ABSTRACT
A robust hard-coated part surface is one that works as intended with full consideration of variation in the part’s manufacturing process, variation resulting from deterioration, and variation during real-time operations. The robust design of a hard alloy-coated part surface for maximum reliability is achievable through understanding which part and process design parameters are critical to the achievement of a performance characteristic and what the optimum values are to achieve the maximum reliability and quality characteristics that minimize failures and life cycle costs. When the operation of the part quality parameters and process performance condition characteristics can be mathematically related to part and process design parameters, the optimum part surface quality and the process performance parameters can then be determined with a regression model and a technological inheritance (TI) model. Since the hard alloy-coated materials, coated part, and process performance relationships are unknown, there is therefore the need for the design of experiments, which will help to develop a multivariate regression model that can aid in determining the part optimum quality and process performance conditions, which of course can be used to determine the optimum reliability and wear resistance coefcients of hard alloy-coated critical part surfaces, machine tools, and industrial equipment, thereby developing a more robust design.
