A Study of Process Variability of the Injection Molding of Plastics Parts Using Statistical Process Control (SPC)

Rex C Kanu

Download Paper | Permalink

Conference: 2013 ASEE Annual Conference & Exposition
Location: Atlanta, Georgia
Publication Date: June 23, 2013
Start Date: June 23, 2013
End Date: June 26, 2013
ISSN: 2153-5965
Conference Session: Practical Teaching
Tagged Division: Manufacturing
Page Count: 9
Page Numbers: 23.110.1 - 23.110.9
DOI: 10.18260/1-2--19124
Permanent URL: https://peer.asee.org/19124
Download Count: 3633

Paper Authors

biography

Rex C Kanu Ball State University

visit author page

Dr. Rex Kanu is the coordinator of the manufacturing engineering technology program at Ball State University, where he teaches plastics materials and processing.

visit author page

Download Paper | Permalink

Abstract

A Study of Process Variability of the Injection Molding of Plastics Parts Using Statistical Process Control (SPC)Process variability in the manufacturing of products is a serious concern because if leftunchecked could lead to product wastes such as a scraps, low productivity, and poor qualityproducts. To prevent these unwanted effects from happening, statistical process control (SPC), astatistical tool, is used to monitor and control process variability. SPC assumes thatmanufactured products have measureable attributes such as mass, dimensions of the products,mechanical properties, and visual appearance to name a few. These attributes are affected bynatural and assignable causes. Natural causes are inherent to the process and may includevariables such as ambient temperature, machine vibration, and relative humidity; these variablesare often very difficult to control. Unlike natural causes, assignable causes are controllable andmay include items such as bad or worn-out machine components that should be replaced. Bymonitoring a process, an assignable cause is detected when process variability exceeds theexpected range caused by natural causes. The primary advantage of SPC is that it detects afaulty process, which if corrected, prevents the manufacturing of defective products unliketraditional quality control practice that identifies defective products after they have beenproduced. The traditional method of quality control leads to a costly manufacturing process.In a manufacturing engineering technology program, SPC was used to monitor and control theinjection molding of plastics parts. Students monitored several injection molding processvariables using SPC x-bar and range control charts while producing 300 plastics parts. The massof the products was used as an attribute representing parts quality. After analyzing the processdata, students were able to determine if the process was stable, that is, in control. Results of thisstudy will be presented at the annual conference. Also to be shared with the audience is thestudents’ learning outcomes that emanates from integrating SPC with the injection moldingprocess.

Citation
Format

Kanu, R. C. (2013, June), A Study of Process Variability of the Injection Molding of Plastics Parts Using Statistical Process Control (SPC) Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--19124

TY - CPAPER
AB - A Study of Process Variability of the Injection Molding of Plastics Parts Using Statistical Process Control (SPC)Process variability in the manufacturing of products is a serious concern because if leftunchecked could lead to product wastes such as a scraps, low productivity, and poor qualityproducts. To prevent these unwanted effects from happening, statistical process control (SPC), astatistical tool, is used to monitor and control process variability. SPC assumes thatmanufactured products have measureable attributes such as mass, dimensions of the products,mechanical properties, and visual appearance to name a few. These attributes are affected bynatural and assignable causes. Natural causes are inherent to the process and may includevariables such as ambient temperature, machine vibration, and relative humidity; these variablesare often very difficult to control. Unlike natural causes, assignable causes are controllable andmay include items such as bad or worn-out machine components that should be replaced. Bymonitoring a process, an assignable cause is detected when process variability exceeds theexpected range caused by natural causes. The primary advantage of SPC is that it detects afaulty process, which if corrected, prevents the manufacturing of defective products unliketraditional quality control practice that identifies defective products after they have beenproduced. The traditional method of quality control leads to a costly manufacturing process.In a manufacturing engineering technology program, SPC was used to monitor and control theinjection molding of plastics parts. Students monitored several injection molding processvariables using SPC x-bar and range control charts while producing 300 plastics parts. The massof the products was used as an attribute representing parts quality. After analyzing the processdata, students were able to determine if the process was stable, that is, in control. Results of thisstudy will be presented at the annual conference. Also to be shared with the audience is thestudents’ learning outcomes that emanates from integrating SPC with the injection moldingprocess.
AU - Rex C Kanu
CY - Atlanta, Georgia
DA - 2013/06/23
PB - ASEE Conferences
TI - A Study of Process Variability of the Injection Molding of Plastics Parts Using Statistical Process Control (SPC)
UR - https://peer.asee.org/19124
DO - 10.18260/1-2--19124
ER -