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Addressing Challenges in Cobot Integration: Using Discrete Event Simulation Models to Redesign Multistage Manufacturing Flow Lines
Conference proceeding   Peer reviewed

Addressing Challenges in Cobot Integration: Using Discrete Event Simulation Models to Redesign Multistage Manufacturing Flow Lines

Manuel Felder, Anita Onay, Elias Hagendorfer, Simon Plunger and Erwin Rauch
Manufacturing 2030 A Perspective to Future Challenges in Industrial Production: Proceedings of the 4th International Symposium on Industrial Engineering and Automation ISIEA 2025 and 18th EPIEM Conference 2025, Vol.1605, pp.185-201
Lecture Notes in Networks and Systems, 1605
4th International Symposium on Industrial Engineering and Automation (Bozen, 18/06/2025–20/06/2025)
2025
Handle:
https://hdl.handle.net/10863/51589

Abstract

Industry 5.0 Human-Robot Collaboration Line performance Processing time variability
Introducing collaborative robots (cobots) into multistage manufacturing flow lines presents significant opportunities but also challenges for production systems. This study explores the use of discrete event simulation (DES) as a powerful tool to support the integration of cobots in a high-volume flow line, where varying order lot sizes are processed across multiple stages. Thus far, human operators perform manufacturing tasks in a predefined sequence in this system. During the redesign project, specific tasks were identified and reallocated to cobots through a structured decision-making process, requiring coordination across various organizational levels and collaboration with experts from within the company and external partners. To capture the dynamic nature and stochasticity of the flow line, we use a DES-model that explicitly factors in the variability of task execution times, including those newly assigned to cobots, by using distribution functions for effective processing times (PTs). Thus, with the DES-model we (1) address critical challenges that may arise from task reallocation from human operators to cobots and (2) mitigate these multifaceted challenges that arise from decision-making complexity, system constraints and dynamics.
url
https://doi.org/10.1007/978-3-032-03722-0_16View

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