Weighted grey relational analysis to evaluate multilevel dispatching rules in wafer fabrication

Abstract

PurposeThis research proposes weighted grey relational analysis (WGRA) method to evaluate the performance of 325 multilevel dispatching rules in the wafer fabrication process.Design/methodology/approachThe research methodology involves multilevel dispatching rule generation, simulations, WGRA and result analysis. A complete permutation of multilevel dispatching rules, including the partial orders, is generated from five basic rules. Performance measures include cycle time, move, tool idling and queue time. The simulation model and data are obtained from a wafer fab in Malaysia. Two seasons varying in customer orders and objective weights are defined. Finally, to benchmark performance and investigate the effect of varying values of coefficient, the models are compared against TOPSIS and VIKOR.FindingsResults show that the seasons prefer different multilevel dispatching rules. In Normal season, the ideal first basic dispatching rule is critical ratio (CR) and CR followed by shortest processing time (SPT) is the best precedence pairing. In Peak season, the superiority of the rule no longer heavily relies on the first basic rule but rather depends on the combination of tiebreaker rules and on-time delivery (OTD) followed by CR is considered the best precedence pairing. Compared to VIKOR and TOPSIS, WGRA generates more stable rankings in this study. The performance of multicriteria decision-making (MCDM) methods is influenced by the data variability, as a higher variability produces a much consistent ranking.Research limitations/implicationsAs research implications, the application illustrates the effectiveness and practicality of the WGRA model in analyzing multilevel dispatching rules, considering the complexity of the semiconductor wafer fabrication system. The methodology is useful for researchers wishing to integrate MCDM model into multilevel dispatching rules. The limitation of the research is that the results were obtained from a simulation model. Also, the rules, criteria and weights assigned in WGRA were decided by the management. Lastly, the distinguishing coefficient is fixed at 0.5 and the effect to the ranking requires further study.Originality/valueThe research is the first deployment WGRA in ranking multilevel dispatching rules. Multilevel dispatching rules are rarely studied in scheduling research although studies show that the tiebreakers affect the performances of the dispatching rules. The scheduling reflects the characteristics of wafer fabrication and general job shop, such as threshold and look-ahead policies.

The evaluation of grey relative incidence

“…This is because GIA models have a range of practical applications. Among the most important of them are: to evaluate multilevel dispatching rules in wafer fabrication (Chia Yee et al. , 2021), optimisation of the investment portfolio (Škrinjarić, 2020), assessment of financial results of stock exchange companies (Javanmardi et al ., 2021), socio-economic policies related to sustainable development (Javanmardi et al ., 2020; Koçak, 2020), project management (Javed and Liu, 2019), selection of the best cities to live in selected countries around the world (Kose et al ., 2020), evaluation of provincial integration degree of “Internet + industry” (Yang and Xie, 2019), broadly understood health diagnostics (Zhang et al ., 2022).…”

Grey angle cosine relational degree model based on generalized greyness of interval grey number

“…According to the deviation degree of interval grey numbers, Liu et al (2017) proposed a grey relational degree model. Although these relational models of interval grey numbers have been widely applied in the evaluation (Bi et al, 2020;Zhang and Luo, 2022;Chia and Yee, 2021) and decision-making (Zhou et al, 2020;Sun, 2020;Yang et al, 2022;, these models are only based on the approximate expression of the external characteristics of interval grey number, and not based on the scientific expression of the connotative information of interval grey number. Therefore, according to the grey immortal axiom, Li and Li (2022a) first put forward the concept of generalized greyness of interval grey number and built a greyness relational degree model based on the greyness distance between two interval grey numbers, which not only realize the scientific expression of interval grey number, but also extend the application range of the classical grey relational degree model.…”

“…Although these relational models of interval grey numbers have been widely applied in the evaluation (Bi et al. , 2020; Zhang and Luo, 2022; Chia and Yee, 2021) and decision-making (Zhou et al. , 2020; Sun, 2020; Yang et al.…”