Review of improvements in wire electrode properties for longer working time and utilization in wire EDM machining

Wire electrical discharge machining (WEDM) is an important technology, which demands high-speed cutting and high-precision machining to realize productivity and improved accuracy for manufacturing hard materials. WEDM has experienced explosive growth and complexity of equipment as well as rising demand for the basic process tool (the wire electrode). Greater taper angles, thicker workpieces, automatic wire threading, and long periods of unattended operation make the selection of the idealwire a much more critical basis for achieving successful operation. This paper focuses on the evolution of EDM wire electrode technologies from using copper to the widely employed brass wire electrodes and from brass wire electrodes to the latest coated wire electrodes. Wire electrodes have been developed to help user demand and needs through maximum productivity and quantity by choosing the best wire. In the final part of the paper, the possible trends for future WEDM electrode research are discussed.

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Increasing the productivity of the wire-cut electrical discharge machine associated with sustainable production

Wire-cut electric discharge machining is a nontraditional technique by which the required profile is acquired using sparks energy. Concerning Wire-cut electric discharge machining, high cutting rates and precision machining is necessary to improve productivity and achieve high quality of machined workpieces. In this research work, an experimental investigation was introduced to achieve higher productivity of the wire electrode associated with sustainable production in terms of product quality and less heat-affected zone. For this purpose, the effects of machining parameters including peak current, pulse on time and wire preloading were investigated using adaptive neuro-fuzzy inference system along with the Taguchi method. From this study, the optimal setting of machining parameters to achieve higher productivity and sustainability was identified. Moreover, Neuro-fuzzy modelling was successfully used to build an empirical model for the selection of machining parameters to achieve higher productivity at highest possible surface quality and minimum cost for sustainable production.

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www.kfs.edu.eg/ibrahemmaher.html