World Scientific
Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×

System Upgrade on Tue, May 28th, 2024 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at customercare@wspc.com for any enquiries.

Applying Simulation Optimization for Agile Vehicle Fleet Sizing of Automated Material Handling Systems in Semiconductor Manufacturing

    https://doi.org/10.1142/S0217595921500184Cited by:1 (Source: Crossref)

    Automated material handling systems (AMHS) have been widely used in semiconductor manufacturing. However, the performance of AMHS heavily hinges on vehicle fleet sizing, which is a complex yet crucial problem. For example, a small fleet size may increase the average wait time, but a large fleet size can also result in traffic congestion. This tradeoff is difficult and can be further exacerbated by profound uncertainty in the manufacturing process. In the literature, the existing models are focused on improving the mean-based performance of AMHS, where the resulting optimal vehicle fleet size is fixed, lacking the ability and flexibility to respond to the changes and/or special requirements that suddenly come up in the manufacturing process. Another drawback with the existing models is that they are not able to characterize the upside/downside risks associated with the resulting vehicle fleet size. This paper, motivated by a real project, presents a novel quantile-based decision model to fill the gap. The adjustment of αα values in the proposed decision model allows for agile vehicle fleet sizing according to the production situations, resulting in the satisfactory performance of AMHS. We develop a simulation optimization solution method, called ES-AMHS in short, to enable the efficient derivation of the optimal vehicle fleet size. A comprehensive numerical analysis is conducted to evaluate the efficiency and efficacy of the solution method. Finally, an empirical study in cooperation with a wafer fab in Taiwan is presented to show the practical usefulness of this methodology in a real-world setting.

    Remember to check out the Most Cited Articles!

    Be inspired by these New Titles in Business & Management today.
    With a wide range of areas, you're bound to find something you like.