This study aims to examine the usability of environmentally harmless vegetable oil in the minimum quantity of lubrication(MQL)system in face milling of AISI O2 steel and to optimize the cutting parameters by different...This study aims to examine the usability of environmentally harmless vegetable oil in the minimum quantity of lubrication(MQL)system in face milling of AISI O2 steel and to optimize the cutting parameters by different statistical methods.Vegetable oil was preferred as cutting fluid,and Taguchi method was used in the preparation of the test pattern.After testing with the prepared test pattern,cutting performance in all parameters has been improved according to dry conditions thanks to the MQL system.The highest tool life was obtained by using cutting parameters of 7.5 m cutting length,100 m/min cutting speed,100 mL/h MQL flow rate and 0.1 mm/tooth feed rate.Optimum cutting parameters were determined according to the Taguchi analysis,and the obtained parameters were confirmed with the verification tests.In addition,the optimum test parameter was determined by applying the gray relational analysis method.After using ANOVA analysis according to the measured surface roughness and cutting force values,the most effective cutting parameter was observed to be the feed rate.In addition,the models for surface roughness and cutting force values were obtained with precisions of 99.63%and 99.68%,respectively.Effective wear mechanisms were found to be abrasion and adhesion.展开更多
Taguchi method with grey relational analysis was used to optimize the machining parameters with multiple performance characteristics in drilling hybrid metal matrix A1356/SiC-mica composites. Experiments were conducte...Taguchi method with grey relational analysis was used to optimize the machining parameters with multiple performance characteristics in drilling hybrid metal matrix A1356/SiC-mica composites. Experiments were conducted on a computer numerical control vertical machining centre and Lzs orthogonal array was chosen for the experiments. The drilling parameters namely spindle speed, feed rate, drill type and mass fraction of mica were optimized based on the multiple performance characteristics including thrust force, surface roughness, tool wear and burr height （exit）. The results show that the feed rate and the type of drill are the most significant factors which affect the drilling process and the performance in the drilling process can be effectively improved by using this approach.展开更多
The wear behavior of multi-walled carbon nano-tubes(MWCNTs)reinforced copper metal matrix composites(MMCs)processed through powder metallurgy(PM)route was focused on and further investigated for varying MWCNT quantity...The wear behavior of multi-walled carbon nano-tubes(MWCNTs)reinforced copper metal matrix composites(MMCs)processed through powder metallurgy(PM)route was focused on and further investigated for varying MWCNT quantity viaexperimental,statistical and artificial neural network(ANN)techniques.Microhardness increases with increment in MWCNTquantity.Wear loss against varying load and sliding distance was analyzed as per L16orthogonal array using a pin-on-disctribometer.Process parameter optimization by Taguchi’s method revealed that wear loss was affected to a greater extent by theintroduction of MWCNT;this wear resistant property of newer composite was further analyzed and confirmed through analysis ofvariance(ANOVA).MWCNT content(76.48%)is the most influencing factor on wear loss followed by applied load(12.18%)andsliding distance(9.91%).ANN model simulations for varying hidden nodes were tried out and the model yielding lower MAE valuewith3-7-1network topology is identified to be reliable.ANN model predictions with R value of99.5%which highly correlated withthe outcomes of ANOVA were successfully employed to investigate individual parameter’s effect on wear loss of Cu?MWCNTMMCs.展开更多
Optimization of an automotive body structure faces the difficulty of having too many design variables and a too large design search space. A simplified model of body-in-prime(BIP) can solve this difficulty by reducing...Optimization of an automotive body structure faces the difficulty of having too many design variables and a too large design search space. A simplified model of body-in-prime(BIP) can solve this difficulty by reducing the number of design variables. In this study, to achieve lighter weight and higher stiffness, the simplified model of BIP was developed and combined with an optimization procedure;consequently, optimal designs of automotive body B-pillar were produced. B-pillar was divided into four quarters and each quarter was modelled by one simplified beam. In the optimization procedure, depth, width, and thickness of the simplified beams were considered as the design variables.Weight, bending and torsional stiffness were also considered as objective functions. The optimization procedure is composed of six stages: designing the experiments, calculating grey relational grade, calculating signal-to noise ratio,finding an optimum design using Taguchi grey relational analysis, performing sensitivity analysis using analysis of variance(ANOVA) and performing non-dominated sorting and multi-criteria decision making. The results show that the width of lower B-pillar has the highest effect(about 55%) and the obtained optimum design point could reduce the weight of B-pillar by about 40% without reducing the BIP stiffness by more than 1.47%.展开更多
文摘This study aims to examine the usability of environmentally harmless vegetable oil in the minimum quantity of lubrication(MQL)system in face milling of AISI O2 steel and to optimize the cutting parameters by different statistical methods.Vegetable oil was preferred as cutting fluid,and Taguchi method was used in the preparation of the test pattern.After testing with the prepared test pattern,cutting performance in all parameters has been improved according to dry conditions thanks to the MQL system.The highest tool life was obtained by using cutting parameters of 7.5 m cutting length,100 m/min cutting speed,100 mL/h MQL flow rate and 0.1 mm/tooth feed rate.Optimum cutting parameters were determined according to the Taguchi analysis,and the obtained parameters were confirmed with the verification tests.In addition,the optimum test parameter was determined by applying the gray relational analysis method.After using ANOVA analysis according to the measured surface roughness and cutting force values,the most effective cutting parameter was observed to be the feed rate.In addition,the models for surface roughness and cutting force values were obtained with precisions of 99.63%and 99.68%,respectively.Effective wear mechanisms were found to be abrasion and adhesion.
基金SCSVMV University, Kanchipuram,India for funding and supporting this research work
文摘Taguchi method with grey relational analysis was used to optimize the machining parameters with multiple performance characteristics in drilling hybrid metal matrix A1356/SiC-mica composites. Experiments were conducted on a computer numerical control vertical machining centre and Lzs orthogonal array was chosen for the experiments. The drilling parameters namely spindle speed, feed rate, drill type and mass fraction of mica were optimized based on the multiple performance characteristics including thrust force, surface roughness, tool wear and burr height （exit）. The results show that the feed rate and the type of drill are the most significant factors which affect the drilling process and the performance in the drilling process can be effectively improved by using this approach.
文摘The wear behavior of multi-walled carbon nano-tubes(MWCNTs)reinforced copper metal matrix composites(MMCs)processed through powder metallurgy(PM)route was focused on and further investigated for varying MWCNT quantity viaexperimental,statistical and artificial neural network(ANN)techniques.Microhardness increases with increment in MWCNTquantity.Wear loss against varying load and sliding distance was analyzed as per L16orthogonal array using a pin-on-disctribometer.Process parameter optimization by Taguchi’s method revealed that wear loss was affected to a greater extent by theintroduction of MWCNT;this wear resistant property of newer composite was further analyzed and confirmed through analysis ofvariance(ANOVA).MWCNT content(76.48%)is the most influencing factor on wear loss followed by applied load(12.18%)andsliding distance(9.91%).ANN model simulations for varying hidden nodes were tried out and the model yielding lower MAE valuewith3-7-1network topology is identified to be reliable.ANN model predictions with R value of99.5%which highly correlated withthe outcomes of ANOVA were successfully employed to investigate individual parameter’s effect on wear loss of Cu?MWCNTMMCs.
文摘Optimization of an automotive body structure faces the difficulty of having too many design variables and a too large design search space. A simplified model of body-in-prime(BIP) can solve this difficulty by reducing the number of design variables. In this study, to achieve lighter weight and higher stiffness, the simplified model of BIP was developed and combined with an optimization procedure;consequently, optimal designs of automotive body B-pillar were produced. B-pillar was divided into four quarters and each quarter was modelled by one simplified beam. In the optimization procedure, depth, width, and thickness of the simplified beams were considered as the design variables.Weight, bending and torsional stiffness were also considered as objective functions. The optimization procedure is composed of six stages: designing the experiments, calculating grey relational grade, calculating signal-to noise ratio,finding an optimum design using Taguchi grey relational analysis, performing sensitivity analysis using analysis of variance(ANOVA) and performing non-dominated sorting and multi-criteria decision making. The results show that the width of lower B-pillar has the highest effect(about 55%) and the obtained optimum design point could reduce the weight of B-pillar by about 40% without reducing the BIP stiffness by more than 1.47%.
