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首页> 外文期刊>The International Journal of Advanced Manufacturing Technology >Digraph and matrix method for the performance evaluation of carbide compacting die manufactured by wire EDM
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Digraph and matrix method for the performance evaluation of carbide compacting die manufactured by wire EDM

机译:电火花线切割机制造硬质合金压模性能的图和矩阵法

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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.
机译:本文提出了一种使用图论方法(GTA)评估硬质合金压模性能的方法。通过使用有向图和矩阵方法建立数学模型来分析影响模具性能及其相互作用的因素。永久功能或模具性能指标是从有向图开发的矩阵模型中获得的。这个永久性的功能/指标值对影响模具性能的因素进行比较和排序。它有助于在模具制造过程中选择最佳工艺参数。因此,在芯片制造过程中,诸如尺寸不正确,较大的表面凹坑,深的重铸层等之类的工艺输出误差将被最小化,这有助于实现更好的芯片性能。在当前的说明中,影响硬质合金压模性能的因素分为五个主要因素,即工作材料,机床,工具电极,模具的几何形状和加工操作。 GTA方法论表明机床具有最高的索引值。因此,它是影响模具性能的最大影响因素。在模具材料中,低钴浓度和小晶粒尺寸可获得良好的表面光洁度,而在机床中,放电能量较低(即,峰值电流,脉冲接通时间,伺服电压和脉冲断开时间的值较低)和较高的放电能量。介电流速产生良好的表面光洁度,因此有利于良好的芯片性能。在模具几何形状的情况下,较大的工件厚度和较小的锥角会导致较小的几何偏差,因此有助于获得更好的模具性能。

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