A Process Capability Index for Three-Dimensional Data - Fotak, Veljko
32,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in über 4 Wochen
  • Broschiertes Buch

I discuss the estimation of a process capability index for three-dimensional data. Initially, I focus on the case in which the engineering tolerance associated with the measurements is a sphere. Then, I extend the discussion to the more general case in which the engineering tolerance is ellipsoidal. In both cases, I develop summary measures for repeatability and reproducibility, to be used in the context of a process capability index. In the spherical tolerance case I define summary measures, where each measure is based on the diameter of a sphere that leads to a pre-specified capture rate. As…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
I discuss the estimation of a process capability index for three-dimensional data. Initially, I focus on the case in which the engineering tolerance associated with the measurements is a sphere. Then, I extend the discussion to the more general case in which the engineering tolerance is ellipsoidal. In both cases, I develop summary measures for repeatability and reproducibility, to be used in the context of a process capability index. In the spherical tolerance case I define summary measures, where each measure is based on the diameter of a sphere that leads to a pre-specified capture rate. As a process capability index, I propose ratios, where each ratio is the diameter of such a sphere divided by the diameter of the tolerance sphere. In the ellipsoidal tolerance case, such summary measure is based on the length of the major axes of the ellipsoid of identical shape and orientation to the tolerance ellipsoid providing a pre-specified capture rate. As a process capability index, Ipropose ratios, where each ratio is the major axis of such ellipsoid divided by the major axis of the tolerance ellipsoid.
Autorenporträt
Veljko Fotak earned a BS degree in Business Administration, an MBA with a concentration in Finance and an Master of Science in Applied Statistics from the Rochester Institute of Technology, in Rochester, NY. He is currently a PhD candidate at the University of Oklahoma and a Senior Research Associate at the Fondazione Eni Enrico Mattei.