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Statistical Methods Can Confirm Industry-sponsored University Design Project Results

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2018 ASEE Annual Conference & Exposition


Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

College Industry Partnerships Division Technical Session 3

Tagged Division

College Industry Partnerships

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Paper Authors


Robert J. Durkin Indiana University-Purdue University of Indianapolis

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Mr. Durkin teaches courses in Mechanical and Electrical Engineering Technology; including the capstone design and independent study projects. He serves as a Faculty Senator, and earned the 2013 Outstanding Teacher Award and the 2017 Trustees Teaching Award.
He has over 25 years of engineering and manufacturing experience including; design, project management, and various engineering, research and manufacturing leadership roles. He has been awarded two US patents.
He is an alumnus of Indiana Institute of Technology, and the University of Notre Dame; where he graduated Magna cum Laude.

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Paul Yearling P.E. Indiana University Purdue University, Indianapolis

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Paul Yearling
Education: PhD. Major: Mechanical Engineering, Minor: Applied Mathematics
Professional Engineer License
Certifications: Lean Six Sigma Black Belt
Current Position: Associate Chair Engineering Technology and Mechanical Engineering Technology Program Director

Industrial Experience

Over 20 years of industrial experience initially as a Royal Naval Dockyard indentured craftsman machinist and Design Draftsman and project manager on Leander class Steam Turbine Naval frigates and diesel electric submarines. Most recently includes 12 years in Research and Development and Lean Six Sigma process improvement experience troubleshooting process issues in the Paper, Chemical, and Converting Industries.

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An industry-sponsored project was recently developed to automatically inspect soup mix packages. The industry sponsor had determined that its highest customer complaint was the absence of a flavor packet within the soup mix package. It partnered with a local university to develop an automatic system to detect the missing flavor packet and remove it from the production line before the package was bulk-packed for shipment. The system was designed, built and installed by a team of EET and MET students. A four-hour production test confirmed that the percentage of soup mix bags without flavor packets detected by the machine was the nearly the same as the total percentage of bags without flavor packets returned by customers the previous year. But how reliable was the system over a longer period? This paper describes a semester-long university project to determine how well the inspection system performed on its production line for six-month period. The honors-student project would utilize multiple statistical methods to determine whether the automatic inspection system actually improved overall quality of the soup mix packages, and led to reduced customer complaints. The pedagogical features of the honors-student project are illustrated, and also include student comments and ratings of the effectiveness of the industry-university project.

Durkin, R. J., & Yearling, P. (2018, June), Statistical Methods Can Confirm Industry-sponsored University Design Project Results Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30984

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