The tool planning problem involves determining how many tools should be allocated to each tool group to achieve a set of objectives. Most previous studies assume that a demand mix has been given for a new factory to be planned. However, when a semiconductor company has several existing fabs, the demand mix for the new fab is not explicitly known, and needs to be allocated from the demand mix of the whole company. This paper presents an integrated approach to determine the optimal demand mix and associated tool plan for the new fab that can minimize the tool cost of the new fab while each fab (new or existing) is requested to meet a predefined target in its mean cycle time. Simulation experiments indicate that the proposed solution is better than that obtained by a heuristic method used in industry. The saving in tool cost for a typical tool planning problem can be over US$ 70 million.
|Number of pages||7|
|Journal||International Journal of Advanced Manufacturing Technology|
|State||Published - 1 Nov 2005|
- Capacity planning
- Cycle time
- Genetic algorithm
- Tool planning