{"title":"Autonomous maintenance preparation system design with axioms","authors":"Suleyman Muftuoglu, E. Çevikcan, B. Durmuşoğlu","doi":"10.1108/jqme-01-2021-0007","DOIUrl":null,"url":null,"abstract":"PurposeThe purpose of this paper is to support total productive maintenance implementers by providing a roadmap for autonomous maintenance (AM) preparation phase.Design/methodology/approachThe authors use the axiomatic design (AD) methodology with lean philosophy as a paradigm.FindingsThis is an exploratory research to find the most important factors in AM preparation phase. A decoupled AD design ensures an effective usage of training within industry (TWI) and the introduction of standardized work (SW). TWI provides value in importance it assigns to leaders, with its “train the trainers” approach and in preparing a training program. Besides being an effective training method, TWI job instruction (TWI JI) provides needed information infrastructure to front load operators SW and equipment trainings.Research limitations/implicationsAlthough AD, TWI and lean artifacts are generally field proven, the research is limited due to the lack of an industrial application.Practical implicationsIn many real-life projects, companies do not know where to start and how to proceed, which leads to costly iterations. The proposed roadmap minimizes iterations and increases the chance of project success.Originality/valueThe authors apply AD for the first time to AM preparation phase despite it is used in the analysis of lean manufacturing. AD permits to structure holistically the most relevant lean manufacturing solutions to obtain a risk free roadmap. TWI has emerged as a training infrastructure; TWI JI-based operator SW training and the adaptation of JI structure to equipment training are original additions.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Quality in Maintenance Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/jqme-01-2021-0007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 2
Abstract
PurposeThe purpose of this paper is to support total productive maintenance implementers by providing a roadmap for autonomous maintenance (AM) preparation phase.Design/methodology/approachThe authors use the axiomatic design (AD) methodology with lean philosophy as a paradigm.FindingsThis is an exploratory research to find the most important factors in AM preparation phase. A decoupled AD design ensures an effective usage of training within industry (TWI) and the introduction of standardized work (SW). TWI provides value in importance it assigns to leaders, with its “train the trainers” approach and in preparing a training program. Besides being an effective training method, TWI job instruction (TWI JI) provides needed information infrastructure to front load operators SW and equipment trainings.Research limitations/implicationsAlthough AD, TWI and lean artifacts are generally field proven, the research is limited due to the lack of an industrial application.Practical implicationsIn many real-life projects, companies do not know where to start and how to proceed, which leads to costly iterations. The proposed roadmap minimizes iterations and increases the chance of project success.Originality/valueThe authors apply AD for the first time to AM preparation phase despite it is used in the analysis of lean manufacturing. AD permits to structure holistically the most relevant lean manufacturing solutions to obtain a risk free roadmap. TWI has emerged as a training infrastructure; TWI JI-based operator SW training and the adaptation of JI structure to equipment training are original additions.
期刊介绍:
This exciting journal looks at maintenance engineering from a positive standpoint, and clarifies its recently elevatedstatus as a highly technical, scientific, and complex field. Typical areas examined include: ■Budget and control ■Equipment management ■Maintenance information systems ■Process capability and maintenance ■Process monitoring techniques ■Reliability-based maintenance ■Replacement and life cycle costs ■TQM and maintenance