Degree Type


Date of Award


Degree Name

Master of Science


Industrial and Manufacturing Systems Engineering

First Advisor

Frank E. Peters


The data needed for quality control in the steel casting process is often difficult to obtain. This is especially true when referring to the surface quality of the part as it undergoes multiple inspections. A typical inspection involves identifying the location of anomalies and marking them for further processing in the cleaning room. Each time an inspector views a casting, information on the part surface quality is conveyed. This information however, is rarely available for analysis since it is recorded directly on the casting. A few foundries have attempted to collect this surface quality data (anomaly type, size, and location) as identified during inspection. Unfortunately, their data format is difficult to manage and has limited analysis opportunities. This paper presents a software program which removes the problems associated with current attempts at data collection. The program provides an easy to use interface for recording anomaly type and location directly on a 3D CAD model. Analysis modules designed for this data include histograms, frequency plots, area calculations, correlations, and principal component analysis (flaw pattern recognition). A case study for collecting and analyzing real data from a steel casting foundry was completed using this program. Some sample results from this study are included in this paper to illustrate benefits achieved from the data collected.


Copyright Owner

Scott Alan Von Busch



Date Available


File Format


File Size

61 pages