Response Surface Methodology and Genetic Algorithm used to Optimize the Cutting condition for Surface Roughness Parameters in CNC Turning

Routara, Bharat Chandra; Sahoo, Ashok Kumar; Parida, A.K.; Padhi, Puja

doi:10.1016/j.proeng.2012.06.232

Cited by 32 publications

(12 citation statements)

References 9 publications

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“…Sometimes the input variables are also called independent variables. RSM is mostly used to analyze the influence of input parameters on the specific responses (Routara et al, 2012). This method can also be used to define the contribution of the independent variables (input parameters) on the desired responses (output parameters).…”

Section: Response Surface Methodology (Rsm)mentioning

confidence: 99%

Modeling and optimization of surface roughness and tool vibration in CNC turning of Aluminum alloy using hybrid RSM-WPCA methodology

Sahoo¹,

Pratap²,

Bandyopadhyay³

2017

10.5267/j.ijiec

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This paper suggests an advanced hybrid multi output optimization technique by applying weighted principal component analysis (WPCA) incorporated with response surface methodology (RSM). This investigation has been carried out through a case study in CNC turning of Aluminum alloy 63400 for surface roughness (Ra) and tool vibration (db) optimization. Primarily, input parameters such as spindle speed (N), feed rate (S) and depth of cut (t) are designed for experiment by using RSM Box-Behnken methodology. The aluminum alloy workpieces are machined by using coated carbide tool (inserts) in dry environment. Secondly, the empirical model for the responses as the functions of cutting parameters are obtained through RSM technique and the adequacy of the models have been checked using analysis of variance (ANOVA). Finally, the process parameters are optimized using WPCA technique. The confirmatory experiment has been performed using optimized result and it reveals that multiple response performance index (MPI) value was increased by 0.2908 from initial setting. The increases in MPI value indicates that the aforesaid optimization methodology is suitably acceptable for multi response optimization for turning process.

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Section: Response Surface Methodology (Rsm)mentioning

confidence: 99%

Modeling and optimization of surface roughness and tool vibration in CNC turning of Aluminum alloy using hybrid RSM-WPCA methodology

Sahoo¹,

Pratap²,

Bandyopadhyay³

2017

10.5267/j.ijiec

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“…Initial population consists of sets of chromosomes. The chromosomes evolve during several iterations called generations [54]. The best individuals are evaluated, recombined and mutated to constitute a new population.…”

Section: Significance Of Input Parametersmentioning

confidence: 99%

“…The crossover split into two chromosomes and then combines one half of each chromosome with the other pair. Mutation involves flipping a single bit of chromosomes [54]. The chromosomes are then evaluated against certain fitness criteria and the best ones are retained while the others are rejected.…”

Section: Significance Of Input Parametersmentioning

confidence: 99%

Multi-objective optimization of minimum quantity lubrication in end milling of aluminum alloy AA6061T6

Najiha

Rahman²,

Kadirgama³

et al. 2015

Int. J. Automot. Mech. Eng.

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The purpose of this research is to optimize the process of minimum quantity lubrication (MQL) in the end milling of AA6061T6 using multi-objective genetic algorithm approach. Response surface methodology coupled with a central composite design of experiments is used for modeling. Data is collected from a vertical CNC milling center and the input parameters are cutting speed, table feed rate, axial depth of cut and the minimum quantity lubrication flow rate. Analysis of variance at a 95% confidence level is implemented to identify the most significant input variables on the CNC end milling process. Optimization of the responses is done using a multi-objective genetic algorithm. A multi-criteria decision making utility is used to find among the feasible range of optimum designs for the operating parameters and the responses. An iterative multi-criteria decision making algorithm is used to find the best design among those obtained from multiobjective optimization with respect to the given conditions. The best design obtained for the equal weightage case is the design at 5252 rpm, with a feed rate of 311 mm/min, a depth of cut of 3.47 mm and MQL flow rate at 0.44 ml/min.

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“…This approach verified with the experimental results obtained in the machining of medium leaded brass using coated carbide tools. Routara et al [29] developed second order mathematical models in terms of machining parameters for surface roughness prediction using RSM to determine the optimum cutting conditions. The experi ments were carried out with coated carbide tool for ma chining of EN8 steel.…”

Section: Surface Roughnessmentioning

confidence: 99%

A Review on Hard Turning by using Design of Experiments

Bhemuni¹,

Rao²

2013

Journal for Manufacturing Science &Amp; Production

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Hard turning is the process of machining hard ened steels that are above 45HRC. In manufacturing, hard turning has emerged as a potential area because of its many advantages over grinding as a finishing operation. In the present paper, a review is done on Design of Exper iment (DOE) techniques that have been employed on various hard turning processes by researchers. DOE is one of the widely used methods for experimental study of many manufacturing processes in engineering. It is a statistical approach in which a mathematical model is developed through a minimum of experimental runs. DOE predicts the possible output, based on the given input parameters in an experiment. The present study predomi nantly focuses on the usage of Response Surface Method, Taguchi's method and Factorial method in hard turning.

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Response Surface Methodology and Genetic Algorithm used to Optimize the Cutting condition for Surface Roughness Parameters in CNC Turning

Cited by 32 publications

References 9 publications

Modeling and optimization of surface roughness and tool vibration in CNC turning of Aluminum alloy using hybrid RSM-WPCA methodology

Modeling and optimization of surface roughness and tool vibration in CNC turning of Aluminum alloy using hybrid RSM-WPCA methodology

Multi-objective optimization of minimum quantity lubrication in end milling of aluminum alloy AA6061T6

A Review on Hard Turning by using Design of Experiments

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