SGER: Identification of General Probability Models for a Taxonomy of Manufacturing Processes

Arizona State University, Scottsdale AZ

Investigators

Abstract

The objectives of this Small Grant for Exploratory Research (SGER) are to: 1) Create general probability models for key quality characteristics of a subset of the taxonomy of manufacturing processes. The selected taxonomy will specify the following classifications (a) the type of Geometric dimensioning and tolerancing (GD&T) requirements for form and location. (b) the type of manufacturing process and product material; and (c) the type of inspection device. The models will be chosen based on their accuracy and generality in representing the realistic behavior of process outputs; and 2) For each of the general probability models, define an appropriate summary statistic that incorporates the engineering requirements and the random nature of the process behavior. Having studied the output from various materials, processes measurement devices, complex GD&T acceptance zones, and normal/non-normal univariate/multivariate distributions in the first part of this research, we plan to define a set of statistics useful for summarizing performance and setting goals. Summary statistics will be chosen based on their distributional properties and will be used to define sample size requirements and critical acceptance values useful for supporting vendor relations and setting process performance goals. The results of this research will constitute a complete methodology for capturing and summarizing the behavior of inspection data (i.e.. probability' models). Data sets provided by industrial partners (Intel. Motorola. and Simula Safety Systems) will provide the modeling environment and validation of research. The project's deliverable will be a published catalogue of probability models that can be directly mapped to form and location GD&T requirements, manufacturing processes, materials and measurement systems for a subset of entries in the manufacturing taxonomy. Should this research prove successful. a follow-on project will be prepared for more categories in the taxonomy. In total, this research project is expected to have usable models for industrial decision-making, planning, and analysis as well as the theoretical contributions in performance summary statistics.