Application of response surface methodology in the optimization of cutting conditions for surface roughness

Öktem, Hasan; Erzurumlu, Tuncay; Kurtaran, Hasan

doi:10.1016/j.jmatprotec.2005.04.096

Cited by 331 publications

(134 citation statements)

References 9 publications

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“…The mathematical model function will be obtained by using the second-order polynomial regression model in this study which will be used as the objective function in GSO. The necessary information to construct the response model are generally accumulated by the simulation works [11,12]. Figure 1 shows the RSM flowchart in this study.…”

Section: Response Surface Methodologymentioning

confidence: 99%

Warpage Optimisation on the Moulded Part using Response Surface Methodology (RSM) and Glowworm Swarm Optimisation (GSO)

et al. 2017

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Abstract. Nowadays, there are various of optimisation methods that have been explored by many researchers to find the appropriate processing parameters setting for the injection moulding process. From the previous researches, it was reported that the optimisation work has improved the moulded part quality. In this study, the application of optimisation work to improve warpage of the front panel housing have been explored. By selecting cooling time, coolant temperature, packing pressure and melt temperature as the variable parameters, design of experiment (DOE) have been constructed by using the rotatable central composite design (CCD) approach. Response Surface Methodology (RSM) was performed to obtain the mathematical model. This mathematical model then will be used in Glowworm Swarm Optimisation (GSO) method in order to determine the optimal processing parameters setting which will optimise the warpage condition. Based on the results, melt temperature is the most significant factor contribute to the warpage condition and warpage have optimised by 39.1% after optimisation. The finding shows that the application of optimisation work offers the best quality of moulded part produced.

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Section: Response Surface Methodologymentioning

confidence: 99%

Warpage Optimisation on the Moulded Part using Response Surface Methodology (RSM) and Glowworm Swarm Optimisation (GSO)

et al. 2017

View full text Add to dashboard Cite

show abstract

“…The mathematical model function will be obtained by using the second-order polynomial regression model in this study which will be used as the objective function in GSO. The necessary information to construct the response model was accumulated by the simulation analysis [12,13]. Figure 1 shows the RSM flowchart in this study.…”

Section: Response Surface Methodologymentioning

confidence: 99%

Warpage Optimisation on the Moulded Part with Conformal Cooling Channels using Response Surface Methodology (RSM) and Glowworm Swarm Optimisation (GSO)

et al. 2017

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Abstract. Today, there are many of optimisation method have been explored by previous researchers to find the appropriate processing parameters setting for the injection moulding process. From the previous researches, it has been proven that the optimisation work improved the quality of the moulded part. However, the application of optimisation work in conformal cooling channels still lacks. Therefore, in this study, the application of optimisation work to improve warpage of front panel housing with conformal cooling channels moulds have been explored. By choosing cooling time, coolant temperature, packing pressure and melt temperature as the variable parameters, design of experiment (DOE) has been defined by using the rotatable central composite design (CCD) approach. Response Surface Methodology (RSM) was performed to determine the mathematical model. The mathematical model then will be used in Glowworm Swarm Optimisation (GSO) method in order to obtain the optimal processing parameters setting which will optimise the warpage condition. Based on the results, cooling time is the most significant factor contributes to the warpage condition and warpage have optimised by 38.7% after optimisation using the proposed approach. This finding shows that the application of conformal cooling channels with optimisation work will produce better quality of the moulded part.

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“…High surface roughness values reduce the fatigue life [2]. Surface roughness is influenced by tool geometry, feed, cutting conditions and the irregularities of machining operations such as tool wear, chatter, tool deflections, cutting fluid, and work piece properties [3]. It would be costly and time consuming to acquire the knowledge of appropriate cutting parameters.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Process Parameters of CNC Lathe Turner by Response Surface Methodology

2015

International Conference on Advancements and Recent Innovations in Mechanical, Production and Industrial Engineering

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Abstract-Efficiency of production and quality are the two major issues on which manufacturing industry is dependent. With the technology up gradation, it is more convenient to work on a CNC Lathe Machine in comparison to a conventional lathe. Turning operation is a widely used process in industries. It has been recognized that parameters during turning operation such as cutting speed, depth of cut and feed rate should be selected in such a way so that it provides minimum surface roughness and increased productivity. By taking three parameters of turning operation i.e. feed rate, depth of cut and cutting speed, the work material is machined according to Central Composite Design. It is found that these parameters influence surface roughness (µm) widely. Using ANOVA and regression analysis, a mathematical model is generated using Response Surface Methodology so that it can be used for giving optimum working condition for different work pieces on the same machine.

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Application of response surface methodology in the optimization of cutting conditions for surface roughness

Cited by 331 publications

References 9 publications

Warpage Optimisation on the Moulded Part using Response Surface Methodology (RSM) and Glowworm Swarm Optimisation (GSO)

Warpage Optimisation on the Moulded Part using Response Surface Methodology (RSM) and Glowworm Swarm Optimisation (GSO)

Warpage Optimisation on the Moulded Part with Conformal Cooling Channels using Response Surface Methodology (RSM) and Glowworm Swarm Optimisation (GSO)

Analysis of Process Parameters of CNC Lathe Turner by Response Surface Methodology

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