Manufacturing Technology Today

N. Natarajan ¹, R. M. Arunachalam ²

Affiliations
1 Dept of Mechanical Engg, Muthayammal Engg College, Rasipuram, IN
2 Dept of Mechanical Engg, Sona College of Technology, Salem, IN

Abstract

This study investigates the optimization of process parameters of micro electric discharge machining (micro-EDM) for stainless steel grade 304 (SS 304) on the machining characteristics using the grey relational analysis (GRA) method. Twenty seven experimental runs based on the orthogonal array (OA) of Taguchi method have been carried out. The multi-objective optimization of the process parameters viz. material removal rate (MRR), tool wear rate (TWR), diametral overcut (DOC) and taper (T) has been performed. The current is identified to be the most influential factor of the MRR, TWR and the T, and the pulse-off time has an impact on DOC. Additionally, the analysis of variance (ANOVA) is also carried out to identify the most significant factor in which the current is observed to be the most significant factor. In-depth studies have also been made to examine the influence of various process parameters through SEM micrographs.

Keywords

Grey Relational Analysis, Multiple Performance, Optimization, Micro-EDM, ANOVA, White Layer, Taguchi, Micro-Hole.

Full Text

     

R. Thanigaivelan ¹, R. M. Arunachalam ²

Affiliations
1 Dept. of Mechanical Engg., Muthayammal Engg. College, Rasipuram, IN
2 Dept. of Mechanical Engg., Sona College of Technology, Salem, IN

Abstract

Electrochemical Micromachining (EMM) is a promising technology for machining the microstructures and components. EMM appears to offer several advantages including better precision, wide range of materials could be machined and no stress on the machined workpiece. This paper is focused on development of an EMM system in which the micro structure and components are fabricated. Influences of tool electrode design (flat, conical with rounded and wedged electrode) on machining rate and overcut by varying the electrolyte concentration are discussed in detail. The wedged electrode produces higher machining rate and conical with rounded electrode improves the micro-hole accuracy by 2.2 times compared to flat electrode. Finally, applications of electrochemical micromachining are also discussed.

Keywords

Electrode, Tool Design, Electrochemical Micromachining, Applications, Machining Set-Up.

Full Text

     

R. Thanigaivelan ¹, R. M. Arunachalam ²

Affiliations
1 Dept. of Mechanical Engg., Muthayammal Engg. College, Rasipuram, IN
2 Dept. of Mechanical Engg., Sona College of Technology, Salem, IN

Abstract

The requirements for micro components in all emerging areas are rapidly increasing. To meet this demand, micro machining is considered as one of the key technologies for the production of micro parts and components. Among the various capable processes, electrochemical micro machining is considered due its advantages of accuracy, no electrode wear and various ranges of materials that can be machined. An experimental set-up for Electrochemical Micro machining (EMM) is developed, which consists of various elements. This paper focuses on experimental study of dominant variables like pulse on-time, current, voltage, and electrolyte concentration on machining speed and overcut when machining 304 stainless steel. From the experimental results, it is evident that the machining speed reaches maximum at a pulse on-time of 30 ms. The most effective range of pulse on-time and electrolyte concentration can be considered as 25-30 ms and 0.23-0.29 mole/l, which gives moderate machining speed and lower overcut.

Full Text

     

J. S. Senthilkumar ¹, P. Asokan ², R. M. Arunachalam ², D. Suresh Babu ², V. Manickam ²

Affiliations
1 Dept. of Mechanical Engg., Sona College of Technology, Salem, Tamil Nadu, IN
2 Dept. of Prod. Engg., National Institute of Technology, Tiruchirapalli, IN

Abstract

This paper describes the combination of Genetic Algorithm (GA) and Artificial Neural Network (ANN) based hybrid approach in real data based optimization. Power consumption, cutting force and surface roughness are the major constraints which directly influence the operating parameters. Many researchers have developed mathematical model of the CNC turning process for the purpose of optimizing the operating parameters. But this will be highly suitable for a particular combination of cutting tool and workpiece. In order to avoid this problem, hybrid approach is proposed in this work (i.e) Genetic algorithm and ANN. GA is used for solving the optimization machining cost and ANN is used for the constraints evaluation. Experimental results demonstrate that this hybrid optimization approach can accurately estimate machining cost without violating those constraints.

Full Text

     

J. S. Senthilkumaar ¹, P. Asokan ², R. M. Arunachalam ¹

Affiliations
1 Dept. of Mechanical Engg., Sona College of Technology, Salem, IN
2 Dept. of Production Engg., National Institute of Technology, Tiruchirapalli, IN

Abstract

Selection of machining parameters is a very important task to the process planer to achieve desired surface roughness with minimum machining cost. Facing operation is an important and inevitable machining process for manufacture of aero space components like disks and blades. The cutting tool manufacturer's recommended cutting parameters are usually for turning operation and common for few materials and so adapting their turning conditions for facing process results in premature tool failure and poor surface finish. Based on the machining experience and earlier research results, uncoated tools performance are better than the coated tools and necessity to control the pollution dry machining are preferred. In this paper, the surface roughness and tool wear when facing Inconel 718 using uncoated carbide cutting tools have been investigated. The results show that the feed and cutting speed were the most influential factors on the surface roughness and flank wear. The optimum machining parameters are predicted for minimization of surface roughness and minimization of tool wear by simultaneously optimized. The predicted results have good agreements with experimental results.

Full Text

     

T. Jesudas ¹, R. M. Arunachalam ¹, K. S. Jayakumar ¹, R. Thiraviam ²

Affiliations
1 Dept. of Mechanical Engg., Sona College of Technology, Salem, IN
2 Sethu Institute of Technology, Kariapatti, Anna University, Tamil Nadu, IN

Abstract

The bronze-alumina (Al₂O₃) alloy is an Metal Matrix Composite (MMC) of interest in several applications like bearing sleeve, piston and cylinder liners etc:The reinforcement used in this MMC makes it difficult to machine using traditional technique. Wire-Electric Discharge Machine (WEDM) seems to be a viable option to machine. This paper presents an investigation on the optimization of machining parameters in WEDM of bronze-alumina MMC. The main objective is to find the optimum cutting parameters to achieve a low value of surface roughness and higher material removal rate (MRR). The cutting parameters considered in this experimental study are, pulse on time, pulse off time and wire feed rate. The settings of cutting parameter's were determined by using Taguchi experimental design method. An L₉ orthogonal array was chosen. Signal to Noise ratio (S/N) and analysis of variance (ANOVA) was used to analyze the effect of the parameters on surface roughness and material removal rmte to identify the optimum cutting parameters. The contribution of each cutting parameter's towards the surface roughness and material removal rate is also identified. The study shows that the Taguchi method is suitable to solve the stated problem with minimum number of trials.

Full Text