Optimization toolkit for scheduling optimization in semiconductor back-ends
2004
Scheduling optimization of manufacturing processes is becoming more and more important, especially as the complex processes in the semiconductor back-end assign us new tasks. Modern algorithms are known, like genetic algorithms or local search strategies, but often the problem is how to connect the well operating algorithm to the practical problem or more precisely to the simulation model. This paper is about a solution to this issue. We are currently working on a toolset which allows connection of abstract algorithm modules to practical control variables of semiconductor fab simulation models with all of its special constraints like batch sizes, lot splitting or demand volumes. This toolkit is designed to work with the simulation system "simcron MODELLER" and will be used to handle typical optimization tasks like the weekly demand plan of a back-end process or optimal batch sizes for burn-in ovens. It is suitable for educational purposes too, and we are using it in practical courses where students learn more about factory scheduling. The platform independent and object-oriented module concept allows adding new connections or adapters to control variables in a very short time. So the system offers a high reusability for any operating sequence optimization problem in the electronic or semiconductor manufacturing industry.
Keywords:
- Scheduling (computing)
- Semiconductor device fabrication
- Computer science
- Real-time computing
- Genetic algorithm
- Control engineering
- Simulation modeling
- Object-oriented programming
- Manufacturing engineering
- Local search (optimization)
- Optimization problem
- Reusability
- Factory
- Control variable
- Engineering
- Industrial engineering
- Production control
- Correction
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