Measurement and optimization of multi-response characteristics in plasma arc cutting of Monel 400™ using RSM and TOPSIS

Ananthakumar, K.; Rajamani, D.; Esakki, Balasubramanian; Davim, J. Paulo

doi:10.1016/j.measurement.2018.12.010

Cited by 68 publications

(31 citation statements)

References 39 publications

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“…At low speed, the kerf gets wider and becomes hardened where in the jet it was unable to flash out the smelted material. However, at high cutting speed, the unstable arc is formed without an increase in the current [17]. Figure 7b exhibits the variation in MRR as a function of change in cutting speed and stand-off distance.…”

Section: Fuzzy Modeling Of Pac Process Parametersmentioning

confidence: 99%

“…Results of their investigation reveal that the surface roughness is significantly influenced by the stand-off distance and arc current, whereas kerf width and microhardness are influenced by the cutting speed and gas pressure. In another study [17], they have successfully utilized the TOPSIS statistical approach for the optimization of PAC process parameters to improve the cut qualities such as material removal rate, minimized kerf taper, and heat affected zone.…”

Section: Introductionmentioning

confidence: 99%

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Prediction and Analysis of Multi-Response Characteristics on Plasma Arc Cutting of Monel 400™ Alloy Using Mamdani-Fuzzy Logic System and Sensitivity Analysis

et al. 2020

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Nickel-based alloys, especially Monel 400™, is gaining its significance in diverse applications owing to its superior mechanical properties and high corrosion resistance. Machining of these materials is extremely difficult through the traditional manufacturing process because of their affinity to rapid work hardening and deprived thermal conductivity. Owing to these difficulties a well-established disruptive metal cutting process namely plasma arc cutting (PAC) can be widely used to cut the sheet metals with intricate profiles. The present work focuses on an intelligent modeling of the PAC process and investigation on the multi-quality characteristics of PAC parameters using the fuzzy logic approach. The Box-Behnken response surface methodology is incorporated to design and conduct the experiments, and to establish the relationship between PAC parameters such as cutting speed, gas pressure, arc current, and stand-off distance and responses which include the material removal rate (MRR), kerf taper (KT), and heat affected zone (HAZ). The quadratic regression models are developed and their performances are assessed using the analysis of variance (ANOVA). Fuzzy set theory-based models are formulated to predict various responses using the Mamdani approach. Fuzzy logic and regression results are compared with the experimental data. A comparative evaluation predicted an average error of 0.04% for MRR, 0.48% for KT, and 0.46% for HAZ, respectively. The effect of variations in PAC process parameters on selected responses are estimated through performing the sensitivity analysis.

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Section: Fuzzy Modeling Of Pac Process Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction and Analysis of Multi-Response Characteristics on Plasma Arc Cutting of Monel 400™ Alloy Using Mamdani-Fuzzy Logic System and Sensitivity Analysis

et al. 2020

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“…Selection of the optimal parametric combination for an NTM process is considered as a multi-response optimization problem where a set of conflicting objectives (process outputs) needs to be simultaneously satisfied. In this direction, grey relational analysis (GRA) [5,6], weighted aggregated sum product assessment (WASPAS) [7], multi-objective optimization using ratio analysis (MOORA) [7], technique for order of preference by similarity to ideal solution (TOPSIS) [8], desirability function approach [9] etc. have been effectively employed by the past researchers.…”

Section: Introductionmentioning

confidence: 99%

Application of grey correlation-based EDAS method for parametric optimization of non-traditional machining processes

Das

Chakraborty

2020

Scientia Iranica

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Higher dimensional accuracy along with better surface finish of various advanced engineering materials has turned out to be the prime desideratum for the present day manufacturing industries. To achieve this, non-traditional machining (NTM) processes have become quite popular because of their ability to produce intricate shape geometries on diverse difficult-to-machine materials. To allow these processes to operate at their fullest capability, it is often recommended to set their different input parameters at the optimal levels. Thus, in this paper, a new technique combining grey correlation method and evaluation based on distance from average solution is applied for simultaneous optimization of three NTM processes, i.e. photochemical machining process, laserassisted jet electrochemical machining process and abrasive water jet drilling process. The derived optimal parametric combinations outperform those as identified by the other popular multi-objective optimization techniques with respect to the considered response values. The results of analysis of variance also identify the most influencing parameters for the said NTM processes. Finally, the developed surface plots would help the process engineers in investigating the effects of different NTM process parameters on the corresponding grey appraisal scores.

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“…They also showed that the cutting speed has more influence on surface roughness, while the current was minimum. Ananthakumar et al [7] showed that, with an increase in cutting speed, the kerf taper was affected and regression models for the output parameters were proposed. Bhowmick et al [8] experimentally studied the PAC of SS 304 grade material and found that an increase in speed and thickness has a significant effect on MRR.…”

Section: Introductionmentioning

confidence: 99%

Experimental investigations on SS 304 alloy using plasma arc machining

Hema

Ganesan

2020

SN Appl. Sci.

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Plasma arc machining is a well-recognized unconventional machining process widely used to machine intricate part profiles for alloys which are difficult to machine. The surface roughness, material removal rate (MRR), and kerf ratio are predominant factors which influence the performance and quality of plasma cut surfaces. The present research focusses on the effect of plasma arc cutting parameters such as arc voltage, cutting speed, standoff distance, and plasma offset on the cut quality characteristics of SS 304 alloy machined using two different types of nozzles (130 A and 200 A). The experiments were conducted according to a mixed Taguchi design of L18 orthogonal array, and grey relational analysis technique is used for optimization of the above-said cutting conditions. The experimentation on SS 304 alloy is carried out using two different nozzles and identified the best suited nozzle to cut SS 304 alloy of thickness 6 mm which produces better surface roughness and MRR characteristics. Scanning electron microscopy analysis is carried out to inspect the surface morphologies at various cutting conditions.

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Measurement and optimization of multi-response characteristics in plasma arc cutting of Monel 400™ using RSM and TOPSIS

Cited by 68 publications

References 39 publications

Prediction and Analysis of Multi-Response Characteristics on Plasma Arc Cutting of Monel 400™ Alloy Using Mamdani-Fuzzy Logic System and Sensitivity Analysis

Prediction and Analysis of Multi-Response Characteristics on Plasma Arc Cutting of Monel 400™ Alloy Using Mamdani-Fuzzy Logic System and Sensitivity Analysis

Application of grey correlation-based EDAS method for parametric optimization of non-traditional machining processes

Experimental investigations on SS 304 alloy using plasma arc machining

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