Design for Quality Approach to Improve Surface Roughness in Milling Operations

G. Abdou, N. A. Basaly
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Abstract

Tooling related malfunction is of particular concern, since tooling condition can cause loss of dimensional part accuracy and loss of the required surface finish. Out of specifications surface parameters will often be confined to less than quality making features and hence affect manufacturability. There is an eminent need for a methodology that enables process designers to evaluate and improve the quality manufacturability of the milling process before machining. This paper describes a methodology of design for quality manufacturability that enables product designers to evaluate, quantify and improve surface roughness in the design stage for milling operations. Different experiments have been conducted to measure cutting forces and surface roughness parameters under dry cutting conditions. The relationships between different operating parameters to the cutting force and surface roughness parameters were examined through extensive experimental work. Different relationships have been developed between five surface roughness parameters and three operating parameters. Further analysis has been conducted on the cutting force pattern: seasonal pattern, nonlinear trend and peak. The results generated from the study are very important for the parameters’ design of manufacturability for the milling operation. The basis for the design for quality is a set of common classes of quality defects (errors), and a set of factors that influence the occurrence of the less quality. The concept of quality errors and the derivation of the index matrix are presented.
改善铣削操作表面粗糙度的质量方法设计
刀具相关的故障是特别值得关注的,因为刀具状况会导致尺寸零件精度的损失和所需表面光洁度的损失。超出规格的表面参数通常局限于低于质量的制造特征,从而影响可制造性。迫切需要一种方法,使工艺设计人员能够在加工前评估和提高铣削工艺的可制造性质量。本文描述了一种设计质量可制造性的方法,使产品设计师能够在铣削操作的设计阶段评估,量化和改善表面粗糙度。在干切削条件下,进行了不同的切削力和表面粗糙度参数测量实验。通过大量的实验研究了不同操作参数与切削力和表面粗糙度参数之间的关系。五个表面粗糙度参数与三个操作参数之间建立了不同的关系。进一步分析了切削力的变化规律:季节性、非线性趋势和峰值。研究结果对铣削加工工艺性参数的设计具有重要意义。质量设计的基础是一组常见的质量缺陷(错误)类别,以及一组影响低质量发生的因素。给出了质量误差的概念和指标矩阵的推导。
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