ANN and RSM approach for modelling and multi objective optimization of abrasive water jet machining process
Abrasive Water Jet Machining is one of the novel nontraditional cutting processes found diverse applications in machining different kinds of difficult-to-machine materials. Process parameters play an important role in finding the economics of machining process at good quality. This research focused...
| 發表在: | Decision Science Letters |
|---|---|
| Main Authors: | , , , |
| 格式: | Article |
| 語言: | 英语 |
| 出版: |
Growing Science
2018-09-01
|
| 主題: | |
| 在線閱讀: | http://www.growingscience.com/dsl/Vol7/dsl_2017_36.pdf |
| _version_ | 1856887735023828992 |
|---|---|
| author | Srinath Reddy N. Dinesh Tirumala Rajyalakshmi Gajjela Raja Das |
| author_facet | Srinath Reddy N. Dinesh Tirumala Rajyalakshmi Gajjela Raja Das |
| author_sort | Srinath Reddy N. |
| collection | DOAJ |
| container_title | Decision Science Letters |
| description | Abrasive Water Jet Machining is one of the novel nontraditional cutting processes found diverse applications in machining different kinds of difficult-to-machine materials. Process parameters play an important role in finding the economics of machining process at good quality. This research focused on the predictive models for explaining the functional relationship between input and output parameters of AWJ machining process. No single set of parametric combination of machining variables can suggest the better responses concurrently, due to its conflicting nature. Hence, an approach of Multi-objective has been attempted for the best combination of process parameters by modelling AWJM process using of ANN. It served a set of optimal process parameters to AWJ machining process, which shows a development with an enhanced productivity. Wide set of trail experiments have been considered with a broader range of machining parameters for modelling and, then, for validating. The model is capable of predicting optimized responses. |
| format | Article |
| id | doaj-art-4df152dbec6a4e3f8a87ed0ba91fcf49 |
| institution | Directory of Open Access Journals |
| issn | 1929-5804 1929-5812 |
| language | English |
| publishDate | 2018-09-01 |
| publisher | Growing Science |
| record_format | Article |
| spelling | doaj-art-4df152dbec6a4e3f8a87ed0ba91fcf492025-08-19T20:29:38ZengGrowing ScienceDecision Science Letters1929-58041929-58122018-09-017453554810.5267/j.dsl.2017.11.003ANN and RSM approach for modelling and multi objective optimization of abrasive water jet machining processSrinath Reddy N.Dinesh TirumalaRajyalakshmi GajjelaRaja Das Abrasive Water Jet Machining is one of the novel nontraditional cutting processes found diverse applications in machining different kinds of difficult-to-machine materials. Process parameters play an important role in finding the economics of machining process at good quality. This research focused on the predictive models for explaining the functional relationship between input and output parameters of AWJ machining process. No single set of parametric combination of machining variables can suggest the better responses concurrently, due to its conflicting nature. Hence, an approach of Multi-objective has been attempted for the best combination of process parameters by modelling AWJM process using of ANN. It served a set of optimal process parameters to AWJ machining process, which shows a development with an enhanced productivity. Wide set of trail experiments have been considered with a broader range of machining parameters for modelling and, then, for validating. The model is capable of predicting optimized responses.http://www.growingscience.com/dsl/Vol7/dsl_2017_36.pdfAWJMResponse surface methodologyArtificial neural networkModelingOptimization |
| spellingShingle | Srinath Reddy N. Dinesh Tirumala Rajyalakshmi Gajjela Raja Das ANN and RSM approach for modelling and multi objective optimization of abrasive water jet machining process AWJM Response surface methodology Artificial neural network Modeling Optimization |
| title | ANN and RSM approach for modelling and multi objective optimization of abrasive water jet machining process |
| title_full | ANN and RSM approach for modelling and multi objective optimization of abrasive water jet machining process |
| title_fullStr | ANN and RSM approach for modelling and multi objective optimization of abrasive water jet machining process |
| title_full_unstemmed | ANN and RSM approach for modelling and multi objective optimization of abrasive water jet machining process |
| title_short | ANN and RSM approach for modelling and multi objective optimization of abrasive water jet machining process |
| title_sort | ann and rsm approach for modelling and multi objective optimization of abrasive water jet machining process |
| topic | AWJM Response surface methodology Artificial neural network Modeling Optimization |
| url | http://www.growingscience.com/dsl/Vol7/dsl_2017_36.pdf |
| work_keys_str_mv | AT srinathreddyn annandrsmapproachformodellingandmultiobjectiveoptimizationofabrasivewaterjetmachiningprocess AT dineshtirumala annandrsmapproachformodellingandmultiobjectiveoptimizationofabrasivewaterjetmachiningprocess AT rajyalakshmigajjela annandrsmapproachformodellingandmultiobjectiveoptimizationofabrasivewaterjetmachiningprocess AT rajadas annandrsmapproachformodellingandmultiobjectiveoptimizationofabrasivewaterjetmachiningprocess |