Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm
This paper presents a new approach to the tolerance synthesis of the component parts of assemblies by simultaneously optimizing three manufacturing parameters: manufacturing cost, including tolerance cost and quality loss cost; machining time; and machine overhead/idle time cost. A methodology has b...
| Main Authors: | , , , |
|---|---|
| Format: | Journal Article |
| Published: |
Springer U K
2012
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/32856 |
| _version_ | 1848753779757809664 |
|---|---|
| author | Geetha, K. Ravindran, D. Siva Kumar, M. Islam, Mohammad Nazrul |
| author_facet | Geetha, K. Ravindran, D. Siva Kumar, M. Islam, Mohammad Nazrul |
| author_sort | Geetha, K. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper presents a new approach to the tolerance synthesis of the component parts of assemblies by simultaneously optimizing three manufacturing parameters: manufacturing cost, including tolerance cost and quality loss cost; machining time; and machine overhead/idle time cost. A methodology has been developed using the Genetic Algorithm (GA) technique to solve this multi-objective optimization problem. The effectiveness of the proposed methodology has been demonstrated by solving a wheel mounting assembly problem consisting of five components, two subassemblies, two critical dimensions, two functional tolerances, and eight operations. Significant cost saving can be achieved by employing this methodology. |
| first_indexed | 2025-11-14T08:29:57Z |
| format | Journal Article |
| id | curtin-20.500.11937-32856 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:29:57Z |
| publishDate | 2012 |
| publisher | Springer U K |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-328562017-09-13T15:51:39Z Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm Geetha, K. Ravindran, D. Siva Kumar, M. Islam, Mohammad Nazrul and manufacturing processes tolerance cost models normalization optimization techniques tolerance synthesis This paper presents a new approach to the tolerance synthesis of the component parts of assemblies by simultaneously optimizing three manufacturing parameters: manufacturing cost, including tolerance cost and quality loss cost; machining time; and machine overhead/idle time cost. A methodology has been developed using the Genetic Algorithm (GA) technique to solve this multi-objective optimization problem. The effectiveness of the proposed methodology has been demonstrated by solving a wheel mounting assembly problem consisting of five components, two subassemblies, two critical dimensions, two functional tolerances, and eight operations. Significant cost saving can be achieved by employing this methodology. 2012 Journal Article http://hdl.handle.net/20.500.11937/32856 10.1007/s00170-012-4662-6 Springer U K fulltext |
| spellingShingle | and manufacturing processes tolerance cost models normalization optimization techniques tolerance synthesis Geetha, K. Ravindran, D. Siva Kumar, M. Islam, Mohammad Nazrul Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm |
| title | Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm |
| title_full | Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm |
| title_fullStr | Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm |
| title_full_unstemmed | Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm |
| title_short | Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm |
| title_sort | multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm |
| topic | and manufacturing processes tolerance cost models normalization optimization techniques tolerance synthesis |
| url | http://hdl.handle.net/20.500.11937/32856 |