{"title":"交互式制造系统分析:迈向基于绩效的评估方法","authors":"Jose Antonio Mulet alberola, Irene Fassi","doi":"10.1049/cim2.12063","DOIUrl":null,"url":null,"abstract":"<p>Current manufacturing systems are forced to meet the most dynamic market demands under sustainable factors. However, not only technical transformations will address the challenge but, to fully cover social needs, the analysis of the human role in highly interactive systems is still decisive, following a socially sustainable approach. To fully extract the most from both agents under a performance point of view, the main added value of agents in the work environment needs to be carefully analysed, captured, and boosted. The context shapes a specific operation or task, which consequently drives the final outcome according to individual necessities. Furthermore, a methodology that potentially helps a proper assessment of these performance-based interactions is still missing. The contribution focusses on the definition of a novel human-centric methodology under a holistic point of view to analyse performance-based interactions and to define appropriate indices and metrics that helps assessing the human-system interactions in the manufacturing domain. The methodology is applied in a case study to guide practitioners with its use.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"4 4","pages":"286-298"},"PeriodicalIF":2.5000,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12063","citationCount":"0","resultStr":"{\"title\":\"Analysis of interactive manufacturing systems: Towards a performance-based assessment methodology\",\"authors\":\"Jose Antonio Mulet alberola, Irene Fassi\",\"doi\":\"10.1049/cim2.12063\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Current manufacturing systems are forced to meet the most dynamic market demands under sustainable factors. However, not only technical transformations will address the challenge but, to fully cover social needs, the analysis of the human role in highly interactive systems is still decisive, following a socially sustainable approach. To fully extract the most from both agents under a performance point of view, the main added value of agents in the work environment needs to be carefully analysed, captured, and boosted. The context shapes a specific operation or task, which consequently drives the final outcome according to individual necessities. Furthermore, a methodology that potentially helps a proper assessment of these performance-based interactions is still missing. The contribution focusses on the definition of a novel human-centric methodology under a holistic point of view to analyse performance-based interactions and to define appropriate indices and metrics that helps assessing the human-system interactions in the manufacturing domain. The methodology is applied in a case study to guide practitioners with its use.</p>\",\"PeriodicalId\":33286,\"journal\":{\"name\":\"IET Collaborative Intelligent Manufacturing\",\"volume\":\"4 4\",\"pages\":\"286-298\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2022-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12063\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Collaborative Intelligent Manufacturing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/cim2.12063\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Collaborative Intelligent Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/cim2.12063","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Analysis of interactive manufacturing systems: Towards a performance-based assessment methodology
Current manufacturing systems are forced to meet the most dynamic market demands under sustainable factors. However, not only technical transformations will address the challenge but, to fully cover social needs, the analysis of the human role in highly interactive systems is still decisive, following a socially sustainable approach. To fully extract the most from both agents under a performance point of view, the main added value of agents in the work environment needs to be carefully analysed, captured, and boosted. The context shapes a specific operation or task, which consequently drives the final outcome according to individual necessities. Furthermore, a methodology that potentially helps a proper assessment of these performance-based interactions is still missing. The contribution focusses on the definition of a novel human-centric methodology under a holistic point of view to analyse performance-based interactions and to define appropriate indices and metrics that helps assessing the human-system interactions in the manufacturing domain. The methodology is applied in a case study to guide practitioners with its use.
期刊介绍:
IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly.
The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).