Process capability indices (PCIs) provide numerical measures on whether a process conforms to the defined manufacturing capability prerequisite. In the literature some PCIs have been used to measure the ability of process to decide how well the process meets the specification limits (SLs). These have been successfully applied by companies to compete with and to lead high-profit markets by evalu...

Abstract—Process capability indices (PCIs) provide numerical measures on whether a process confirms to the defined manufacturing capability prerequisite. In the literature, some PCIs have been used to measure the ability of process to decide how well the process meets the specification limits (SLs). These have been successfully applied by companies to compete with and to lead high-profit market...

Innovation capabilities are the key ingredient in enhancing the firms’ competitiveness and ensuring their survival. Obviously, there are quite different in innovation activities between mauufacturing firms and service firms. It is necessary to consider the distinctness between them in evaluating firms’ innovation capabilities. This paper proposes a model of innovation capabilities in manufactur...

A wide array of organic chemicals occur in biosolids and other residuals recycled to land. The extent of our knowledge about the chemicals and the impact on recycling programs varies from high to very low. Two significant challenges in regulating these materials are to accurately determine the concentrations of the organic compounds in residuals and to appropriately estimate the risk that the c...

Abstract Gaussian Process (GP) regression models typically assume that residuals are Gaussian and have the same variance for all observations. However, applications with input-dependent noise (heteroscedastic residuals) frequently arise in practice, as do applications in which the residuals do not have a Gaussian distribution. In this paper, we propose a GP Regression model with a latent variab...