Title: Assessing process time estimation for job sequencing in moving mixed-model assembly lines

Authors: Faisal S. Alfaiz; David S. Kim; Hector A. Vergara

Addresses: School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University, 204 Rogers Hall, Corvallis, Oregon, USA ' School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University, 204 Rogers Hall, Corvallis, Oregon, USA ' School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University, 204 Rogers Hall, Corvallis, Oregon, USA

Abstract: Job sequencing optimisation in moving mixed-model assembly lines has been studied extensively, and many optimisation procedures require average job processing times as input. However, in practice estimating average job processing times can be difficult for multiple reasons. In this study, various factors related to job processing time estimation are investigated to provide insight into more efficient job processing time estimation to support sequencing optimisation. To this end job sequencing optimisation was performed using job processing times representing estimates, where specific differences from assumed true average processing times were controlled, and separately with the assumed true average processing times. Experiments were conducted to identify the characteristics of the estimated processing times having the greatest impact on job sequence performance (i.e., the performance differences between using estimated, and assumed true processing times in job sequencing optimisation). The results indicate that if the estimated processing times used for job sequencing optimisation replicate specific properties (e.g., the rank) of true processing times, which may be different for different assembly systems, then most benefits of job sequencing optimisation may be realised.

Keywords: sequencing; job sequencing; assembly lines; assessing processing time; mixed-model assembly lines; MMAL; processing time; processing time estimation; processing time estimation properties; work overload; makespan.

DOI: 10.1504/IJISE.2024.136416

International Journal of Industrial and Systems Engineering, 2024 Vol.46 No.2, pp.215 - 237

Received: 07 Mar 2022
Accepted: 29 May 2022
Published online: 01 Feb 2024 *

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