Abstract

Coatings are used to increase the surface quality of cutting tools, metal forming stamping, punching tool, plastic injection molding, sliding engine components for automobiles or decorative applications. Many parameters affect the manufacturing performance. Chromium nitride is frequently used for metal forming, plastic molding, medical implants and cutting tools because it has a low coefficient of friction, high hardness and good thermal stability. Optimizing multiattribute characteristics (MACs) requires experience but is crucial to the manufacturing process. This study uses a combination of entropy and range of value methods to optimize MACs to minimize surface roughness (E₁), flank wear (E₂) and hardness (E₃) for CrWN hard film tools that are used for turning AISI 304 stainless steel. And the results are compared with those for grey relational analysis (GRA). The L₉ Taguchi experimental data are used to rank the coating configurations (alternatives) for each experimental test, and a decision matrix is initially defined. The results show that flank wear (E₂) has the greatest effect on the outputs. Combination F₉ (A₃B₃C₂D₁) ranks highest of the coating configurations and the value is the same as that which is calculated using GRA. The proposed method features a relatively simple computational procedure and can be easily used by a technicians or engineers to optimize MACs for real manufacturing practices and environments.

中文翻译：

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优化车削AISI 304不锈钢时CrWN硬膜工具的多属性特性

摘要

涂层用于提高切削工具，金属成型冲压，冲孔工具，塑料注射成型，汽车或装饰应用的滑动发动机部件的表面质量。许多参数会影响制造性能。氮化铬由于具有低摩擦系数，高硬度和良好的热稳定性，因此经常用于金属成型，塑料成型，医疗植入物和切削工具。优化多属性特征（MAC）需要经验，但对制造过程至关重要。这项研究结合了熵和值范围方法来优化MAC，以最大程度地降低表面粗糙度（E ₁），侧面磨损（E ₂）和硬度（E ₃）用于车削AISI 304不锈钢的CrWN硬膜工具。并将结果与​​灰色关联分析（GRA）进行比较。的大号₉田口的实验数据被用于排序各实验测试的涂层结构（替代），和一个决策矩阵初始地被定义。结果表明，侧面磨损（E ₂）对输出的影响最大。组合F ₉（A ₃ B ₃ C ₂ D ₁）在涂层配置中排名最高，其值与使用GRA计算得出的值相同。所提出的方法具有相对简单的计算过程，并且可以被技术人员或工程师轻松地用来针对实际制造实践和环境优化MAC。