Statistical models commonly used in quality improvement studies often do not perform well when predictions are made away from the observed data points. Yet models based on engineering/physics laws don’t often reflect reality. Engineering/statistical models are proposed that overcome the disadvantages of the aforementioned models. The model is obtained through sequential adjustments to the engineering model and is based on empirical Bayes methods. The methodology is illustrated on a problem predicting surface roughness in a microcutting process and the optimization of a spot welding process.
© 2001-2024 Fundación Dialnet · Todos los derechos reservados