiple quality characteristic analysis chart for simultaneous monitoring of process mean and variance of steering knuckle pin for green manufacturing

Abstract

To solve the problems of overconsumption and the increasing environmental pollution brought by rapid industrial development, governments around the world have been introducing a series of green manufacturing (GM) policies to reduce the negative effects of manufacturing. A high-quality product means less time wasted on interruptions and restarts in the production process as well as less waste and defective products. However, once the quality of the product reaches a certain level (e.g., five Sigma), it becomes harder to attain greater economic and environmental benefits. Clearly, both excessive and inadequate quality exert a profound impact on corporations, society, and the environment. This study presents an improved Q_pm multiple quality characteristic analysis chart (Q_pm MQCAC) to ensure that product quality meets a specified standard with minimum input. Quality optimization is used to improve quality characteristics which do not meet the standard by joint monitoring of possible shifts in the process mean µ and/or process standard deviation σ. A guide is also provided to ensure successful quality improvement. The proposed approach not only identifies the factors that influence production quality, but avoids excessive consumption of resources, thereby achieving GM goals. The proposed approach is demonstrated in a step-by-step manner using the example of a steering knuckle pin. Future works are also discussed.

Keywords:

• green manufacturing
• multiple quality characteristic analysis chart
• process capability index
• Six Sigma quality indices
• steering knuckle pin

Acknowledgments

The author would like to thank the Editor, Marcus Perry, and two anonymous referees for their helpful comments and careful reading, which significantly improved the presentation of this paper.

Additional information

Funding

This work was financially supported by National Natural Science Foundation of China under grant No. 71762008, Quality and Brand Development Research Center in Dongguan University of Technology under Grant No. GB200101, the Guangxi Natural Science Foundation Youth Project of China under Grant No. 2019GXNSFBA245060, and Foundation of College’s Key Research base on Humanities and Social Science in Guangdong Province, China: Pearl River Delta Industrial Ecology Research Center under Grant No. 2016WZJD005.

Notes on contributors

Chun-Ming Yang

Chun-Ming Yang received the Ph.D. degree in management sciences from Tamkang University, Taiwan, in 2015. From 2016 to 2019, he worked at Business School, Guilin University of Technology, China. In 2020, he joined School of Economics and Management in Dongguan University of Technology, China and now serves as an Associate Professor and Discipline Backbone. He has authored or coauthored over 43 research papers in national and international well-reputed journals and conferences, including the Journal of Computational and Applied Mathematics, International Journal of Production Research, Journal of the Chinese Institute of Engineers, Journal of Statistical Computation and Simulation, Journal of Engineering Manufacture, Journal of Testing and Evaluation, IEEE Access, and Applied Sciences-Basel. His research interests mainly include process capability analysis, quality management, supplier selection, Six Sigma, multiple attribute decision making (MADM), and decision-making in quality management.