Machining performance optimization for electro-discharge machining of Inconel 601, 625, 718 and 825: an integrated optimization route combining satisfaction function, fuzzy inference system and Taguchi approach

Rahul, *; Abhishek, Kumar; Datta, Saurav; Biswal, Bibhuti Bhusan; Mahapatra, Siba Sankar

doi:10.1007/s40430-016-0659-7

Cited by 53 publications

(15 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Axial depth of cut is reported as the dominant process variable affecting tangential cutting force (49%) and axial cutting force (47%) while radial depth of cut contributed 70% variation in radial force. Application of hybrid optimization methodology employing principal component analysis (PCA) integrated with desirability function analysis (DFA) and grey function analysis (GRA) [19], PSO integrated with ANN [20] and fuzzy logic coupled with Taguchi technique [21] have been attempted. Desirability graph approach coupled with user's preference method is applied by Harmesh et al [22] for multi-response optimization of SR, cutting speed and spark gap in WEDM of Al/SiCp-MMC.…”

Section: Review Of Literaturementioning

confidence: 99%

Fuzzy logic-integrated PSO methodology for parameters optimization in end milling of Al/SiCp MMC

Devarajaiah

Chandrasekaran

2019

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

This paper deals with a novel integrated parametric optimization in end milling of Al-SiC p metal-matrix composites using carbide tool. Fuzzy logic modeling combined with particle swarm optimization (PSO) technique is applied as intelligent optimization methodology to obtain optimal process parameters in end milling process. Fuzzy rules-based surface roughness prediction model is developed with SiC p percentage as one the input parameter is addition to spindle speed, feed and depth of cut. Comparison of fuzzy rule model predictions with confirmation data sets showed 95.44% average prediction accuracy. The effect of process parameters on surface roughness is also studied. Analysis of variance established feed rate as the most significant process variable with 69.93% contribution followed by SiC p (19%) and spindle speed (9.73%), respectively. The integrated PSO optimizer optimizes the process parameters for an objective to minimize the machining time satisfying desired surface roughness to be obtained. A number of problems with different values of desired surface roughness are solved and algorithm converged in less than ten iterations.

show abstract

Section: Review Of Literaturementioning

confidence: 99%

Fuzzy logic-integrated PSO methodology for parameters optimization in end milling of Al/SiCp MMC

Devarajaiah

Chandrasekaran

2019

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…Similarly, micro-grooves have been produced in the titanium alloy as reported by Lei et al [ 21 ] through EDM. Likewise, Rahul et al [ 22 ] machined different grades of nickel alloy through EDM to explore the effect of process parameters over the surface roughness and tool wear rate. In another consulted research work of Misal et al [ 23 ], surface roughness analysis of Inconel 718 has been carried out to understand the effect of photochemical machining parameters.…”

Section: Introductionmentioning

confidence: 99%

Achieving the Minimum Roughness of Laser Milled Micro-Impressions on Ti 6Al 4V, Inconel 718, and Duralumin

et al. 2020

View full text Add to dashboard Cite

Titanium-aluminium-vanadium (Ti 6Al 4V) alloys, nickel alloys (Inconel 718), and duraluminum alloys (AA 2000 series) are widely used materials in numerous engineering applications wherein machined features are required to having good surface finish. In this research, micro-impressions of 12 µm depth are milled on these materials though laser milling. Response surface methodology based design of experiment is followed resulting in 54 experiments per work material. Five laser parameters are considered naming lamp current intensity (I), pulse frequency (f), scanning speed (V), layer thickness (LT), and track displacement (TD). Process performance is evaluated and compared in terms of surface roughness through several statistical and microscopic analysis. The significance, strength, and direction of each of the five laser parametric effects are deeply investigated for the said alloys. Optimized laser parameters are proposed to achieve minimum surface roughness. For the optimized combination of laser parameters to achieve minimum surface roughness (Ra) in the titanium alloy, the said alloy consists of I = 85%, f = 20 kHz, V = 250 mm/s, TD = 11 µm, and LT = 3 µm. Similarly, optimized parameters for nickel alloy are as follows: I = 85%, f = 20 kHz, V = 256 mm/s, TD = 8 µm, and LT = 1 µm. Minimum roughness (Ra) on the surface of aluminum alloys can be achieved under the following optimized parameters: I = 75%, f = 20 kHz, V = 200 mm/s, TD = 12 µm, and LT = 3 µm. Micro-impressions produced under optimized parameters have surface roughness of 0.56 µm, 2.46 µm, and 0.54 µm on titanium alloy, nickel alloy, and duralumin, respectively. Some engineering applications need to have high surface roughness (e.g., in case of biomedical implants) or some desired level of roughness. Therefore, validated statistical models are presented to estimate the desired level of roughness against any laser parametric settings.

show abstract

“…Rahul et al [ 19 ] exploited the performance characteristics of electric discharge machining on the Inconel superalloy using a hybrid fuzzy-Taguchi approach. Kuriachen et al [ 20 ] utilized FL and particle swarm optimization for the development of the system and optimization of the micro-wire electric discharge machining process.…”

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

View full text Add to dashboard Cite

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.

show abstract

Machining performance optimization for electro-discharge machining of Inconel 601, 625, 718 and 825: an integrated optimization route combining satisfaction function, fuzzy inference system and Taguchi approach

Cited by 53 publications

References 43 publications

Fuzzy logic-integrated PSO methodology for parameters optimization in end milling of Al/SiCp MMC

Fuzzy logic-integrated PSO methodology for parameters optimization in end milling of Al/SiCp MMC

Achieving the Minimum Roughness of Laser Milled Micro-Impressions on Ti 6Al 4V, Inconel 718, and Duralumin

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

Contact Info

Product

Resources

About