A new framework for balancing and performance evaluation in stochastic assembly line using queueing networks

Mehmet Pınarbaşı and Mustafa Yüzükırmızı

European Journal of Industrial Engineering, 2023, vol. 17, issue 2, 220-252

Abstract: Real world assembly lines have a characterisation of variability in arrival, service and departure processes. Modelling these variabilities and their interactions, and the optimisation of a line have not been achieved yet. The purpose of this research is to provide an analytical solution framework for finding the best combinations of task assignment under variability. A queueing-based decomposition model that considers all variations sources has been proposed for the performance evaluation of a stochastic assembly line. A closed, nonlinear constraint programming model has been developed. Mathematical relations from the variability sources are established to measure the overall system performance. Numerical experiments which are conducted on several numerical examples demonstrate that the approach is a viable and an effective solution method. The results also indicate that changes in the coefficient of variance of either the service or arrival process, alter both the task assignment combinations, station workloads and line performance. [Submitted: 10 July 2021; Accepted: 19 January 2022]

Keywords: stochastic assembly line balancing; variability; queueing network; constraint programming; decomposition; simulation. (search for similar items in EconPapers)
Date: 2023
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