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Mathematical Sciences, Technology, and Economic Competitiveness
in the process of planning viable repair and maintenance facilities, especially if the facilities are complex, involving multiple work stations, sources of supplies, and so on. The same considerations apply as well to the design of manufacturing facilities. The initial consideration is feasibility: will the proposed facility function well, in terms of costs, inventory, and production cycle time? Once feasibility is established, simulations provide invaluable information regarding facility design, deployment, and use of machinery, parts, and personnel. After an optimally designed facility has been built, further simulations allow final adjustment of operating procedures to achieve optimal performance.
Consider the case of United Airlines, faced with the problem of turbine blade repair. Although the general image of aircraft repair may be one of mechanics swarming over planes, in what constitutes a job shop approach, in actuality there may be significant cost savings in establishing specialized facilities to ''remanufacture'' certain standard parts. United decided to establish such a dedicated facility to remanufacture turbine blades. The facility was expected to cost $15 million. An initial feasibility study was undertaken to determine whether the dedicated facility would function better than the job shop in terms of costs, inventory, and repair cycle time. The simulations were based on probability models for distributions of demand for repaired blades, supplies of defective blades, and the progression of repair through the remanufacturing stages of the facility. Once feasibility was established, simulations allowed optimal balance of all production and repair machinery. After the construction of this optimally designed facility, the actual operation gave rise to additional data in terms of revised probability measures in the simulation model, which allowed further simulations, to achieve improved performance.
The economic leverage of these simulations is considerable, as a small investment in simulation can save many hundreds of thousands of dollars on a project of the size discussed above.