A fixture repeatability and reproducibility measure to predict the quality of machined parts

The production of high quality parts in a flexible manufacturing system is obtained by careful monitoring and control of various operating inputs such as manufacturing processes, fixtures, and gauges that are required to produce these parts. This research focuses on the performance of machining fixtures and develops a measure called the Fixture Repeatability and Reproducibility Measure (FR-R) to evaluate the performance of machining fixtures. This FR-R measure quantifies the variability of a part dimension that is contributed by the fixture under static loading conditions. This measure was used to evaluate the performance of two different fixtures that were utilized to produce two different parts. One part was machined only in parallel planes after location and clamping on the fixture. The second part, of a different geometry, was located and clamped in a different fixture, and then machined in mutually perpendicular planes. An investigation of data for the first part revealed that the FR-R detected the existence of fixture malfunctions. After the fixture was repaired, fresh measurements and further analysis with this FR-R measure revealed inherent problems in the manufacturing process that were addressed by redesigning the part and fixture for the next generation of product. The FR-R measure on the second part confirmed that the current performance of the fixture was satisfactory and matched the historical performance of the fixture. The conclusion was made that this FR-R measure was not only viable, but also desirable. For example, this measure facilitated pre-production evaluation of machining fixtures. Further, the FR-R measure is generated by using an off-line coordinate measuring machine to evaluate fixtures; thus minimizing the use of expensive production machines to do the same job. Finally, this measure showed that it could be used to monitor fixture performance during production, and prevent the production of scrap parts. In summary, this FR-R measure could be used to predict the quality of machined parts in a flexible manufacturing environment.