Experimental Investigation of Machining Parameters for EDM Using U-shaped Electrode of AISI P20 Tool Steel

The correct selection of manufacturing conditions is one of the most important aspects to take into consideration in the majority of manufacturing processes and, particularly, in processes related to Electrical Discharge Machining (EDM). It is a capable of machining geometrically complex or hard material components, that are precise and difficult-to-machine such as heat treated tool steels, composites, super alloys, ceramics, carbides, heat resistant steels etc. being widely used in die and mold making industries, aerospace, aeronautics and nuclear industries. AISI P20 Plastic mould steel that is usually supplied in a hardened and tempered condition. Good machinability, better polishability, it has a grooving rang of application in Plastic moulds, frames for plastic pressure dies, hydro forming tools These steel are categorized as difficult to machine materials, posses greater strength and toughness are usually known to create major challenges during conventional and non- conventional machining. The Electric discharge machining process is finding out the effect of machining parameter such as discharge current, pulse on time and diameter of tool of AISI P20 tool steel material. Using U-shaped cu tool with internal flushing. A well-designed experimental scheme was used to reduce the total number of experiments. Parts of the experiment were conducted with the L18 orthogonal array based on the Taguchi method. Moreover, the signal-to-noise ratios associated with the observed values in the experiments were determined by which factor is most affected by the Responses of Material Removal Rate (MRR), Tool Wear Rate (TWR) and over cut (OC)

Multi-objective optimisation and analysis of EDM of AISI P20 tool steel

Electric Discharge Machining (EDM) is one of the non traditional machining processes used to produce critical shape on hard or brittle conductive materials and it can also be successfully applied on materials that are extremely difficult-to-machine using traditional machining processes. The experimental investigation of EDM process parameters is of utter importance in order to improve the productivity, surface integrity and quality characteristics. An efficient method for determining the optimum process parameters for multiple performance characteristics, through various multi-optimisation techniques from the experiment trials, is a necessity of the present industry. The work piece material for the current research work was AISI P20 tool steel and a cylindrical copper electrode was used with lateral flushing of dielectric fluid during the first phase of the study. AISI P20 tool steel has growing range of applications like in plastic moulds, frames for plastic pressure dies, hydro forming tools, which offer difficulty in conventional machining in hardened condition. Influence of various process parameters on MRR, TWR and OC has been investigated during EDMof AISI P20 tool steel. Different multi-objective optimisation techniques such as grey-Taguchi and fuzzy logic combined with Response Surface Methodology (RSM) have been utilized in order to achieve optimal combinations of EDM parameters like discharge current, pulse-on time, work time, lift time, and inter electrode gap which would result in maximum MRR as well as minimum TWR and OC. Working time did not have any influence on performance measures of EDM, while other parameters had significant effect. Both grey relation analysis and fuzzy logic technique have been implemented to convert multiple responses in EDM into a single one and optimise the above responses. Finally, respective confirmation tests were carried out to obtain optimal process parameters

Multi-response optimization of surface integrity characteristics of EDM process using grey-fuzzy logic-based hybrid approach

Surface integrity remains one of the major areas of concern in electric discharge machining (EDM). During the current study, grey-fuzzy logic-based hybrid optimization technique is utilized to determine the optimal settings of EDM process parameters with an aim to improve surface integrity aspects after EDM of AISI P20 tool steel. The experiment is designed using response surface methodology (RSM) considering discharge current (Ip), pulse-on time (Ton), tool-work time (Tw) and tool-lift time (Tup) as process parameters. Various surface integrity characteristics such as white layer thickness (WLT), surface crack density (SCD) and surface roughness (SR) are considered during the current research work. Grey relational analysis (GRA) combined with fuzzy-logic is used to determine grey fuzzy reasoning grade (GFRG). The optimal solution based on this analysis is found to be Ip = 1 A, Ton = 10 μs, Tw = 0.2 s, and Tup = 0.0 s. Analysis of variance (ANOVA) results clearly indicate that Ton is the most contributing parameter followed by Ip, for multiple performance characteristics of surface integrity

Modeling and optimization of ultrasonic metal welding on dissimilar sheets using fuzzy based genetic algorithm approach

Ultrasonic welding has been used in the market over the past twenty years and serving to the manufacturing industries like aviation, medical, microelectronics and many more due to various hurdles faced by conventional fusion welding process. It takes very short time (less than one second) to weld materials, thus it can be used for mass production. But many times, the problems faced by industries due to this process are the poor weld quality and strength of the joints. In fact, the quality and success of the welding depend upon its control parameters. In this present study, the control parameters like vibration amplitude, weld pressure and weld time are considered for the welding of dissimilar metals like aluminum (AA1100) and brass (UNS C27000) sheet of 0.3 mm thickness. Experiments are conducted according to the full factorial design with four replications to obtain the responses like tensile shear stress, T-peel stress and weld area. All these data are utilized to develop a non-linear second order regression model between the responses and predictors. As the quality is an important issue in these manufacturing industries, the optimal combinations of these process parameters are found out by using fuzzy logic approach and genetic algorithm (GA) approach. During experiments, the temperature measurement of the weld zone has also been performed to study its effect on different quality characteristics. From the confirmatory test, it has been observed that, the fuzzy logic yields better output results than GA. A variety of weld quality levels, such as “under weld”, “good weld” and “over weld” have also been defined by performing micro structural analysis

Abstracts of National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020

This book presents the abstracts of the papers presented to the Online National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020 (RDMPMC-2020) held on 26th and 27th August 2020 organized by the Department of Metallurgical and Materials Science in Association with the Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, India. Conference Title: National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020Conference Acronym: RDMPMC-2020Conference Date: 26–27 August 2020Conference Location: Online (Virtual Mode)Conference Organizer: Department of Metallurgical and Materials Engineering, National Institute of Technology JamshedpurCo-organizer: Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, IndiaConference Sponsor: TEQIP-