Experimental investigation and optimisation in EDM process of AISI P20 tool steel

Abstract

Electro Discharge Machining (EDM) is an extremely prominent machining process among newly developed non -traditional machining techniques for “difficult to machine” conducting materials such as heat treated tool steels, composites, super alloys, ceramics, hastelloys, nitralloy, nemonic alloys, carbides, heat resistant steels etc. In EDM, the material removal of the electrode is achieved through high frequency sparks between the tool and the work-piece immersed into the dielectric. The Material Removal Rate (MRR), Tool Wear Rate (TWR) and surface integrity are some of the important performance attributes of EDM process. The objective of EDM is to get high MRR along with achieving reasonably good surface quality of machined component.The machining parameters that achieve the highest MRR strongly depend on the size of the machining surface i.e. the engaged electrode and work-piece surface.With upcoming worldwide applications of AISI P20 machining has become an important issue which needs to be investigated in detail. The AISI P20 steel is applied by the tooling industry as material for injection molding tools. These steel are categorized as “difficult to machine” materials, since they posses greater strength and toughness. Therefore, AISI P20 steel is usually known to create major challenges during conventional and non- conventional machining.Keeping this in view, an experimental investigation to explore the productivity, quality, surface integrity, and accuracy on the EDM surface. The work has been carried out by conducting a set of experiments using AISI P20 tool steel work-piece with copper electrode. Important machining parameters like Discharge current (Ip), Pulse on Time(Ton), Pulse off Time (Toff ), Lift Time (Tup) and Work Time (Tw) are considered for investigation. The effect of the machining parameters on the responses such as MRR, TWR, Surface Roughness (SR), and Micro hardness were investigated. Now-a-days optimization and modeling of EDM process is a highly demanding re