Erfan Shahab, Amirhossein Kazemisaboor, S. Khaleghparast, Omid Fatahi Valilai
{"title":"云制造网络中的生产反弹方法:新冠肺炎大流行的案例研究","authors":"Erfan Shahab, Amirhossein Kazemisaboor, S. Khaleghparast, Omid Fatahi Valilai","doi":"10.1080/17509653.2022.2112781","DOIUrl":null,"url":null,"abstract":"ABSTRACT Industry 4.0 paradigm has enabled manufacturing systems with reformations for Cloud-based manufacturing business models. This reformation can create resilient structures as an inevitable opportunity for manufacturing supply networks. This is achieved by using service composition capabilities in Cloud manufacturing network which significantly enhances supply network performance when encountering disruptions. Focusing on redundancy as one of the most effective approaches to resiliency, a new model for manufacturing service composition is proposed. The model considers a minimum level of subentropy when responding to the demands at the process level while controlling the entropy overall at supply network level. This creates a balanced policy for entropy at the network level, and subentropies at the process level to both fulfill an optimal redundancy for disruption fulfillment and controling the complexity throughout the network. A case study is considered for manufacturing ventilator production COVID-19 pandemic. The capabilities of the proposed model for optimal application of unused firm capacities from other supply networks like military and university research groups have been discussed. The proposed model is also investigated for fulfillment of disruptions like COVID-19 equipment supply network with mentioned capabilities. These capabilities fulfill the transition of manufacturing business models to a service-oriented paradigm with resilient structures.","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A production bounce-back approach in the Cloud manufacturing network: case study of COVID-19 pandemic\",\"authors\":\"Erfan Shahab, Amirhossein Kazemisaboor, S. Khaleghparast, Omid Fatahi Valilai\",\"doi\":\"10.1080/17509653.2022.2112781\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Industry 4.0 paradigm has enabled manufacturing systems with reformations for Cloud-based manufacturing business models. This reformation can create resilient structures as an inevitable opportunity for manufacturing supply networks. This is achieved by using service composition capabilities in Cloud manufacturing network which significantly enhances supply network performance when encountering disruptions. Focusing on redundancy as one of the most effective approaches to resiliency, a new model for manufacturing service composition is proposed. The model considers a minimum level of subentropy when responding to the demands at the process level while controlling the entropy overall at supply network level. This creates a balanced policy for entropy at the network level, and subentropies at the process level to both fulfill an optimal redundancy for disruption fulfillment and controling the complexity throughout the network. A case study is considered for manufacturing ventilator production COVID-19 pandemic. The capabilities of the proposed model for optimal application of unused firm capacities from other supply networks like military and university research groups have been discussed. The proposed model is also investigated for fulfillment of disruptions like COVID-19 equipment supply network with mentioned capabilities. These capabilities fulfill the transition of manufacturing business models to a service-oriented paradigm with resilient structures.\",\"PeriodicalId\":46578,\"journal\":{\"name\":\"International Journal of Management Science and Engineering Management\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2022-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Management Science and Engineering Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/17509653.2022.2112781\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Management Science and Engineering Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/17509653.2022.2112781","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
A production bounce-back approach in the Cloud manufacturing network: case study of COVID-19 pandemic
ABSTRACT Industry 4.0 paradigm has enabled manufacturing systems with reformations for Cloud-based manufacturing business models. This reformation can create resilient structures as an inevitable opportunity for manufacturing supply networks. This is achieved by using service composition capabilities in Cloud manufacturing network which significantly enhances supply network performance when encountering disruptions. Focusing on redundancy as one of the most effective approaches to resiliency, a new model for manufacturing service composition is proposed. The model considers a minimum level of subentropy when responding to the demands at the process level while controlling the entropy overall at supply network level. This creates a balanced policy for entropy at the network level, and subentropies at the process level to both fulfill an optimal redundancy for disruption fulfillment and controling the complexity throughout the network. A case study is considered for manufacturing ventilator production COVID-19 pandemic. The capabilities of the proposed model for optimal application of unused firm capacities from other supply networks like military and university research groups have been discussed. The proposed model is also investigated for fulfillment of disruptions like COVID-19 equipment supply network with mentioned capabilities. These capabilities fulfill the transition of manufacturing business models to a service-oriented paradigm with resilient structures.
期刊介绍:
International Journal of Management Science and Engineering Management (IJMSEM) is a peer-reviewed quarterly journal that provides an international forum for researchers and practitioners of management science and engineering management. The journal focuses on identifying problems in the field, and using innovative management theories and new management methods to provide solutions. IJMSEM is committed to providing a platform for researchers and practitioners of management science and engineering management to share experiences and communicate ideas. Articles published in IJMSEM contain fresh information and approaches. They provide key information that will contribute to new scientific inquiries and improve competency, efficiency, and productivity in the field. IJMSEM focuses on the following: 1. identifying Management Science problems in engineering; 2. using management theory and methods to solve above problems innovatively and effectively; 3. developing new management theory and method to the newly emerged management issues in engineering; IJMSEM prefers papers with practical background, clear problem description, understandable physical and mathematical model, physical model with practical significance and theoretical framework, operable algorithm and successful practical applications. IJMSEM also takes into account management papers of original contributions in one or several aspects of these elements.