Open this publication in new window or tab >>2024 (English)In: Procedia Computer Science, E-ISSN 1877-0509, Vol. 232, p. 3121-3130Article in journal (Refereed) Published
Abstract [en]
The performance of a production system is primarily evaluated by its throughput, which is constrained by throughput bottlenecks. Thus, bottleneck analysis (BA), encompassing bottleneck identification, diagnosis, prediction, and prescription, is a crucial analytical process contributing to the success of manufacturing industries. Nevertheless, BA requires a substantial quantity of information from the manufacturing system, making it a data-intensive task. Based on the dynamic nature of bottlenecks, the optimal strategy for BA entails making well-informed decisions in real-time and executing necessary modifications accordingly. The efficient implementation of BA requires gathering, storing, analyzing, and illustrating data from the shop floor. Utilizing Industry 4.0 technologies, such as cyber-physical systems and cloud technology, facilitates the execution of data-intensive operations for the successful management of BA in real-world settings. The main objective of this study is to establish a framework for BA through the utilization of Cloud-Based Cyber-Physical Systems (CB-CPSs). First, a literature review was conducted to identify relevant research and current applications of CB-CPSs in BA. Using the results of the review, a CB-CPSs framework was subsequently introduced for BA. The application of the framework was assessed via simulation in a real-world manufacturer of marine engines. The findings indicate that the implementation of CB-CPSs can contribute significantly to throughput improvement.
Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Bottleneck analysis, Cyber-physical systems, Industry 4.0, Simulation
National Category
Production Engineering, Human Work Science and Ergonomics Computer Systems
Research subject
Virtual Production Development (VPD)
Identifiers
urn:nbn:se:his:diva-23729 (URN)10.1016/j.procs.2024.02.128 (DOI)001196800603017 ()2-s2.0-85189816187 (Scopus ID)
Conference
5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023 Lisbon 22 November 2023 through 24 November 2023
Projects
ACCURATE 4.0
Funder
Knowledge Foundation, 20200181
Note
CC BY-NC-ND 4.0 DEED
© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)
Correspondence Address: E. Mahmoodi; Division of Intelligent Production Systems, School of Engineering Science, University of Skövde, Skövde, 54128, Sweden; email: Ehsan.mahmoodi@his.se
We would like to express our gratitude to the Knowledge Foundation (KKS), Sweden, for their financial support through the ACCURATE 4.0 project, under grant agreement No. 20200181. We also wish to extend our appreciation to our industrial partner, Volvo Penta, Sweden. Their collaboration, expertise, and invaluable insights have significantly contributed to this study.
2024-04-182024-04-182024-08-15Bibliographically approved