This grant provides funding for the development of a probabilistic approach to sequential tolerance control in discrete parts manufacturing. This research will make effective use of real-time measurement data to enhance production yield by considering the variability and distributions of the data throughout the different
operations. To accommodate this probabilistic approach, a general method for yield computation will be developed that will provide quick, computationally feasible and accurate estimates of yield. The yield computation method will provide the measure of effectiveness that is necessary to drive an optimization search technique that will be tailored to provide accurate solutions to the probabilistic set point adjustment problem. A data processing module will be developed to identify distribution (statistical) information that is acquired during the production process. Also, techniques will be developed that provide a predictive model for determining the optimum frequency and location of measurements and set point adjustments.
If successful, the results of this research will extend the methodologies of sequential tolerance control and provide a comprehensive framework for a probabilistic approach to sequential set point adjustment. These innovative techniques are used to dynamically reposition the set points of process plan operations to
optimize the production of acceptable parts. These techniques are especially beneficial in the production of complex low-volume, high-value-added machined parts, and the results of this research will make available an integrated set of tools and solution methodologies for this class of problems. The data processing module
will provide an effective way to utilize the measurements returned by advanced metrology equipment such as coordinate measuring machines and machine tool mounted probes. The predictive model for determining the optimum frequency and location of set point adjustments will provide a way of reducing the cost associated with sequential tolerance control while still allowing significant yield improvement.
|Effective start/end date||9/1/99 → 8/31/02|
- National Science Foundation: $153,690.00