The use of automated process planning to minimise unit cost whilst retaining flexibility of manufacturing method
The use of automated process planning to minimise unit cost whilst retaining flexibility of manufacturing method
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.
University of Southampton
Cooper, David Stephen
0b4ecdad-664b-4e94-b51e-920c13080cfc
August 2016
Cooper, David Stephen
0b4ecdad-664b-4e94-b51e-920c13080cfc
Scanlan, James
7ad738f2-d732-423f-a322-31fa4695529d
Cooper, David Stephen
(2016)
The use of automated process planning to minimise unit cost whilst retaining flexibility of manufacturing method.
University of Southampton, Doctoral Thesis, 294pp.
Record type:
Thesis
(Doctoral)
Abstract
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.
Text
Cooper Thesis 2017 April 20
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Published date: August 2016
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Local EPrints ID: 413583
URI: http://eprints.soton.ac.uk/id/eprint/413583
PURE UUID: 7b46a071-d176-4605-8b06-64040d8ab024
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Date deposited: 29 Aug 2017 16:30
Last modified: 16 Mar 2024 05:29
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Author:
David Stephen Cooper
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