Visual Data's Effect On Quality And Productivity At A Tier One Automotive Components Manufacturer
- Conference
- Location
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Honolulu, Hawaii
- Publication Date
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June 24, 2007
- Start Date
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June 24, 2007
- End Date
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June 27, 2007
- ISSN
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2153-5965
- Conference Session
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Technology Integration in the Classroom for Manufacturing II
- Tagged Division
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Manufacturing
- Page Count
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9
- Page Numbers
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12.1591.1 - 12.1591.9
- DOI
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10.18260/1-2--3047
- Permanent URL
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https://peer.asee.org/3047
- Download Count
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427
Paper Authors
Thomas Smith Purdue University
Thomas D. Smith is an industrial engineer with a large manufacturer of pneumatic automation products. He holds a master's degree in Technology and a bachelor's degree in Industrial Engineering from Purdue University; he has over 10 years of industrial engineering experience with emphasis on lean manufacturing, plant layout, and continuous improvement. Mr. Smith has provided engineering services to companies such as General Motors, Delco Electronics, Ingersoll-Rand, and ITT Aerospace.
Niaz Latif Purdue University
Dr. Niaz Latif is Professor of Industrial Technology and Assistant Dean for Statewide Technology Administration at Purdue University. He was ETD program chair for the 2003 Conference on Industry Education Collaboration (CIEC), and he served as the Director and Secretary of the Executive Board of the Engineering Technology Leadership Institute (ETLI). He is a program evaluator for Mechanical Engineering Technology and also Manufacturing Engineering Technology under the Technology Accreditation Commission (TAC) of the Accreditation Board for Engineering and Technology (ABET). Dr. Latif is currently the Editor-in-Chief for the Journal of Engineering Technology.
Stephen Elliott Purdue University
Dr. Elliott is an Associate Professor in the Department of Industrial Technology. He teaches a junior-level course in Automatic Identification and Data Capture (AIDC), and two graduate-level courses, Biometric Technology and Applications, and AIDC for the Enterprise. He is the past Vice Chair of the International Committee for Information Technology Standards, and has been the Head of Delegation for the WG1 Vocabulary working group within the ISO/IEC JTC 1 SC37 committee on Biometrics. Dr. Elliott is the head of the Biometrics Standards, Performance, and Assurance Laboratory at Purdue University. He is also involved in educational initiatives for the American National Standards Institute, and is a member of Purdue University's e-Enterprise, Learning, and CERIAS Centers.
Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract
Visual Data’s Effect on Quality and Productivity at a Tier One Automotive Components Manufacturer
Abstract
To remain competitive in their market, manufacturers must employ timely measurement of performance such as productivity and quality. A solution to this problem is the implementation of visual data-based information systems that can provide a manufacturer with productivity and quality performance information quickly. These systems will help the manufacturer make quick decisions related to scrap, re-work, and poor performance, thus reducing the production costs.
For this project, a single production assembly line was chosen at a tier-one automotive components manufacturing plant. A visual data system was implemented on a high-volume production line and thus provided the manufacturer with productivity and quality performance information quickly. After the implementation, the quality and productivity of the production line were observed to be significantly higher. The average number of defects was reduced by 30%, and the average number of parts produced per person per hour was increased by 5% for the production line.
Sharing the project with undergraduate/graduate students in the manufacturing field will help students understand the application of manufacturing methods/technology and see the relevancy of their learning as connected to the industry. Therefore, the students in manufacturing will appreciate the immediate applicability of their classroom learning in improving productivity and quality.
Introduction
In the manufacturing sector, automotive manufacturers are experiencing increased competitiveness as the market becomes increasingly global. This increased competition has made the automotive manufacturing environment more information driven and has increased the need to measure manufacturing performance on a timely basis. If timely measures of performance such as productivity and quality are not taken and evaluated, manufacturers will have difficulty remaining competitive in their market. Visual data-based information systems can provide manufacturers productivity and quality performance information quickly so that decisions concerning scrap, rework, and poor performance can be evaluated quickly.
This project deals with a production line (for automotive components) where visual performance measures were implemented and the resulting impact on quality and productivity. Implementation of the visual system in this production line has never been implemented before so there was no historical data to support a cost savings in similar high volume automotive components cases. The motivation for such implementation was to see if a visual data system would result in a cost savings through increased quality of the automotive components, or increased productivity.
Smith, T., & Latif, N., & Elliott, S. (2007, June), Visual Data's Effect On Quality And Productivity At A Tier One Automotive Components Manufacturer Paper presented at 2007 Annual Conference & Exposition, Honolulu, Hawaii. 10.18260/1-2--3047
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