A. Duarte, Marcia Regina Santiago Santiago Scarpin
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Application of predictive maintenance practices should be considered as the primary training tool.Research limitations/implicationsThis study used a secondary database, limiting the research design and data manipulation.Practical implicationsThe article provides practitioners with an analysis of maintenance practices by category (predictive, preventive and corrective), and the impact of each practice on the OEE of continuous process productive plants. Moreover, it explores the importance of training for extracting more results from maintenance practices.Social implicationsCompanies are investing in new technologies, but it is also essential to invest in training people. There is a demand for Industry 4.0 through the introduction of upskilling and reskilling programs.Originality/valueThis study used practice-based view (PBV) theory to explain how maintenance practices help firms achieve greater OEE. Furthermore, it introduced training practice as a moderating variable in the relationship between maintenance practices and OEE.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Maintenance practices and overall equipment effectiveness: testing the moderating effect of training\",\"authors\":\"A. Duarte, Marcia Regina Santiago Santiago Scarpin\",\"doi\":\"10.1108/jqme-04-2021-0033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"PurposeThis study aims to identify the relationship between different maintenance practices and productive efficiency in continuous process productive plants as well as the moderating effect of good training practices.Design/methodology/approachThe empirical data were drawn from a database containing 609 observations of 29 productive units. Scales were validated using the Q-sort method. The panel data technique was used as the analysis methodology, with the inclusion of fixed effects for each productive plant.FindingsMaintenance practices can effectively contribute to increasing the overall equipment effectiveness (OEE) of firms. Application of predictive maintenance practices should be considered as the primary training tool.Research limitations/implicationsThis study used a secondary database, limiting the research design and data manipulation.Practical implicationsThe article provides practitioners with an analysis of maintenance practices by category (predictive, preventive and corrective), and the impact of each practice on the OEE of continuous process productive plants. Moreover, it explores the importance of training for extracting more results from maintenance practices.Social implicationsCompanies are investing in new technologies, but it is also essential to invest in training people. There is a demand for Industry 4.0 through the introduction of upskilling and reskilling programs.Originality/valueThis study used practice-based view (PBV) theory to explain how maintenance practices help firms achieve greater OEE. 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Maintenance practices and overall equipment effectiveness: testing the moderating effect of training
PurposeThis study aims to identify the relationship between different maintenance practices and productive efficiency in continuous process productive plants as well as the moderating effect of good training practices.Design/methodology/approachThe empirical data were drawn from a database containing 609 observations of 29 productive units. Scales were validated using the Q-sort method. The panel data technique was used as the analysis methodology, with the inclusion of fixed effects for each productive plant.FindingsMaintenance practices can effectively contribute to increasing the overall equipment effectiveness (OEE) of firms. Application of predictive maintenance practices should be considered as the primary training tool.Research limitations/implicationsThis study used a secondary database, limiting the research design and data manipulation.Practical implicationsThe article provides practitioners with an analysis of maintenance practices by category (predictive, preventive and corrective), and the impact of each practice on the OEE of continuous process productive plants. Moreover, it explores the importance of training for extracting more results from maintenance practices.Social implicationsCompanies are investing in new technologies, but it is also essential to invest in training people. There is a demand for Industry 4.0 through the introduction of upskilling and reskilling programs.Originality/valueThis study used practice-based view (PBV) theory to explain how maintenance practices help firms achieve greater OEE. Furthermore, it introduced training practice as a moderating variable in the relationship between maintenance practices and OEE.
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