Title
Optimization of the multi-flow rate mode selection for a pneumatic dispensing valve system using clonal selection based artificial immune system algorithm
Abstract
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.
Year
DOI
Venue
2011
10.1109/ICCSCE.2011.6190546
Control System, Computing and Engineering
Keywords
Field
DocType
artificial immune systems,artificial intelligence,cost reduction,filling,flow control,pneumatic control equipment,valves,PWM flow,big flow,clonal selection based artificial immune system algorithm,custom made pneumatic valve,dispensed weight,liquid dispensing process,liquid filling industry,manufacturing process,material cost reduction,modified artificial intelligent technique,multiflow rate mode selection,optimal dispensing speed,optimal liquid dispensing technique,optimal performance,optimization,pneumatic dispensing valve system,simulation program,small flow,spit flow,viscosity,Artificial Immune System,Clonal Selection,Dispensing System,Optimization,Pneumatic Dispensing Valve
Artificial immune system,Flow (psychology),Pulse-width modulation,Algorithm,Mode selection,Control engineering,Flow control (data),Engineering,Clonal selection,Cost reduction,Volumetric flow rate
Conference
ISBN
Citations 
PageRank 
978-1-4577-1640-9
0
0.34
References 
Authors
1
3
Name
Order
Citations
PageRank
Yaw, M.W.100.34
Koh, S.P.200.34
Chong, K.H.300.34