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Optimisation of the Bauer Equation Using the Least Squares Method for Thermoplastics Turning

机译:用最小二乘法转向的最小二乘法优化鲍瓦方程

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摘要

>A number of equations are available for predicting the output of machining processes. These equations are most commonly used for the prediction of surface roughness after tooling. Surface roughness can be influenced by many factors, including cutting parameters, tool geometry and environmental factors such as the coolant used. It is difficult to create a universally applicable equation for all machining because of the variations in different materials' behaviours (e.g. metal, wood, plastic, composite, ceramic). There are also many differences between the various types of machining process such as the machining tools, rotational or translational movements, cutting speeds, cutting methods, etc. The large number of parameters required would make such an equation unusable, and difficult to apply quickly. The goal is thus to create a simple formulation with three or four inputs to predict the final surface roughness of the machined part within adequate tolerances. The two main equations used for this purpose are the Bauer and Brammertz formulas, both of which need to be optimised for a given material. In this paper, the turning of thermoplastics was investigated, with the aim of tuning the Bauer formula for use with thermoplastics. Eleven different plastics were used to develop a material-dependent surface roughness equation. Only new tooling inserts were used to eliminate the effects of tool wear.
机译:>可以使用许多方程用于预测加工过程的输出。这些方程最常用于工具后表面粗糙度的预测。表面粗糙度可能受到许多因素的影响,包括切割参数,工具几何形状和环境因素,例如所使用的冷却剂。由于不同材料的行为(例如金属,木材,塑料,复合,陶瓷),难以为所有加工创造一个普遍适用的等式(例如,金属,木材,塑料,复合,陶瓷)。各种类型的加工过程之间也存在许多差异,例如加工工具,旋转或平移运动,切割速度,切割方法等。所需的大量参数将使这样的等式不可用,并且难以快速施加。因此,目标是创造具有三个或四个输入的简单配方,以预测机加工部分的最终表面粗糙度在足够的公差中。用于此目的的两个主要方程是鲍尔和Brammertz公式,两者都需要针对给定材料进行优化。在本文中,研究了热塑性塑料的转弯,目的是调整鲍尔配方以用于热塑性塑料。使用11种不同的塑料来开发材料依赖性表面粗糙度方程。只使用新的工具插入物来消除工具磨损的效果。

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