Abstract
This paper presents a methodology to evaluate the performance of carbide compacting die using graph theoretic approach (GTA). Factors affecting the die performance and their interactions are analysed by developing a mathematical model using digraph and matrix method. Permanent function or die performance index is obtained from the matrix model developed from the digraphs. This permanent function/index value compares and ranks the factors affecting the die performance. It helps in selection of optimum process parameters during die manufacturing. Hence, process output errors such as dimensional inaccuracy, large surface craters, deep recast layers, etc. will be minimised during die manufacturing which helps to achieve better die performance. In present illustration, factors affecting the performance of carbide compacting die are grouped into five main factors namely work material, machine tool, tool electrode, geometry of die and machining operation. GTA methodology reveals that the machine tool has highest index value. Therefore, it is the most influencing factor affecting the die performance. In case of die material low cobalt concentration and small grain size yields good surface finish, while in machine tool low discharge energy (i.e. low values of peak current, pulse-on time, servo voltage and high value of pulse-off time) and high dielectric flow rate yields good surface finish and, hence, favours the good die performance. In case of die geometry, large work piece thickness and small taper angles results in lesser geometrical deviations and hence helps to achieve better die performance.
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More From: The International Journal of Advanced Manufacturing Technology
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