Date of Award

4-2005

Degree Name

Master of Science in Engineering

Department

Industrial and Manufacturing Engineering

First Advisor

Dr. David Lyth

Second Advisor

Dr. Paul Engelmann

Third Advisor

Dr. Azim Houshyar

Fourth Advisor

Dr. Steven Butt

Access Setting

Masters Thesis-Open Access

Abstract

Customer demands for high-quality, defect-free injection-molded products are ever increasing. In order to satisfy these quality requirements, much effort is spent monitoring and controlling variable data such as cycle time, part weight, and dimensions. Attribute defects such as sink or splay are often overlooked in the development of process control systems. However, customers reject products because of these attribute defects. Industrial control systems based upon process variables and product design variables can detect conditions that may result in the molding of products with attribute defects. The systems can then correct the process prior to the molding of these defective products.

This research included process experimentation and the construction of a measurement system to facilitate the collection of data. The data were analyzed and a model was regressed to predict attribute defects in injection-molded parts based upon process and product characteristics. The primary goal of the research was to develop a statistically derived model of the sink phenomenon that can be applied to process control.

Comments

Fifth advisor: Dr. Philip Guichelaar

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