{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T00:36:25Z","timestamp":1775522185427,"version":"3.50.1"},"reference-count":19,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2017,11,6]],"date-time":"2017-11-06T00:00:00Z","timestamp":1509926400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["GS"],"published-print":{"date-parts":[[2017,11,6]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this paper is to clarify several commonly used quality cost models based on Juran\u2019s 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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>This paper demonstrates that DGM can be used to forecast quality cost based on Juran\u2019s 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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>This paper perfects the theory of quality cost based on Juran\u2019s characteristic curve and expands the scope of application of grey system theory.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/gs-06-2017-0016","type":"journal-article","created":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T07:21:45Z","timestamp":1507879305000},"page":"376-384","source":"Crossref","is-referenced-by-count":9,"title":["Study of a discrete grey forecasting model based on the quality cost characteristic curve"],"prefix":"10.1108","volume":"7","author":[{"given":"Wenjie","family":"Dong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sifeng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhigeng","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyu","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liangyan","family":"Tao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2020120420301918500_ref001","first-page":"60","article-title":"What is return on quality, and why you should care","volume":"10","year":"1992","journal-title":"Electronic News"},{"key":"key2020120420301918500_ref002","first-page":"8","article-title":"The benchmarking bandwagon","volume":"24","year":"1991","journal-title":"Quality Progress"},{"issue":"3","key":"key2020120420301918500_ref003","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1002\/npr.4040100304","article-title":"Pinpointing the real cost of quality in a service company","volume":"10","year":"1991","journal-title":"National Productivity Review"},{"issue":"3","key":"key2020120420301918500_ref004","first-page":"33","article-title":"CoQ systems: the right stuff","volume":"30","year":"1997","journal-title":"Quality Progress"},{"issue":"3","key":"key2020120420301918500_ref005","first-page":"8","article-title":"Modeling quality-cost dynamics","volume":"13","year":"1997","journal-title":"International Journal of Quality & Reliability Management"},{"issue":"9","key":"key2020120420301918500_ref006","first-page":"84","article-title":"Study on grey GM(1,1) model of Juran quality cost based on poor information","volume":"47","year":"2017","journal-title":"Mathematics in Practice and Theory"},{"issue":"1","key":"key2020120420301918500_ref008","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/0026-2714(84)90638-3","article-title":"New analytical models for logistics support cost and life cycle cost vs reliability function","volume":"24","year":"1984","journal-title":"Microelectronics Reliability"},{"key":"key2020120420301918500_ref009","volume-title":"Quality Control Handbook","year":"1951"},{"key":"key2020120420301918500_ref010","unstructured":"Liu, S., Forrest, J.Y.L. and Yang, Y. 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