Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Response Surface Methodology based Desirability Approach for Optimization of Roller Burnishing Process Parameter
Abstract In the present study, an optimization of roller burnishing process in CNC machining centre has been discussed using response surface methodology (RSM) collectively with desirability function approach (DFA). Response surface methodology is a statistical technique used to model and optimize the response. Using a rotatable central composite design (CCD) of RSM, model was developed to predict surface roughness. Burnishing speed, Interference, Feed and No of tool pass were considered as model variables to develop the predictive models. Experiments were conducted on Aluminium alloy 6061 work material based on five-level design with spindle speed, interference, feed, and number of tool pass as model variables to develop the predictive models. The results indicated that Interference and feed were the most significant factors on the surface roughness. The validity of the predicted model has been confirmed by performing verification experiments under the optimal conditions. Results of the experimentation at the optimum process parameter combination confirm the effectiveness of the developed model using response surface method for optimum burnishing parameters.
Response Surface Methodology based Desirability Approach for Optimization of Roller Burnishing Process Parameter
Abstract In the present study, an optimization of roller burnishing process in CNC machining centre has been discussed using response surface methodology (RSM) collectively with desirability function approach (DFA). Response surface methodology is a statistical technique used to model and optimize the response. Using a rotatable central composite design (CCD) of RSM, model was developed to predict surface roughness. Burnishing speed, Interference, Feed and No of tool pass were considered as model variables to develop the predictive models. Experiments were conducted on Aluminium alloy 6061 work material based on five-level design with spindle speed, interference, feed, and number of tool pass as model variables to develop the predictive models. The results indicated that Interference and feed were the most significant factors on the surface roughness. The validity of the predicted model has been confirmed by performing verification experiments under the optimal conditions. Results of the experimentation at the optimum process parameter combination confirm the effectiveness of the developed model using response surface method for optimum burnishing parameters.
Response Surface Methodology based Desirability Approach for Optimization of Roller Burnishing Process Parameter
Patel, Kirankumar Ambalal (Autor:in) / Brahmbhatt, Pragnesh Kantilal (Autor:in)
Journal of The Institution of Engineers (India): Series C ; 99 ; 729-736
22.05.2017
8 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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