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Implementing The Use Of Statistical Analysis Tools In The Manufacturing Processes Of The Automotive Industry

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2009 Annual Conference & Exposition


Austin, Texas

Publication Date

June 14, 2009

Start Date

June 14, 2009

End Date

June 17, 2009



Conference Session

Research and Project Initiatives in IT and IET

Tagged Division

Engineering Technology

Page Count


Page Numbers

14.698.1 - 14.698.13



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Paper Authors


Immanuel Edinbarough University of Texas, Brownsville

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Dr. Immanuel Edinbarough is a Professor in the department of Applied Engineering Technology at the University of Texas at Brownsville. He has successful track record spanning over 25 years in the service oriented and challenging fields of academia, industry and military. He is a hands-on manufacturing expert who has worked in several areas of engineering, manufacturing, and technical management including research, design, and production of mechanical, electronic, and electromechanical systems. Recognized trainer and resource person in the fields of CAD/CAM/CIM, Robotics and Automation, Machine vision, ISO 9000 and Lean Six Sigma. He has published several papers, in these areas, in various national & international conferences and journals. He has won several teaching awards including the recent academic excellence award, NISOD 2008, from the University of Texas at Austin.

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Karla Ramirez University of Texas, Brownsville

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NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Implementing the use of Statistical Analysis Tools for the Optimization of Manufacturing Processes in the automotive industry


Senior design project in the Engineering and Technology curriculum provide an excellent opportunity for the students to experience for the first time the real world application of engineering and mathematical tools. Project based learning such as the senior design project bring the students close to the teacher and shop floor engineers and teaches them the art of confidently approaching the intricate shop floor problems and propose optimum solutions. This article looks at the successful trouble shooting and problem solving approach to a complex manufacturing problem attempted through the application of Statistical Analysis Tools.


Project-Based learning (PBL) is an innovative teaching methodology available to teachers in the form of senior design projects. PBL is designed to make learning relevant and useful to students through the establishment of connections outside of the classroom1. The main objective of the senior design project is to provide an opportunity to the student to attempt a real life engineering problem and solve it with the flexible use of engineering, mathematical and scientific concepts learnt in the program. In this aspect, university and industry cooperation plays a vital role in providing and trusting the student with a complex practical industrial problem. The senior design study presented in this article explores the trouble shooting and successful implementation of statistical analysis tools for the optimization of manufacturing process in an automotive industry.

The industry sponsor for this project is a leading global supplier of mobile electronics and transportation systems for automobile industries including safety and security systems. Products and systems from this industry are engineered to meet and exceed the rigorous standards of the automotive industry. The automotive industry is the industry involved in the design, development, manufacture, marketing, and sale of motor vehicles. In 2008, more than 73 million motor vehicles, including cars and commercial vehicles were produced worldwide2. However, the quality of the products is an important issue that needs to be addressed consistently. All the products from the sponsor industry including the airbag deployment system, which is the product chosen for the study, are designed and produced to meet or exceed customer requirements.

The airbag deployment system offers self-contained assessment of occupant size and proximity during airbag deployment and adjusts its output to provide an appropriate level of restraint. The airbag lowers its deployment energy for near-proximity occupants, helping to reduce the need for seat-based suppression systems. This is achieved through the control of a parameter known as ‘High Slope.’ The high slope is the mathematical calculation of the output pressure in KPa in relation to the time in ms, and it is measured in KPa/ms. The slope is the rate of output pressure (KPa/ms) measured in the time between the 10 % and the 50 % of the peak pressure, which means how fast the output pressure passes through the gates. The airbag deployment systems that have failed the inspection have high slope conditions. This was severely affecting the sponsor

Edinbarough, I., & Ramirez, K. (2009, June), Implementing The Use Of Statistical Analysis Tools In The Manufacturing Processes Of The Automotive Industry Paper presented at 2009 Annual Conference & Exposition, Austin, Texas. 10.18260/1-2--4973

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