Using a Kinematic Model of a Machine Tool to Predict Component Feature Capability

Improved techniques for the characterisation of geometric errors in machine tools and improvements in controller error compensation capability have enabled manufacturers to achieve higher accuracy and better process capability. Apart from the obvious benefit of being able to make more accurate components, there is a significant opportunity to enable a better match between design requirement and machine tool capability. Although product designers and manufacturers are keen to compete for market share through improving product performance and quality, the key driver for market share is now product cost. A major contributor to the cost of manufacture has always been process capability, and a lot of effort is spent designing and refining robust processes. However, too much time is spent on the refining of a part rather than the designing part. In most cases the focus is on fixing the problems after the event rather than designing them out in the first place. Effort is now being directed towards modelling the process and feeding the information into the design at an early stage of the process. By limiting the designer to fixed ranges of feature size and tolerance parameters a more predictable process can be achieved. This predictability then enables more accurate estimates to be made of the cost of achieving the various levels of tolerance. This paper describes work done to demonstrate the prediction of machine capability based on a kinematic model of actual machine parameters. Having done a full machine calibration, machining trials were performed on typical aerospace component features. The test demonstrated good correlation between predicted and measured feature geometry errors.