A greedy heuristic for locating crossovers in conveyor-based AMHS in wafer fabs

Authors:
Andrew Johnson;Hector J. Carlo;Jesus A. Jimenez;Dima Nazzal;Vernet Lasrado
Affiliations:
Texas A&M University, College Station, Texas;University of Puerto Rico-Mayagüez, Mayaguez, PR;Texas State University-San Marcos, San Marcos, TX;University of Central Florida, Orlando, FL;University of Central Florida, Orlando, FL
Venue:
Winter Simulation Conference
Year:
2009

Citing 3
Cited 3

Semiconductor fabrication facility design using a hybrid search methodology

Computers and Industrial Engineering
Survey of research in modeling conveyor-based automated material handling systems in wafer fabs

Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
An analytical model for conveyor based amhs in semiconductor wafer fabs

Proceedings of the 40th Conference on Winter Simulation

Simulating conveyor-based AMHS layout configurations in small wafer lot manufacturing environments

Proceedings of the Winter Simulation Conference
Design of a manufacturing facility layout with a closed loop conveyor with shortcuts using queueing theory and genetic algorithms

Proceedings of the Winter Simulation Conference
Enhancing simulation as a decision-making support tool for a cross-docking center in a dynamic retail-distribution environment

Proceedings of the Winter Simulation Conference

Quantified Score

Hi-index	0.01

Visualization

Abstract

Finding the optimal layout of Automated Material Handling Systems (AMHS) is critical for the design of next generation semiconductor wafer fabs. This paper proposes a greedy heuristic to determine the configuration of a conveyor-based AMHS featuring turntables and crossovers. Using a conveyor-based analytical model, the heuristic identifies the crossover that provides the greater benefit in terms of work-in process and delivery time reduction. The virtual SEMATECH 300 mm fab is used to demonstrate the application of the heuristic. Numerical results show that adding crossovers reduced the system's delivery time by up to 22-percent in the scenarios under consideration.