Arno Kasper , Martin Land , Will Bertrand , Jacob Wijngaard
{"title":"Designing production planning and control in smart manufacturing","authors":"Arno Kasper , Martin Land , Will Bertrand , Jacob Wijngaard","doi":"10.1016/j.compind.2024.104104","DOIUrl":null,"url":null,"abstract":"<div><p>To make manufacturing technology productive, manufacturers rely on a production planning and control (PPC) framework that plans ahead and monitors ongoing transformation processes. The design of an appropriate framework has far-reaching implications for the manufacturing organization as a whole. Yet, to date, there has been no unified guidance on key PPC design issues. This is strongly needed, as it has been argued that novel information processing technologies – as part of Industry 4.0 – result in PPC frameworks with decentral structures. This conflicts with traditional works arguing for hierarchical or central structures. Therefore, we review the PPC design literature to create a comprehensive overview and summarize design proposals. Based on our review, we come to the intermediate conclusion that PPC frameworks continue to have a hierarchical structure, although decision-making is shifted more to decentral levels compared to traditional hierarchies. Our analysis suggests that the effect of a decentralization shift has potentially strong and poorly understood implications, both from a decision-making and organizational perspective.</p></div>","PeriodicalId":55219,"journal":{"name":"Computers in Industry","volume":"159 ","pages":"Article 104104"},"PeriodicalIF":8.2000,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0166361524000320/pdfft?md5=0bb013d88ab81a8ce87b3c8fefc23521&pid=1-s2.0-S0166361524000320-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in Industry","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0166361524000320","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
To make manufacturing technology productive, manufacturers rely on a production planning and control (PPC) framework that plans ahead and monitors ongoing transformation processes. The design of an appropriate framework has far-reaching implications for the manufacturing organization as a whole. Yet, to date, there has been no unified guidance on key PPC design issues. This is strongly needed, as it has been argued that novel information processing technologies – as part of Industry 4.0 – result in PPC frameworks with decentral structures. This conflicts with traditional works arguing for hierarchical or central structures. Therefore, we review the PPC design literature to create a comprehensive overview and summarize design proposals. Based on our review, we come to the intermediate conclusion that PPC frameworks continue to have a hierarchical structure, although decision-making is shifted more to decentral levels compared to traditional hierarchies. Our analysis suggests that the effect of a decentralization shift has potentially strong and poorly understood implications, both from a decision-making and organizational perspective.
期刊介绍:
The objective of Computers in Industry is to present original, high-quality, application-oriented research papers that:
• Illuminate emerging trends and possibilities in the utilization of Information and Communication Technology in industry;
• Establish connections or integrations across various technology domains within the expansive realm of computer applications for industry;
• Foster connections or integrations across diverse application areas of ICT in industry.