Experimental Analysis of Wire EDM Process Parameters for Micromachining of High Carbon High Chromium Steel by Using MOORA Technique

Sahoo, Sarat Kumar; Naik, Sunita Singh; Rana, Jaydev

doi:10.1007/978-3-319-99900-5_7

Cited by 16 publications

(8 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Methodsmentioning

confidence: 99%

“…The authors did not find literature which reports the effect of dielectric by making it as one of the WEDM parameters; this maiden study may provide the significance of dielectric alongside other regular WEDM parameters. 44 In this study, DM water is used as a base dielectric fluid and newer dielectrics are developed by mixing Al 2 O 3 nano-particles, ethylene glycol, and oxygen gas to the base dielectric. Four different dielectric fluids are developed based on the extensive trials and study of literature and handbooks on the subject.…”

Section: Dielectric Fluids and Their Breakdown Mechanismmentioning

confidence: 99%

See 1 more Smart Citation

Multi-response optimization for Nimonic alloy miniature gear fabrication using wire electrical discharge machining

Chaudhary

Siddiquee

Chanda³

et al. 2020

Advances in Mechanical Engineering

View full text Add to dashboard Cite

Generally, gear is an essential component in various electro-mechanical devices, but its manufacturing at the micro-level is challenging. The non-conventional manufacturing processes, such as electro-discharge machining (EDM), is suitable in gear fabrication. Although miniature gears have strict accuracy requirements, the optimization of the EDM process parameters, especially for advanced materials and alloys, is critical. In this paper, Nimonic alloy miniature gears are manufactured using wire-EDM and the effect of process parameters, such as peak current, pulse-off (POFF) time, pulse-on (PON) time, wire tension, and dielectric fluid on the response factors are analyzed. The primary response factors, such as surface roughness, machining time, material removal rate, kerf width (KW), surface microhardness, and depth of microhardness are considered. Also, different dielectric fluids are prepared, which include ethylene glycol mixed demineralized water, oxygen mixed demineralized water, ethylene glycol and alumina powder mixed demineralized water, and ethylene glycol alumina powder and oxygen mixed demineralized water. Furthermore, the effect of process parameters on the multi-response using Pareto ANOVA has been analyzed. The results demonstrate that ethylene glycol mixed demineralized water, as a dielectric fluid, is the most influencing parameter to reduce the surface roughness, machining time, KW, and improve micro-hardness. Thus, dielectric fluid is an essential factor obtained from multi-response optimization followed by peak current, POFF time, wire tension, and PON time.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Dielectric Fluids and Their Breakdown Mechanismmentioning

confidence: 99%

Multi-response optimization for Nimonic alloy miniature gear fabrication using wire electrical discharge machining

Chaudhary

Siddiquee

Chanda³

et al. 2020

Advances in Mechanical Engineering

View full text Add to dashboard Cite

show abstract

“…The importance of optimization in different engineering fields are listed below; Effective utilization of input resources, Maximization of benefits and Minimization of cost in various manufacturing and construction, Optimal production planning, controlling and scheduling, peak allocation of assets or facilities among numerous activities, preparation of maintenance and equipment replacement to decrease operational cost, Inventory mechanism, selection of manufacturing condition in metal cutting method to minimize manufacture cost, improvement of industry productivity. [6] Maximization of output in terms of quality and quantity of the process with minimization of input in terms of material and cost is the basic target of every manufacturing industry. The EDM technique is a combination of number of factors like electro-dynamics, electro-magnetic, thermo-dynamic and hydro-dynamic activities, which unveils a complex nature of the process performance.…”

Section: A Optimizationmentioning

confidence: 99%

Optimization of Electrical Discharge Coating Process by Desirability Function approach

Sahoo¹,

Bhaskar²

2019

CVRJST

Self Cite

View full text Add to dashboard Cite

Optimization is used to obtain a higher value of output with a lower value of the input. To attain high quality with low cost in the manufacture process, the optimization of method factors is required. In this work process factors of electrical discharge coating (EDC) process are optimized by using desirability function approach (DFA), a multi-objective optimization technique used in optimization multiple output responses at a time. ANOVA table and response table are also calculated to show the importance of individual parameters.

show abstract

“…The EDM of porous metal requires optimal process parameters, which significantly benefits manufacturing industries in terms of improved product quality, reduced machining cost, enhanced productivity, etc. Sahoo et al [ 13 ] have experimented on high carbon, high chromium steel, as a workpiece and brass as wire electrode material. They have designed the experiments using Taguchi

orthogonal array, and machining process parameters are optimized by employing multi-objective optimization by ratio analysis (MOORA) method.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques

et al. 2022

View full text Add to dashboard Cite

Electric discharge machining is an essential modern manufacturing process employed to machine porous sintered metals. The sintered 316L porous stainless steel (PSS) components are widely used in diverse engineering domains, as interconnected pores are present. The PSS material has excellent lightweight and damping properties and superior mechanical and metallurgical properties. However, conventional machining techniques are not suitable for porous metals machining. Such techniques tend to block the micro-pores, resulting in a decrease in porous materials’ breathability. Thus, the EDM process is an effective technique for porous metal machining. The input process parameters selected in this study are peak current (Ip), pulse on time (Ton), voltage (V), flushing pressure (fp), and porosity. The response parameters selected are material removal rate (MRR) and tool wear rate (TWR). The present work aims to obtain optimum machining process parameters in the EDM of porous sintered SS316L using two meta-heuristic optimization techniques, i.e., Teaching Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO) algorithms, to maximize the MRR and minimize the TWR values. In the case of PSS having a 12.60% porosity value, PSO and TLBO algorithms give same optimum machining parameters. However, for PSS having an 18.85% porosity value, the PSO algorithm improves by about 5.25% in MRR and by 5.63% in TWR over the TLBO. In the case of PSS having a 31.11% porosity value, the PSO algorithm improves about 3.73% in MRR and 6.46% in TWR over the TLBO. The PSO algorithm is found to be consistent and to converge more quickly, taking minimal computational time and effort compared to the TLBO algorithm. The present study’s findings contribute valuable information in regulating the EDM performance in machining porous SS316L.

show abstract

Experimental Analysis of Wire EDM Process Parameters for Micromachining of High Carbon High Chromium Steel by Using MOORA Technique

Cited by 16 publications

References 10 publications

Multi-response optimization for Nimonic alloy miniature gear fabrication using wire electrical discharge machining

Multi-response optimization for Nimonic alloy miniature gear fabrication using wire electrical discharge machining

Optimization of Electrical Discharge Coating Process by Desirability Function approach

Multi-Objective Optimization of the Process Parameters in Electric Discharge Machining of 316L Porous Stainless Steel Using Metaheuristic Techniques

Contact Info

Product

Resources

About