{"title":"在供应商-买家供应链模型中提高制造质量和降低成本","authors":"Arunava Majumder, Rekha Guchhait, B. Sarkar","doi":"10.1504/EJIE.2017.087678","DOIUrl":null,"url":null,"abstract":"Quality improvement and setup cost reduction of any production system are endless procedure. Customer's demand is always intended to have the best quality product and the industries always try to improve the quality of products. This paper develops a two-echelon supply chain model with quality improvement of products and setup cost reduction under controllable lead time. The lead time demand follows a normal distribution and in the second case, it does not consider any specific distribution except a mean and standard deviation. Both models are solved analytically to obtain global solution. Two improved iterative algorithms are developed in order to obtain the optimal results of decision variables numerically to minimise the total system cost. The expected value of additional information is calculated to show the financial effect for collecting the information about lead time demand distribution. Some numerical examples and sensitivity analysis are given to illustrate the model. [Received 8 December 2016; Revised 27 March 2017; Accepted 21 April 2017]","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2017-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.087678","citationCount":"34","resultStr":"{\"title\":\"Manufacturing quality improvement and setup cost reduction in a vendor-buyer supply chain model\",\"authors\":\"Arunava Majumder, Rekha Guchhait, B. Sarkar\",\"doi\":\"10.1504/EJIE.2017.087678\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quality improvement and setup cost reduction of any production system are endless procedure. Customer's demand is always intended to have the best quality product and the industries always try to improve the quality of products. This paper develops a two-echelon supply chain model with quality improvement of products and setup cost reduction under controllable lead time. The lead time demand follows a normal distribution and in the second case, it does not consider any specific distribution except a mean and standard deviation. Both models are solved analytically to obtain global solution. Two improved iterative algorithms are developed in order to obtain the optimal results of decision variables numerically to minimise the total system cost. The expected value of additional information is calculated to show the financial effect for collecting the information about lead time demand distribution. Some numerical examples and sensitivity analysis are given to illustrate the model. [Received 8 December 2016; Revised 27 March 2017; Accepted 21 April 2017]\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2017-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1504/EJIE.2017.087678\",\"citationCount\":\"34\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1504/EJIE.2017.087678\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1504/EJIE.2017.087678","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Manufacturing quality improvement and setup cost reduction in a vendor-buyer supply chain model
Quality improvement and setup cost reduction of any production system are endless procedure. Customer's demand is always intended to have the best quality product and the industries always try to improve the quality of products. This paper develops a two-echelon supply chain model with quality improvement of products and setup cost reduction under controllable lead time. The lead time demand follows a normal distribution and in the second case, it does not consider any specific distribution except a mean and standard deviation. Both models are solved analytically to obtain global solution. Two improved iterative algorithms are developed in order to obtain the optimal results of decision variables numerically to minimise the total system cost. The expected value of additional information is calculated to show the financial effect for collecting the information about lead time demand distribution. Some numerical examples and sensitivity analysis are given to illustrate the model. [Received 8 December 2016; Revised 27 March 2017; Accepted 21 April 2017]
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.