Some Investigations Into Multi-Objective Optimization of Wire Electro-Discharge Machining of Al/SiCp Composites

Patil, Nilesh G.; Brahmankar, P.K.; Navale, L. G.

doi:10.1115/msec2007-31060

Cited by 6 publications

(4 citation statements)

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“…The variation of MRR and surface roughness with machining parameters is mathematically modeled by using non-linear regression analysis method. Patil and Brahmankar [54] examined the effect of various input parameters such as pulse on time, pulse off time, ignition pulse current, wire speed, wire tension and flushing pressure on cutting speed and surface finish of Al/SiCp by using Taguchi methods. Shandilya et al [38] concluded that to achieve higher value of the average cutting speed, lower value of voltage and higher value of pulse-off time should be used during WEDC of SiCp/6061 Al MMC.…”

Section: Literature Review: Process Modeling and Optimizationmentioning

confidence: 99%

Analysis and Optimization of Process Parameters in Wire Electrical Discharge Machining Based on RSM: A Case Study

Sağbaş¹

2023

Response Surface Methodology - Research Advances and Applications

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In this book chapter a review and critical analysis on current research trends in wire electrical discharge machining (WEDM) and relation between different process parameters including pulse on time, pulse off time, servo voltage, peak current, dielectric flow rate, wire speed, wire tension on different process responses include material removal rate (MRR), surface roughness (Ra), sparking gap, wire lag and wire wear ration (WWR) and surface integrity factors was investigated. On the basis of critical evaluation of the available literature following conclusions are summarized. In addition, different modeling and optimization methods used in WEDM were discussed and a case study based on response surface method (RSM) including design of experiment (DoE) carried out to find optimal process parameters effect on surface roughness was conducted. In the final part of the present study was presented some recommendations about the trends for future WEDM researches.

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Section: Literature Review: Process Modeling and Optimizationmentioning

confidence: 99%

Analysis and Optimization of Process Parameters in Wire Electrical Discharge Machining Based on RSM: A Case Study

Sağbaş¹

2023

Response Surface Methodology - Research Advances and Applications

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“…However, wire breakages can be reduced by employing higher flushing pressures, higher pulse off times, and suitable values of servo reference voltage. In general, it was suggested that large pulse on time, high flushing pressure, appropriate wire speed and wire tension, large pulse off time, and appropriate pulse current should be used to obtain optimum machining performance [267]. Figure 27 displays the effect of discharge energy on SR and MRR during the WEDM of 45% (volume fraction) SiC p /Al [268].…”

Section: Wire Edm (Wedm)mentioning

confidence: 99%

A review on conventional and nonconventional machining of SiC particle-reinforced aluminium matrix composites

Chen

2020

Adv. Manuf.

113

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Among the various types of metal matrix composites, SiC particle-reinforced aluminum matrix composites (SiC p /Al) are finding increasing applications in many industrial fields such as aerospace, automotive, and electronics. However, SiC p /Al composites are considered as difficult-to-cut materials due to the hard ceramic reinforcement, which causes severe machinability degradation by increasing cutting tool wear, cutting force, etc. To improve the machinability of SiC p /Al composites, many techniques including conventional and nonconventional machining processes have been employed. The purpose of this study is to evaluate the machining performance of SiC p /Al composites using conventional machining, i.e., turning, milling, drilling, and grinding, and using nonconventional machining, namely electrical discharge machining (EDM), powder mixed EDM, wire EDM, electrochemical machining, and newly developed high-efficiency machining technologies, e.g., blasting erosion arc machining. This research not only presents an overview of the machining aspects of SiC p /Al composites using various processing technologies but also establishes optimization parameters as reference of industry applications.

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“…Taguchi orthogonal array is one such approach which was used to study the effect of various input parameters such as current, pulse on-time, off-time, servo reference voltage, maximum feed speed, wire speed, flushing pressure and wire tension on kerf width and cutting speed. [6] The Taguchi analysis, being used for single objective analysis, has been improved for multi objective optimization with the use of Grey relational approach along with Taguchi orthogonal array [7].…”

Section: Introductionmentioning

confidence: 99%

Application of Machine Learning Techniques for Multi Objective Optimization of Response Variables in Wire Cut Electro Discharge Machining Operation

Shukla

Priyadarshini

2019

MSF

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Wire Cut Electrical Discharge Machining (WEDM) is a non-conventional thermal machining process which is capable of accurately machine alloys having high hardness or part having complex shapes that are very difficult to be machined by the conventional machining processes. The WEDM finds applications in automobiles, aero–space, medical instruments, tool and die industries, etc. The input parameters considered for WEDM are pulse on time, pulse off time, flushing pressure, servo voltage, wire feed rate and wire tension. Performance of WEDM is mainly assessed by output variables such as, material removal rate (MRR), kerf width (Kw) and surface roughness (Ra) of the work piece being machined. Looking at the need of a suitable optimization model, the present work explores the feasibility of machine learning concepts to predict optimum surface roughness and kerf width simultaneously by making use of experimental data available in the literature for machining of Hastelloy C– 276 using WEDM. In most of the literatures, single objective optimization has been carried out for predicting optimum cutting parameters for WEDM. Hence, the present work presents a methodology that makes use of a machine learning algorithm namely, gradient descent method as an optimization technique to optimize both surface roughness and kerf width simultaneously (multi objective optimization) and compare the results with the existing literatures. It was observed that the input parameters such as pulse on time, pulse off time, and peak current have significant effect on both surface roughness and kerf width. The gradient descent method was successfully used for predicting the optimum values of response variables.

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Some Investigations Into Multi-Objective Optimization of Wire Electro-Discharge Machining of Al/SiCp Composites

Cited by 6 publications

References 0 publications

Analysis and Optimization of Process Parameters in Wire Electrical Discharge Machining Based on RSM: A Case Study

Analysis and Optimization of Process Parameters in Wire Electrical Discharge Machining Based on RSM: A Case Study

A review on conventional and nonconventional machining of SiC particle-reinforced aluminium matrix composites

Application of Machine Learning Techniques for Multi Objective Optimization of Response Variables in Wire Cut Electro Discharge Machining Operation

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