1 March 1994 Decision support and analysis tool for planning in a semiconductor manufacturing facility
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Abstract
As part of the recently completed Microelectronics Manufacturing Science and Technology (MMST) project, a decision support and analysis tool for planning in a semiconductor manufacturing facility has been developed. Design of the planning system uses an object- oriented approach, and implementation is performed in the Smalltalk programming environment. The system continually maintains a plan for wafer release into a facility, and predicts processing completion dates. The system has been built to run in a distributed environment, allowing simultaneous users in different parts of the facility. The system also provides several types of what-if analysis, both on the existing production plan and on production data. Production plan analysis is used to assist in making operational decisions related to the facility in its current state, such as determining the least disruptive time to take a piece of equipment down for maintenance. Production data analysis, which can be performed independent of the production plan, determines information such as equipment throughput rates to achieve given product cycle-times. All planning is performed using artificial intelligence search techniques, and is based on a time-phased capacity model of the facility. Uncertainty inherent in production data, such as cycle-times, is modeled using fuzzy arithmetic. This tool was used during the final 1000 wafer demonstration for MMST, and is currently being installed in other semiconductor manufacturing facilities. This paper describes the main goals of the planning system, the overall approach to planning and analysis, and a brief description of the current status.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hugh E. Fargher, Richard A. Smith, "Decision support and analysis tool for planning in a semiconductor manufacturing facility", Proc. SPIE 2244, Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry, (1 March 1994); doi: 10.1117/12.169402; https://doi.org/10.1117/12.169402
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