Multi-parametric Optimization of WEDM Using Artificial Neural Network (ANN)-Based PCA for Al/SiCp MMC

Phate, Mangesh; Toney, Shraddha; Phate, Vikas

doi:10.1007/s40032-020-00615-1

Cited by 23 publications

(11 citation statements)

References 25 publications

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“…ANOVA is performed for the response GRG (Overall grade) to know the impact of various process parameters on the overall performance of the machining. ANOVA before pooling (Table 7) does not show significant results since the degrees of freedom (DOF) is associated with the term 'error' is 'zero' [19]. The error is due to the mismatching of various process parameters and their levels.…”

Section: Resultsmentioning

confidence: 96%

“…The parameters IP has a significant impact on response TWR followed by the POFF and B4C. Similarly, the parameter B4C has a considerable impact on the response Ra followed by the IP and POFF [19]. The impact of different machining parameters on the various responses has appeared in Table 6.…”

Section: Resultsmentioning

confidence: 99%

“…The Al/Cu/Ni alloy was prepared, and experiments were carried out to know the ease of the EDM process [18]. The researcher examined the WEDM of Al/SiC MMC to determine the optimized machining parameters [19]. The machining process parameters were investigated to machine hypereutectic Al-Si alloys and optimize the finishing process [20].…”

Section: Introductionmentioning

confidence: 99%

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Multi-response Optimization and Analysis of Al/B4Cp EDM using Grey Relational Analysis

Toney¹,

Phate²,

Phate³

2022

JMechE

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Development of material, especially metal matrix composite (aluminumbased MMC), attracts worldwide researchers due to its enhancement in wear and abrasive resistance, lightweight and high strength, low coefficient of thermal expansion. This work investigates the electrical discharge machining (EDM) of Aluminum/Boron Carbide (Al/B4C) MMC. The optimization will help the researchers or metal processing industries use the investigated optimized process parameters for efficient and effective machining parameters. Pulse on time (PON), pulse off time (POFF), a variation of boron carbide(CP), and input current (IP) were varied to measure material removal rate (MRR), wear rate of the tool (TWR), and the surface roughness (Ra). The Taguchi method is used for the analysis of the machining parameters. Grey relational grade (GRA) is employed for the optimization of machining responses and the input parameters. The influence of various EDM parameters is investigated by analysis of variance (ANOVA). The multi-response optimization was carried out by GRA (CP: 4% of B4C, PON” 25 micro-sec, POFF: 9 micro-sec, and input current of 8 amp). The optimum responses were MRR: 17.58 mm3 /sec, TWR: 0.064 mm3 /sec, and Ra: 1.20 microns. The Aluminum-based alloys or composites are widely used in aerospace applications, automobile sectors, construction, aircraft industries, etc.

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Section: Resultsmentioning

confidence: 96%

Section: Resultsmentioning

confidence: 99%

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Multi-response Optimization and Analysis of Al/B4Cp EDM using Grey Relational Analysis

Toney¹,

Phate²,

Phate³

2022

JMechE

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“…Phate et al 116 fabricated Al/Gr/C p 5 MMC and investigated the effect of T on , I P and f w on Ra during its machining using WEDM and found that T on is the most significant factor affecting Ra, followed by I P and f w . Phate et al 117 witnessed that the % composition of silicate, T off , and I P are the most significant factors influencing the WEDM performance characteristics during machining of Al/SiC p . Further, they used artificial neural network (ANN) and principal component analysis (PCA) techniques for the optimization of multiple parameters, and found that 15% weight percentage of SiC, T on at 112 µs, T off at 56 µs, F W at 4 mm/min, I P at 3 amp, T w at 4 kg, and FP at 13 kg/m 2 are the optimum set of input parameters for the optimized output responses i.e.…”

Section: Edm/wedm Of Advanced Mmcs’ and Low-conducting Ceramic Materialsmentioning

confidence: 99%

A comprehensive review on wire EDM performance evaluation

Alam

Siddiquee

Khan

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part E:

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Wire electric discharge machining (WEDM) technique is a fast-growing, advanced manufacturing process which is used for machining of hard materials including various alloys of steel, nickel, tungsten, cubic boron nitride, metal matrix composites (MMC's), superalloys, and ceramic materials. Moreover, it is employed for machining complex profiles and micromachining of hardened materials which are not feasible by various conventional machining processes. Generally, this process is employed to machine electrically conductive materials but during this scenario, it is also being used for machining of electrically low conducting and non-conducting ceramics including silicon carbide, aluminium oxide, silicon nitrate, and zirconium oxide ceramics by modifying the WEDM method with assisted electrode technique or forming composite of conductive and non-conductive materials. This paper presents a comprehensive review on the influence of several WEDM control factors including pulse-on time, pulse-off time, wire feed rate, peak current, wire tension, type of wire (tool) materials, types of base materials and types of powder mixed dielectric fluids on the output responses such as surface roughness (Ra), material removal rate (MRR), width of cut (kerf), wire wear ratio (WWR), wire breakage, microstructural defects, recast layer thickness, and thermal deformation. Moreover, various simulation methods, post processing methods and optimization of WEDM parameters using various techniques were discussed and at last this paper shapes the important recommendations and upcoming developments in WEDM.

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“…e results reveal that integrated form optimization techniques deliver an effective optimal solution. Based on available literature, it can be noted that wire feed rate, pulse off time, and pulse on time are the major influencing parameters in WEDM [19]. Machinability analysis of graphene-based surface composites has rarely been reported.…”

Section: Introductionmentioning

confidence: 99%

Investigations on the WEDM of Friction Stir Processed Magnesium/Graphene-Boron Nitride Hybrid Surface Composite through the Entropy-COPRAS Approach

Kavimani

Gopal

Sivamaran³

et al. 2022

Advances in Materials Science and Engineering

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In this research, friction stir processing (FSP) is utilized to develop the graphene-boron nitride-reinforced hybrid magnesium surface composite with varying volume percentages of reinforcements. A Taguchi-coupled Entropy-COPRAS approach is adopted to understand the influence of control factors of wire electrical discharge machining on the developed magnesium surface composite. An optimal combination of machining factors to attain maximum material removal rate (MRR) along with minimal kerf width and surface roughness is to be finalized. The Taguchi method is utilized for planning the experiments with three levels and four factors, namely, reinforcement volume %, pulse off time, wire feed rate, and pulse on time. ANOVA results show that pulse on time and reinforcement volume % act as the most significant factors for output responses. Using the Entropy-COPRAS approach, an optimal combination for output response was found for a maximum MRR of 16.20 mm3/min; minimal surface roughness of 3.86 μm; and 0.29 μm of kerf width.

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Multi-parametric Optimization of WEDM Using Artificial Neural Network (ANN)-Based PCA for Al/SiCp MMC

Cited by 23 publications

References 25 publications

Multi-response Optimization and Analysis of Al/B4Cp EDM using Grey Relational Analysis

Multi-response Optimization and Analysis of Al/B4Cp EDM using Grey Relational Analysis

A comprehensive review on wire EDM performance evaluation

Investigations on the WEDM of Friction Stir Processed Magnesium/Graphene-Boron Nitride Hybrid Surface Composite through the Entropy-COPRAS Approach

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