Abstract
In a wafer fabrication facility, automated material handling system (AMHS) to dispatch the material flow is a critical and challenging task. This paper investigates the integrated delivery of automated material handling system (AMHS) and processing tools for a large-scale complex wafer fabrication facility. Although the dispatching rules are one of the most frequently used approach for effective semiconductor manufacturing schedule, it is necessary to adapt new techniques due to time-consuming nature of dispatching rules when the number of variables and iterations increases. There are very few studies on enhancing the rule-based scheduling system. To address this issue, we proposed an evolutionary algorithmic approach for enhancing the rule-based scheduling system. We explored the best possible genetic algorithm parameters from famous approach called Taguchi, and then, statistical analysis, i.e., regression analysis, has been conducted to find out the significance of the parameters. Later, with hierarchical rule-based scheduling approach, the combined sequential dispatching rules are formed to achieve better efficiency and effectiveness of the scheduling.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chang YJ. Multi-objective scheduling for IC sort and test with a simulation test bed. IEEE Tran Semi Cond Manuf. 1998;11(2):304-15.
Li L, Qiao F, Jiang H. The research on dispatching rules for improving on time delivery for semi conductor wafer fab. In: 8th International Conference on Control, Aero Machine, Robotics and Vision ICARCV, 2004, p. 404–4.
Wu MC, Huag Y, Chang VC, Yang KF. Dispatching in semi conductor with machine-dedication features. Int J Adv Manuf Techhnol. 2006;28(9):978–84.
Chen JC, Chen KH, Wu JJ, Chen CW. A study of the flexible job shop scheduling problem with parallel machine and re-entrant process. Int J of Adv Manuf Technol. 2008;39(3–4):344–5.
Baek DH, Yoon WC, Part SC. A special rule adaptation procedure for reliable production control in a wafer fabrication system. Int J Pro Res. 1998;36(6):147–9.
Can B, Hevey C. A comparison of genetic programming and artificial neural networks in meta-modelling of discrete events simulation models. Comp OR. 2012;39(2):424–36.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer India
About this paper
Cite this paper
Manupati, V.K., Revanth, A.S., Srikanth, K.S.S.L., Maheedhar, A., Sreekara Reddy, M.B.S. (2016). Real-Time Rule-Based Scheduling System for Integrated Delivery in a Semiconductor Manufacturing Using Evolutionary Algorithm-Based Simulation Approach. In: Dash, S., Bhaskar, M., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 394. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2656-7_90
Download citation
DOI: https://doi.org/10.1007/978-81-322-2656-7_90
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2654-3
Online ISBN: 978-81-322-2656-7
eBook Packages: EngineeringEngineering (R0)