Analysis of assembly-time performance (ATP) in manufacturing operations with collaborative robots: a systems approach

Nan Chen, Ningjian Huang, Robert Radwin and Jingshan Li

International Journal of Production Research, 2022, vol. 60, issue 1, 277-296

Abstract: Reducing station processing times has a significant importance in manufacturing assembly systems. In recent years, there has been a growing interest in using collaborative robots to assist human operators in many manufacturing systems, which can not only improve ergonomics measures but also reduce processing time and increase throughput. In this paper, a system-theoretic approach is introduced to analyse the assembly-time performance (ATP) of assembly systems with collaborative robots, where ATP is defined as the probability to finish all the assembly operations in a station within a desired time interval. Specifically, the assembly operations are described by stochastic processes with both individual (human operator and robot) preparation tasks and joint collaboration tasks, characterised by general or arbitrary distributions of task times. Then an efficient algorithm is presented by using gamma distributions to approximate task times and aggregate multiple interacting tasks to calculate ATP. High accuracy in ATP evaluation is obtained through such an approximation method. In addition, system properties, such as monotonicity and sensitivity, i.e. bottlenecks, are investigated. Finally, a case study at an automotive powertrain assembly plant is introduced to illustrate the applicability of the method and the effectiveness for assembly time reduction through using collaborative robots.

Date: 2022
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DOI: 10.1080/00207543.2021.2000060

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