Orthogonal Metal Cutting Operations
Finite Element Modeling and Taguchi Statistical Optimization
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With the advent of the powerful computers, numerical modeling of the manufacturing processes has gained much importance. As a numerical modeling technique, Finite Element Modeling (FEM) is one of the most important techniques that engineers utilize in order to simulate many hard-to-solve physical and mechanical problems. Cutting is considered as an extreme one because it is almost impossible for any physical device to exactly determine what is happening in the tool-chip contact areas. On the other hand, Design of Experiments (DoE) is a collection of statistical techniques intended to reduce th...
With the advent of the powerful computers, numerical modeling of the manufacturing processes has gained much importance. As a numerical modeling technique, Finite Element Modeling (FEM) is one of the most important techniques that engineers utilize in order to simulate many hard-to-solve physical and mechanical problems. Cutting is considered as an extreme one because it is almost impossible for any physical device to exactly determine what is happening in the tool-chip contact areas. On the other hand, Design of Experiments (DoE) is a collection of statistical techniques intended to reduce the number of experiments with the least adverse effects on the final outcome of the entire experimental setup. Orthogonal arrays are examples of balanced matrices that Taguchi method adopted it to economically optimize the experimentation processes. This book couples FEM and Taguchi statistical optimization to optimize orthogonal cutting operations using Deform 2D software. The outcome of this book should help engineers to emphasize the capabilities of coupling FEM and Taguchi method in optimizing one of the most extreme scenarios of the manufacturing processes.
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