This research focussed on the automatic generation of the optimal method of manufacture, and the cost thereof, at an early stage in design. It used geometric and tolerance data, combined with a database of centrally stored manufacturing knowledge. This allowed the construction of potential manufacturing routes, and the evaluation of their cost. In order to find the least costly method of manufacture for a given component, with defined geometry and tolerance, it is necessary to take a holistic view of the manufacturing process. This thesis shows that the typical sequential approach of choosing the manufacturing process, followed by sequencing, will not necessarily find the global optimum. Dynamic process seletion is required to consider both the choice of manufacturing processes and the sequence together to avoid sub-optimisation. Backward and forward propagation from a final manufacturing process, using a random mutation hill climber, was used to construct potential manufacturing process sets. For each process set constructed, the inner optimisation loop was used to find the optimal sequence of manufacturing operations, with the aid of a repair operator to ensure feasibility. Prior to finding the optimal manufacturing sequence, the forming shape for all potential forming processes was required; this research encompasses a methodology to automatically deduce this shape. This methodology demonstrated convergence to the global optimum on a contrived test case, and has demonstrated accurate results on a real commercial test case. Major areas for improvement could be a combination of the developed methodology with feature recognition, to enable maximum usefulness as a fully automated process planning and cost evaluation tool. In summary this research demonstrates that the lack of a holistic view can cause sub-optimal results, and proposes a methodology which provides a holistic perspective. The methodology has been proved to be accurate, generic and expandable.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:722885 |
| Date | January 2016 |
| Creators | Cooper, David Stephen |
| Contributors | Scanlan, James |
| Publisher | University of Southampton |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://eprints.soton.ac.uk/413583/ |
Page generated in 0.0019 seconds