Simulations-based and solver-based optimization approaches for batch processes in semiconductor manufacturing

Authors:
Andreas Klemmt;Sven Horn;Gerald Weigert;Thomas Hielscher
Affiliations:
Technische Universität Dresden, Dresden, Germany;Technische Universität Dresden, Dresden, Germany;Technische Universität Dresden, Dresden, Germany;Qimonda, Dresden, Germany
Venue:
Proceedings of the 40th Conference on Winter Simulation
Year:
2008

Citing 2
Cited 2

Alternative loading and dispatching policies for furnace operations in semiconductor manufacturing: a comparison by simulation

Proceedings of the 32nd conference on Winter simulation
Semiconductor manufacturing: using simulation-based scheduling to maximize demand fulfillment in a semiconductor assembly facility

Proceedings of the 34th conference on Winter simulation: exploring new frontiers

Evaluation of modeling, simulation and optimization approaches for work flow management in semiconductor manufacturing

Winter Simulation Conference
A comparison of mip-based decomposition techniques and VNS approaches for batch scheduling problems

Winter Simulation Conference

Quantified Score

Hi-index	0.00

Visualization

Abstract

Scheduling is one of the key factors for semiconductor fabrication productivity. Objectives like lot cycle time and throughput must be optimized to push the technological development and secure the existence on the rapid growing global market. But especially in the frontend the manufacturing process is dominated by cluster-tools and reentrance flows which makes a production planning and optimization very hard. The workflow here is mostly controlled only by dispatch rules. To get a further improvement in manufacturing planning strategies, there is an increasing request of exact or simulation-based solution methods for specified work centers or bottleneck machine groups. One example of this is the semiconductor oven process. Here, complex batch processes with a lot of restrictions have to be scheduled. A reduction of cycle time in this section by optimized manufacturing strategies has a great influence on all global optimization objectives. Two approaches are investigated in this paper.