Optimization of the multi-flow rate mode selection for a pneumatic dispensing valve system using clonal selection based artificial immune system algorithm
Liquid filling industry needs optimal liquid dispensing technique in their manufacturing process in order to increases the production as well to reduce the material cost. This can be achieved by a custom made pneumatic valve where it has the capabilities of producing big flow, small flow, PWM flow a...
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my.uniten.dspace-58162018-01-03T07:54:27Z Optimization of the multi-flow rate mode selection for a pneumatic dispensing valve system using clonal selection based artificial immune system algorithm Yaw, M.W. Koh, S.P. Chong, K.H. Liquid filling industry needs optimal liquid dispensing technique in their manufacturing process in order to increases the production as well to reduce the material cost. This can be achieved by a custom made pneumatic valve where it has the capabilities of producing big flow, small flow, PWM flow and spit flow in the dispensing process. This paper presents a modified artificial intelligent technique to optimize the selection of the flow rate to complete the liquid dispensing process with the most optimal dispensing speed and the accuracy of the dispensed weight. Clonal Selection based Artificial Immune System is used to determine the most optimal performance of the system. The developed algorithm is tested on the simulation program where it is used to control the dispensing valve to dispense the liquid with various viscosities. The experiment results are encouraged. © 2011 IEEE. 2017-12-08T07:26:24Z 2017-12-08T07:26:24Z 2011 Conference Paper 10.1109/ICCSCE.2011.6190546 en_US Proceedings - 2011 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2011 2011, Article number 6190546, Pages 327-331 |
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Liquid filling industry needs optimal liquid dispensing technique in their manufacturing process in order to increases the production as well to reduce the material cost. This can be achieved by a custom made pneumatic valve where it has the capabilities of producing big flow, small flow, PWM flow and spit flow in the dispensing process. This paper presents a modified artificial intelligent technique to optimize the selection of the flow rate to complete the liquid dispensing process with the most optimal dispensing speed and the accuracy of the dispensed weight. Clonal Selection based Artificial Immune System is used to determine the most optimal performance of the system. The developed algorithm is tested on the simulation program where it is used to control the dispensing valve to dispense the liquid with various viscosities. The experiment results are encouraged. © 2011 IEEE. |
format |
Conference Paper |
author |
Yaw, M.W. Koh, S.P. Chong, K.H. |
spellingShingle |
Yaw, M.W. Koh, S.P. Chong, K.H. Optimization of the multi-flow rate mode selection for a pneumatic dispensing valve system using clonal selection based artificial immune system algorithm |
author_facet |
Yaw, M.W. Koh, S.P. Chong, K.H. |
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Yaw, M.W. |
title |
Optimization of the multi-flow rate mode selection for a pneumatic dispensing valve system using clonal selection based artificial immune system algorithm |
title_short |
Optimization of the multi-flow rate mode selection for a pneumatic dispensing valve system using clonal selection based artificial immune system algorithm |
title_full |
Optimization of the multi-flow rate mode selection for a pneumatic dispensing valve system using clonal selection based artificial immune system algorithm |
title_fullStr |
Optimization of the multi-flow rate mode selection for a pneumatic dispensing valve system using clonal selection based artificial immune system algorithm |
title_full_unstemmed |
Optimization of the multi-flow rate mode selection for a pneumatic dispensing valve system using clonal selection based artificial immune system algorithm |
title_sort |
optimization of the multi-flow rate mode selection for a pneumatic dispensing valve system using clonal selection based artificial immune system algorithm |
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2017 |
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1644493783281172480 |
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13.214268 |