Response surface approach to robust design of assembly cells through simulation

Abstract

Purpose This paper aims to present a multi-response robust design (RD) optimization approach for U-shaped assembly cells (ACs) with multi-functional walking-workers by using operational design (OD) factors in a simulation setting. The proposed methodology incorporated the design factors related to the operation of ACs into an RD framework. Utilization of OD factors provided a practical design approach for ACs addressing system robustness without modifying the cell structure. Design/methodology/approach Taguchi’s design philosophy and response surface meta-models have been combined for robust simulation optimization (SO). Multiple performance measures have been considered for the study and concurrently optimized by using a multi-response optimization (MRO) approach. Simulation setting provided flexibility in experimental design selection and facilitated experiments by avoiding cost and time constraints in real-world experiments. Findings The present approach is illustrated through RD of an AC for performance measures: average throughput time, average WIP inventory and cycle time. Findings are in line with expectations that a significant reduction in performance variability is attainable by trading-off optimality for robustness. Reductions in expected performance (optimality) values are negligible in comparison to reductions in performance variability (robustness). Practical implications ACs designed for robustness are more likely to meet design objectives once they are implemented, preventing changes or roll-backs. Successful implementations serve as examples to shop-floor personnel alleviating issues such as operator/supervisor resistance and scepticism, encouraging participation and facilitating teamwork. Originality/value ACs include many activities related to cell operation which can be used for performance optimization. The proposed framework is a realistic design approach using OD factors and considering system stochasticity in terms of noise factors for RD optimization through simulation. To the best of the authors’ knowledge, it is the first time a multi-response RD optimization approach for U-shaped manual ACs with multi-functional walking-workers using factors related to AC operation is proposed.

The job rotation scheduling problem considering human cognitive effects: an integrated approach

“…In their modeling, the learning effects were incorporated to calculate the output of each station. Aydin et al (2018) analyze the effect of worker allocation strategies on three performance measures of the u-shaped lines and show the significance of these effects in their response surface model. However, in this study, operators are homogenous.…”

“…Consequently, allocation decisions are not periodic and the length of rotations is constant. Except for the study by Aydin et al (2018), none of the above-mentioned studies address the job rotation scheduling in a U-shaped lean cell.…”

“…The advantage of a lean cell is derived from how the line is balanced, as well as, how the operators are allocated to the tasks (Aydin et al, 2018;Yılmaz, 2020). However, heterogeneity of operators has not been addressed extensively in the context of the lean cell design (Huang, 1999;Askin and Huang, 2001;Norman et al, 2002;Shewchuk, 2008;Akyol and Baykaso glu, 2019a).…”

A lean production system design for semiconductor crystal-ingot pulling manufacturing using hybrid Taguchi method and simulation optimization

“…Kuo et al (2008) combined simulation and the Taguchi method to optimize an integrated-circuit packaging system. Aydin et al (2018) proposed a response surface approach to robust design of assembly cells through simulation.…”

A novel optimization approach for segmented rabbit chase oriented U-type assembly line design: an application from lighting industry

“…Moreover, walking time is studied regarded as a parameter for worker allocation problem in U-shaped production lines (Nakade and Ohno, 2003;Shewchuk, 2008) as well as assembly (Aydin et al, 2018) and manufacturing (Edwards et al, 1993) cells. Moreover, time spent for walking is minimized as an objective function in some metaheuristic studies (Sirovetnukul and Chutima, 2009;Sirovetnukul and Chutima, 2010a;Chutima and Kid-Arn, 2013) for the same problem in UAL.…”