Pub Date : 2023-11-08DOI: 10.1080/21693277.2023.2279329
Chen Chen, Tiong Lee Kong, Wu Kan
Industry 4.0 technologies create a connected ecosystem that allows for real-time monitoring, control, and optimization. This enables the manufacturing industry to move the ultimate goal of their businesses from lean to leagile. Then, to meet the needs of leagile manufacturing, an integrated production planning and scheduling system is needed. The academic world responds to the need by the growth of papers. Many methodologies, models, frameworks, and methods have been proposed. Literature abounds on classifying them, yet it remains inconclusive mainly on their applicability to Industry 4.0. In this regard, this paper conducts a literature review aiming to show the state of the art and discover the most promising production planning and scheduling method for Industry 4.0 among the many. Lastly, on the basis of this study, recommendations on possible future research directions are provided for researchers, and the design of the next-generation production planning and scheduling system for Industry 4.0 is also suggested.
{"title":"Identifying the promising production planning and scheduling method for manufacturing in Industry 4.0: a literature review","authors":"Chen Chen, Tiong Lee Kong, Wu Kan","doi":"10.1080/21693277.2023.2279329","DOIUrl":"https://doi.org/10.1080/21693277.2023.2279329","url":null,"abstract":"Industry 4.0 technologies create a connected ecosystem that allows for real-time monitoring, control, and optimization. This enables the manufacturing industry to move the ultimate goal of their businesses from lean to leagile. Then, to meet the needs of leagile manufacturing, an integrated production planning and scheduling system is needed. The academic world responds to the need by the growth of papers. Many methodologies, models, frameworks, and methods have been proposed. Literature abounds on classifying them, yet it remains inconclusive mainly on their applicability to Industry 4.0. In this regard, this paper conducts a literature review aiming to show the state of the art and discover the most promising production planning and scheduling method for Industry 4.0 among the many. Lastly, on the basis of this study, recommendations on possible future research directions are provided for researchers, and the design of the next-generation production planning and scheduling system for Industry 4.0 is also suggested.","PeriodicalId":37891,"journal":{"name":"Production and Manufacturing Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135393319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The fourth industrial revolution (I4.0) has changed the traditional business model, bringing various benefits, including increased efficiency and productivity in organizations. However, to attain success in I4.0 practices requires collaboration from various stakeholders. This study objectives to identify the facilitators of I4.0 practices that can lead to successful collaboration among stakeholders from a circular perspective. An extensive literature review is performed to identify 14 potential facilitators. Further, the study adopts a mixed methodology of Best-Worst Method (BWM) and Interpretive Structural Modeling (ISM) to analyze the interconnectedness among the identified facilitators. BWM method was used to determine the relative importance of the identified facilitators, while ISM technique was used to determine the relationships between the facilitators of I4.0 practices. The findings from the study reveal that to strengthen stakeholder collaboration, organizations need to focus more on training and capacity-building programs and create more opportunities for technology exchange.
{"title":"Examining the facilitators of I4.0 practices to attain stakeholders’ collaboration: a circular perspective","authors":"Ashish Dwivedi, Shefali Srivastava, Dindayal Agrawal, Suchi Dubey, Tripti Singh, Saurabh Pratap","doi":"10.1080/21693277.2023.2266643","DOIUrl":"https://doi.org/10.1080/21693277.2023.2266643","url":null,"abstract":"The fourth industrial revolution (I4.0) has changed the traditional business model, bringing various benefits, including increased efficiency and productivity in organizations. However, to attain success in I4.0 practices requires collaboration from various stakeholders. This study objectives to identify the facilitators of I4.0 practices that can lead to successful collaboration among stakeholders from a circular perspective. An extensive literature review is performed to identify 14 potential facilitators. Further, the study adopts a mixed methodology of Best-Worst Method (BWM) and Interpretive Structural Modeling (ISM) to analyze the interconnectedness among the identified facilitators. BWM method was used to determine the relative importance of the identified facilitators, while ISM technique was used to determine the relationships between the facilitators of I4.0 practices. The findings from the study reveal that to strengthen stakeholder collaboration, organizations need to focus more on training and capacity-building programs and create more opportunities for technology exchange.","PeriodicalId":37891,"journal":{"name":"Production and Manufacturing Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135141667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Process windows in injection molding are habitually built with only one performance measure in mind. In reality, a more realistic picture can be obtained when considering multiple performance measures at a time, especially in the presence of conflict. In this work, the construction of process windows for injection molding (IM) is undertaken considering two and three performance measures in conflict simultaneously. The best compromises between the criteria involved are identified through the direct application of the concept of Pareto-dominance in multiple criteria optimization. The aim is to provide a formal and realistic strategy to set processing conditions in IM operations. The resulting optimization approach is easily implementable in MS Excel. The solutions are presented graphically to facilitate their use in manufacturing plants.
{"title":"Simulation-based process windows simultaneously considering two and three conflicting criteria in injection molding.","authors":"Alicia Berenice Rodríguez-Yáñez, Yaileen Méndez-Vázquez, Mauricio Cabrera-Ríos","doi":"10.1080/21693277.2014.949359","DOIUrl":"https://doi.org/10.1080/21693277.2014.949359","url":null,"abstract":"<p><p>Process windows in injection molding are habitually built with only one performance measure in mind. In reality, a more realistic picture can be obtained when considering multiple performance measures at a time, especially in the presence of conflict. In this work, the construction of process windows for injection molding (IM) is undertaken considering two and three performance measures in conflict simultaneously. The best compromises between the criteria involved are identified through the direct application of the concept of Pareto-dominance in multiple criteria optimization. The aim is to provide a formal and realistic strategy to set processing conditions in IM operations. The resulting optimization approach is easily implementable in MS Excel. The solutions are presented graphically to facilitate their use in manufacturing plants.</p>","PeriodicalId":37891,"journal":{"name":"Production and Manufacturing Research","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/21693277.2014.949359","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32927174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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