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Study of a discrete grey forecasting model based on the quality cost characteristic curve

Wenjie Dong (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Sifeng Liu (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Zhigeng Fang (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Xiaoyu Yang (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Qian Hu (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Liangyan Tao (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China)

Grey Systems: Theory and Application

ISSN: 2043-9377

Article publication date: 6 November 2017

193

Abstract

Purpose

The purpose of this paper is to clarify several commonly used quality cost models based on Juran’s characteristic curve. Through mathematical deduction, the lowest point of quality cost and the lowest level of quality level (often depicted by qualification rate) can be obtained. This paper also aims to introduce a new prediction model, namely discrete grey model (DGM), to forecast the changing trend of quality cost.

Design/methodology/approach

This paper comes to the conclusion by means of mathematical deduction. To make it more clear, the authors get the lowest quality level and the lowest quality cost by taking the derivative of the equation of quality cost and quality level. By introducing the weakening buffer operator, the authors can significantly improve the prediction accuracy of DGM.

Findings

This paper demonstrates that DGM can be used to forecast quality cost based on Juran’s cost characteristic curve, especially when the authors do not have much information or the sample capacity is rather small. When operated by practical weakening buffer operator, the randomness of time series can be obviously weakened and the prediction accuracy can be significantly improved.

Practical implications

This paper uses a real case from a literature to verify the validity of discrete grey forecasting model, getting the conclusion that there is a certain degree of feasibility and rationality of DGM to forecast the variation tendency of quality cost.

Originality/value

This paper perfects the theory of quality cost based on Juran’s characteristic curve and expands the scope of application of grey system theory.

Keywords

Acknowledgements

The relevant research done for this paper has been supported by the Marie Curie International Incoming Fellowship within the European Union’s Seventh Framework Programme for Research and Technological Development (Grant No. FP7-PIIF-GA-2013-629051), the National Natural Science Foundation of China (No. 71671091), the Open Fund of Postgraduate Innovation Base (Laboratory) at the Nanjing University of Aeronautics and Astronautics (No. kfjj20170906) and the Postgraduate Research and Practice Innovation Program of Jiangsu province. The authors are grateful to two anonymous reviewers for their comments during the review process. In addition, the authors want to thank Regional Associate Editor Naiming Xie and Dr Ye Chen for their selfless help.

Citation

Dong, W., Liu, S., Fang, Z., Yang, X., Hu, Q. and Tao, L. (2017), "Study of a discrete grey forecasting model based on the quality cost characteristic curve", Grey Systems: Theory and Application, Vol. 7 No. 3, pp. 376-384. https://doi.org/10.1108/GS-06-2017-0016

Publisher

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Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

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