Mohammed A. Noman, Adel M. Al-Shayea, E. A. Nasr, Husam Kaid, A. Al-Ahmari, A. Kamrani, Haitham A. Mahmoud
{"title":"基于EWMA和CUSUM控制图的维修计划和过程质量控制优化模型","authors":"Mohammed A. Noman, Adel M. Al-Shayea, E. A. Nasr, Husam Kaid, A. Al-Ahmari, A. Kamrani, Haitham A. Mahmoud","doi":"10.21278/TOF.451021920","DOIUrl":null,"url":null,"abstract":"The performance of a production system is highly dependent on the smooth operation of various equipment and processes. Thus, reducing failures of the equipment and processes in a cost-effective manner improves overall performance; this is often achieved by carrying out maintenance and quality control policies. In this study, an integrated optimization method that addresses both maintenance strategies and quality control practices is proposed using an exponentially weighted moving average (EWMA) chart, in which both corrective and preventive maintenance policies are considered. The integrated model has been proposed to find optimal decision variables of both the process quality decision parameters and the optimal interval of preventive maintenance (i.e., Ns, Hs, L, λ, and t ) to result in overall optimal expected hourly total system costs. A case study is then utilized to investigate the impact of cost criteria on the proposed integrated model and to compare the proposed model with a model using the cumulative sum (CUSUM) control chart. The improved model outputs indicate that there is a reduction of 34.6% in the total expected costs compared with those of the other model using the CUSUM chart. Finally, an analysis of sensitivity to present the effectiveness of the model parameters and the main variables in the overall costs of the system is provided.","PeriodicalId":49428,"journal":{"name":"Transactions of FAMENA","volume":"45 1","pages":"0-0"},"PeriodicalIF":1.4000,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Model for Maintenance Planning and Process Quality Control Optimization Based on EWMA and CUSUM Control Charts\",\"authors\":\"Mohammed A. Noman, Adel M. Al-Shayea, E. A. Nasr, Husam Kaid, A. Al-Ahmari, A. Kamrani, Haitham A. Mahmoud\",\"doi\":\"10.21278/TOF.451021920\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The performance of a production system is highly dependent on the smooth operation of various equipment and processes. Thus, reducing failures of the equipment and processes in a cost-effective manner improves overall performance; this is often achieved by carrying out maintenance and quality control policies. In this study, an integrated optimization method that addresses both maintenance strategies and quality control practices is proposed using an exponentially weighted moving average (EWMA) chart, in which both corrective and preventive maintenance policies are considered. The integrated model has been proposed to find optimal decision variables of both the process quality decision parameters and the optimal interval of preventive maintenance (i.e., Ns, Hs, L, λ, and t ) to result in overall optimal expected hourly total system costs. A case study is then utilized to investigate the impact of cost criteria on the proposed integrated model and to compare the proposed model with a model using the cumulative sum (CUSUM) control chart. The improved model outputs indicate that there is a reduction of 34.6% in the total expected costs compared with those of the other model using the CUSUM chart. Finally, an analysis of sensitivity to present the effectiveness of the model parameters and the main variables in the overall costs of the system is provided.\",\"PeriodicalId\":49428,\"journal\":{\"name\":\"Transactions of FAMENA\",\"volume\":\"45 1\",\"pages\":\"0-0\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2021-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transactions of FAMENA\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.21278/TOF.451021920\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions of FAMENA","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.21278/TOF.451021920","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
A Model for Maintenance Planning and Process Quality Control Optimization Based on EWMA and CUSUM Control Charts
The performance of a production system is highly dependent on the smooth operation of various equipment and processes. Thus, reducing failures of the equipment and processes in a cost-effective manner improves overall performance; this is often achieved by carrying out maintenance and quality control policies. In this study, an integrated optimization method that addresses both maintenance strategies and quality control practices is proposed using an exponentially weighted moving average (EWMA) chart, in which both corrective and preventive maintenance policies are considered. The integrated model has been proposed to find optimal decision variables of both the process quality decision parameters and the optimal interval of preventive maintenance (i.e., Ns, Hs, L, λ, and t ) to result in overall optimal expected hourly total system costs. A case study is then utilized to investigate the impact of cost criteria on the proposed integrated model and to compare the proposed model with a model using the cumulative sum (CUSUM) control chart. The improved model outputs indicate that there is a reduction of 34.6% in the total expected costs compared with those of the other model using the CUSUM chart. Finally, an analysis of sensitivity to present the effectiveness of the model parameters and the main variables in the overall costs of the system is provided.