Categorical Performance Metrics

The nature of the performance metric, y, is determined by the characteristics of the specific process under analysis. Since we are particularly interested in analyzing situations where y is related to product or process quality, it is quite common to find systems where a categorical variable y is chosen to classify and evaluate their performance. This may happen due to the intrinsic nature of y (e.g., it can only be measured and assume qualitative values, such as good, high, and low ), or because y is derived from a quantization of the values of a surrogate continuous measure of performance (e.g., y = good if some characteristic z of the product has value within the range of its specifications, and y= bad, otherwise). 

In Section IV we considered a categorical performance metric y. Although that represents a common practice, especially when y defines the quality of a product or process operation, there are many instances where system performance is measured by a continuous variable. Even when y is quality-related, it is becoming increasingly clear that explicit continuous quality cost models should be adopted and replace evaluations of performance based on categorical variables. 

Both situations with categorical and continuous, real-valued performance metrics will be considered and analyzed. Since Taguchi loss functions provide quality cost models that allow the different objectives to be expressed on a commensurate basis, for continuous performance variables only minor modifications in the problem definition of the approach presented in Section V are needed. On the other hand, if categorical variables are chosen to characterize the system s multiple performance metrics, important modifications and additional components have to be incorporated into the basic learning methodology described in Section IV. 

The global thermoset resins market is expected to reach as high as 95 million metric tons by 2016 (Axis Research Mind report 2012). Excluding the alkyd resins, which are used primarily in the coatings, commercially important major types of thermoset resins, altuig with their relative % market share, estimated from literature (Fosdyke and Starr 2002), can be categorized as follows Polyurethanes (31 %), PhenoUcs (18 %), Amino resins (18 %), Unsaturated polyesters (12 %), Epoxies and other specialty/high performance thermosets (12 %), such as silicones, polyimides, bismaleimides (BMl), cyanate ester thermosets, etc. 

There are many ways to categorize safety performance measures. They are often classified as trailing or leading indicators, outcome or process oriented, results or activity-based measures, downstream factors or upstream factors, and/or qualitative or quantitative metrics. 

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