An hierarchical model for FMS control.

Abstract

Flexible Manufacturing Systems (FMSs) are usually composed of general purpose machines with automatic tool changing capability and integrated material handling. FMSs offer the advantages of high utilization levels and simultaneous production of a variety of part types with minimal changeover time. The complexity of FMSs however requires sophisticated control. In this dissertation a four level control hierarchy along with computationally feasible control algorithms for each level is presented. Decisions are made at each level utilizing the flexibility inherent in FMSs. The proposed scheme has the advantages of ensuring satisfaction of higher level decisions as lower level operating decisions are made, and allows performance and status data collected at lower levels to be fed back and influence future high level decisions. The top level is concerned with the choice of part types and volumes to be assigned to the FMS over the next several months. Within this horizon, production volumes are planned for each period, a period typically being between a week and a month in length. A linear programming model is used for planning at this level. The second level plans daily or shift production. Advantage is taken of the FMSs ability to be configured to respond to different part mixes to allocate tools to machines so as to minimize holding costs. Separate mathematical programming models are formulated to match various FMS environments. A heuristic for solution of a model of an automated production flexible environment is detailed. Computational results are presented. Extensions of this heuristic to other environments are outlined. The third level determines process routes for each part type in order to minimize material handling. Additional tools are loaded on machines when possible to maximize alternate routings, and using the flexibility offered by FMSs to process parts along alternate routes, routing assignments are made to minimize workload assignment. These routing assignments are used by level four for actual routing, sequencing and material handling path control. The level three model is formulated as a linear program and heuristics are used for level four. An example is provided to illustrate the completeness of the decision hierarchy and the relationships between levels.