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Integrating Statistical Methods in Engineering Technology Courses

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Conference

2018 ASEE Annual Conference & Exposition

Location

Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

ET Pedagogy I

Tagged Division

Engineering Technology

Page Count

14

DOI

10.18260/1-2--30689

Permanent URL

https://peer.asee.org/30689

Download Count

201

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Paper Authors

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Sanjeevi Chitikeshi Old Dominion University

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Dr. Sanjeevi Chitikeshi is an Assistant Professor in Electrical Engineering Technology program at Old Dominion University, Norfolk, VA. Prior to current position, he worked at Murray State University, Murray, KY and also as a control engineer in industry in California. He earned both his Masters and Ph.D in Electrical and Computer Engineering from Sothern Illinois University, Carbondale, IL, in 2004 and 2007 respectively. His research interests are in Mechatronics systems, Big Data Analysis, Smart instrumentation and Controls for Biomedical Applications and Structural Health monitoring. He worked on funded projects from NASA, Caterpillar and Federal High way. He published journals and conference papers in the areas of smart instrumentation and control and mechatronics systems.

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Jake Hildebrant Murray State University

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Jake Hildebrant is an Assistant Professor in the Institute of Engineering at Murray State University and the program coordinator for the Electromechanical Engineering Technology program. He is also the program coordinator for the online Energy Management program at Madisonville Community College. He specializes in Motion Control, Robotics, Programmable Logical Controllers, Sustainability Management, Energy Systems, and Energy Management.

He received his Master's of Science Degree from Western Kentucky University in Engineering Technology Management and his Bachelor's of Science from Murray State University in Electromechanical Engineering Technology. Before teaching higher education, he worked over seven years for the federal government as an Instrument and Controls Technologist.

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Otilia Popescu Old Dominion University

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Dr. Otilia Popescu received the Engineering Diploma and M.S. degree from the Polytechnic Institute of Bucharest, Romania, and the PhD degree from Rutgers University, all in Electrical and Computer Engineering. Her research interests are in the general areas of communication systems, control theory, and signal processing. She is currently an Assistant Professor in the Department of Engineering Technology, Old Dominion University in Norfolk, Virginia. In the past she has worked for the University of Texas at Dallas, University of Texas at San Antonio, Rutgers University, and Politehnica University of Bucharest. She is a senior member of the IEEE, serves as associate editor for IEEE Communication Letters, and has served in the technical program committee for the IEEE ICC, WCNC, RWW, VTC, GLOBECOM, and CAMAD conferences.

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Orlando M. Ayala Old Dominion University

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Dr. Ayala received his BS in Mechanical Engineering with honors (Cum Laude) from Universidad de Oriente (Venezuela) in 1995, MS in Mechanical Engineering in 2001 and PhD in Mechanical Engineering in 2005, both from University of Delaware (USA). Dr. Ayala is currently serving as Assistant Professor of Mechanical Engineering Technology Department, Frank Batten College of Engineering and Technology, Old Dominion University, Norfolk, VA.

Prior to joining ODU in 2013, Dr. Ayala spent three years as a Postdoctoral Researcher at University of Delaware where he expanded his knowledge on simulation of multiphase flows while acquiring skills in high performance parallel computing and scientific computation. Before that, Dr. Ayala hold a faculty position at Universidad de Oriente at Mechanical Engineering Department where he taught and developed graduate and undergraduate courses for a number of subjects such as Fluid Mechanics, Heat Transfer, Thermodynamics, Multiphase Flows, Fluid Mechanics and Hydraulic Machinery, as well as Mechanical Engineering Laboratory courses.

In addition, Dr. Ayala has had the opportunity to work for a number of engineering consulting companies, which have given him an important perspective and exposure to industry. He has been directly involved in at least 20 different engineering projects related to a wide range of industries from petroleum and natural gas industry to brewing and newspaper industries. Dr. Ayala has provided service to professional organizations such as ASME. Since 2008 he has been a member of the Committee of Spanish Translation of ASME Codes and the ASME Subcommittee on Piping and Pipelines in Spanish. Under both memberships the following Codes have been translated: ASME B31.3, ASME B31.8S, ASME B31Q and ASME BPV Sections I.

While maintaining his industrial work active, his research activities have also been very active; Dr. Ayala has published about 90 journal and peer-reviewed conference papers. His work has been presented in several international forums in Austria, USA, Venezuela, Japan, France, Mexico, and Argentina. Dr. Ayala has an average citation per year of all his published work of 36.17.

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Vukica M. Jovanovic Old Dominion University Orcid 16x16 orcid.org/0000-0002-8626-903X

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Dr. Vukica Jovanovic is an Associate Professor of Engineering Technology in Mechanical Engineering Technology Program. She holds a Ph.D. from Purdue University in Mechanical Engineering Technology, focus on Digital Manufacturing. Her research is focused on mechatronics, digital manufacturing, digital thread, cyber physical systems, broadening participation, and engineering education. She is a Director of Mechatronics and Digital Manufacturing Lab at ODU and a lead of Area of Specialization Mechatronics Systems Design. She worked as a Visiting Researcher at Commonwealth Center for Advanced Manufacturing in Disputanta, VA on projects focusing on digital thread and cyber security of manufacturing systems. She has funded research in broadening participation efforts of underrepresented students in STEM funded by Office of Naval Research, focusing on mechatronic pathways. She is part of the ONR project related to the additive manufacturing training of active military. She is also part of the research team that leads the summer camp to nine graders that focus on broadening participation of underrepresented students into STEM (ODU BLAST).

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Abstract

Statistical methods and procedures are very important in engineering applications. In most of the engineering fields electronic devices are used as sensing and controlling components. Lack of proper calibration of these devices and of performance analysis using different statistical methods may lead to erroneous measurements and results. In medical or manufacturing areas such errors in the experimental results could be catastrophic. Applying different statistical tests and procedures enhance the quality of engineering work. Traditionally, most engineering curricula have at least one required course in applied statistics in engineering, but that is not generally the case in engineering technology programs. Most of the engineering technology BS graduates work as field engineers and collect the data from different physical processes and do data anaysis to validate the systems performances. Exposure to statistical methods use and data analysis will provide technology graduates with valuable skills in the current high tech job market. This paper focuses on how statistical analysis and methods using hand calculations and software tools can be integrated in undergraduate engineering technology courses, enhancing the hands on approach of real engineering projects with software assisted data analysis. Learning the skills of collecting experimental data from real processes and performing statistical analysis on it is the effective approach of solving engineering problems, and it provides higher learning outputs than simulation based approach. Specifically, integration of statistical analysis was introduced in an industrial instrumentation class, in which the lab component included the use of various sensors and other measurement instruments. By the end of the class, students demonstrated newly acquired statistical skills by performing sensor calibration and they also applied simple linear regression analysis model on the experimental data.

Chitikeshi, S., & Hildebrant, J., & Popescu, O., & Ayala, O. M., & Jovanovic, V. M. (2018, June), Integrating Statistical Methods in Engineering Technology Courses Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30689

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