Washington, District of Columbia
June 23, 1996
June 23, 1996
June 26, 1996
1.269.1 - 1.269.4
Integration of Industrial and Manufacturing Systems Engineering Using a Microprocessor Controlled Injection Molding Machine: Applications of Statistical Process Control
Laura L. Sullivan and Courtney R. Oliver GMI Engineering& Management Institute
Abstract An independent study project was developed to apply the principles of statistical process control (SPC) to polymer processing using a new microprocessor controlled injection molding machine, purchased through a 1994 Instrumentation and Laboratory Improvement (ILI) award from the National Science Foundation. The project began with a machine capability study and an investigation of the SPC package on the machine. An investigation of the repeatability of specimens produced included mass, length and thickness measurements. Following this, a simulation designed to vary the viscosity of the material being processed was undertaken, and the SPC methods and measurements previously defined were applied in order to determine which machine monitors were capable of detecting slight changes in viscosity typical of material contamination. The hydraulic pressure applied when the machine switched from filling to packing the mold cavity proved to be excellent in detecting changes in material viscosity within only a few machine cycles. Use of this SPC technique can therefore halt production of polymer parts leading to poor quality soon after material contamination - or any other process variation leading to a change in material viscosity - occurs.
Introduction The injection molding of thermoplastics is as much art as it is science. Changes in processing parameters are known to have great influence on the properties of molded plastic; but changes of near equal magnitude can result from modest changes in environmental conditions, small differences between operators, or minimal material contamination. The focus of this project, conducted by an undergraduate industrial engineering student, was to quantify the level of contamination which could be detected by the machine even though it may remain undetected by the operator. Traditionally, small levels of contamination resulting in inferior geometric stability and mechanical properties may not appear obvious until a large number of parts have been produced and material wasted. Methods to detect changes in the polymer which can influence the quality of the final product are therefore very valuable. The use of statistical process control to measure the capability of the injection molding machine to stay within strict processing limits, and then the use of these limits to detect
?@& 1996 ASEE Annual Conference Proceedings ) ‘..+,m?j .
Sullivan, L. L., & Oliver, C. R. (1996, June), Integration Of Industrial And Manufacturing Systems Engineering Using A Microprocessor Paper presented at 1996 Annual Conference, Washington, District of Columbia. https://peer.asee.org/6130
ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 1996 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015