, marital status, number of children, parents’ educationalachievement and enrollment information.Table 2 contains the evaluation of the group performance. The enrolled students were dividedinto three groups because gauge R&R studies require at least two operators to be conducted.Student performance was evaluated as Exceptional (A-level), Effective (B-level), Acceptable (C-level) and Unsatisfactory (D-F level). In general, the student performance was unsatisfactory.Only one group performed a gauge R&R study using the steel rule at an acceptable level. Theanalyses of gauge R&R studies using the caliper and micrometer were unsatisfactory for everygroup. All groups made the same mistake when gathering data for the gauge R&R studies
, financial statements andfinancial accounting with special emphasis on the balance sheet and income statement, and costaccounting was covered. In part A of the case study, the students (working in groups of 4) wereassigned an in depth financial statement analysis on the large U.S. retailer that would sponsor thecase study problem for part B of the case study. The students were required to complete an indepth analysis of three years of corporate financial statements by completing a series of ratiocalculations. This would give the students real life practice working with corporate financialstatements and also allow them to gain an understanding and background of the large U.S.retailer that would be sponsoring the real life case study competition in
summary statistics, statistical models were builtto predict exam performance based on the variables outlined in the previous sections. Logisticregression was chosen because of the non-normality of the outcome variable (exam scores) andthe many categorical variables. For a logistic regression model, the outcome variable must bedichotomous. As a result, the exam score variable was transformed to a binary variable with 1indicating the score was 80% or higher (A or B) and 0 indicating the score was less than 80% (C,D, or F). Multinomial regression was considered but rejected because of concerns that there wasnot a large enough sample size for this technique.Instead of one model that predicts the overall course grade, three models were built to
field of engineering had become, a paper “Education forFactory Management” was presented by Hugo Diemer in 1903. He was on the faculty atPenn State and he played a pivotal role in the development of the first IndustrialEngineering program the country at that institution in 19084. Frank B. Gilbreth joinedS.P.E.E. in 1911 and he held a Symposium on Scientific Management in 1912. Anotherfounding father of Industrial Engineering, Frederick W. Taylor received an M.E. degreeat night from Stevens Institute of Technology in 1883. He died suddenly of pneumoniaon March 21, 1915 and his obituary appeared in the S.P.E.E. journal5.The Constitution of S.P.E.E. required that a group of members that desired officialrecognition be first formed as a Committee
syllabusThe main points discussed in classroom were: 1) The Decision Making Process 2) Review on Economic Engineering 3) Risk Analysis a. Definition; b. Decision tree analysis; c. Uncertainty analysis; d. Review on probability and statistics; e. Sensitivity analysis. Page 11.398.3 4) Implementation of Risk Analysis a. Petroleum Engineering applications. 5) Error and Uncertainty 6) Case Studies 7) Government Policies and RegulationsIn items 3, 4 and 5 various examples available in the current literature were discussed4,5,6,7,8. Acomputer software for Monte Carlo simulation of simple problems was distributed
reflections located relevant information located in these located in these in these cells B—Articulate uncertainties cells cells Step 2: EXPLORE C— Overall, FIRST Integrate multiple reflections Overall, SECOND perspectives and located in these reflections located clarify assumptions D—Qualitatively cells in these cells interpret information and create a Overall, SECOND meaningful reflections organization
?DisclaimerThe views expressed in this paper are those of the authors and do not necessarily reflect theofficial policy or position of the U.S. Air Force, the U.S. Department of Defense, or the U.S.Government.References 1. Lynch, P.C., Bober, C., Wilck, J.H., “An Integrated Approach to Developing Business Expertise in Industrial Engineering Students,” Proceedings of the 2015 ASEE Annual Conference & Exposition, 2015. 2. Barron, E., “Invent Penn State: Let’s turn great discoveries into a great economy, together” Penn State News, January 8th, 2015. 3. Archibald, M., Reuber, M., Allison, B., “Reconciling Well-defined Capstone Objectives and Criteria with Requirements for Industry Involvement,” Proceedings of the 2002 American
for the United States measured at 80 meters. It is important to note the wind energyresource is highly localized and driven in great part by large scale geographic topology. As withthe solar radiation data, data set used in this study is sponsored by NASA and can be accessed atthis site: http://eosweb.larc.nasa.gov/cgi-bin/sse/sse.cgi? As before, the location is specified byentering the latitude and longitude. For Manhattan, KS enter: 39, -96. When the parameterselection screen appears, refer to Figure 11, select from Meteorology (Wind) and then specifythree items: Meteorology (Wind) and a. Wind Speed at 50 meters and specify the following two adjustments b. Gipe Power Law rule with "Airport" flat roughness, and
of Engineering Education.3. Fragoso-Diaz, G. M., Gray, B., & Jones, E. (2015). Enhancing Students’ Learning Experience Using Case Studies. 122nd ASEE Annual Conference and Exposition. Seattle: American Society for Engineering Education.4. Gibson, J. D. (1998). The Use of Industrial Design Projects as a Means for Integrating Senior Engineering Design and Engineering Economics. 1998 ASEE Annual Conference and Exposition. American Society for Engineering Education.5. Hackney, R. A., McMaster, T., & Harris, A. (2003). Using cases as a teaching tool in IS education. Journal of Information Systems Education, 14(3), 229-234.6. Hartman, J. C. (1999). Readers' Forum: Suggestions for Teaching Engineering
follows: A. Easy-to-use – user-friendliness of software in terms of creating the simulation model, visualization, preparing animations, cooperation with Excel, preparing presentations, distinguishing various competence levels of users, B. Direct cooperation with a 3D model – students are very enthusiastic about working with 3D models, C. User-friendliness in terms of optimization possibilities D. Easy-to-create statistical distributions, E. Free access to the so called viewer, which makes it possible to start simulation without changing the model and input data, F. Elasticity, positive attitude of the software distributor towards the idea of cooperation between a university, industry and software distributor
for 12.5% (6 projects) of the projects. • A rate of return method was used for 8.33% (4 projects) of the projects. Page 24.771.4 • Both the manufacturing costs and breakeven analysis was performed for 4.167% (2 projects) of the projects. • The following methods were used by 2.08% (one project) of the projects: B/C ratio, estimation, future worth, and life cycle costs. • For industry types having more than four projects, no specific economic analysis method was used for all projects within that category.Figure 1: Number of engineering economic analysis methods used by the 48 projects. Forexample, 18.75% of the
Category 1 $926.11 Category 2 $472.99 Category 3 $454.08The hospital does not know the exact number of patients that they would expect to see in theevent of a tornado but they are interested in determining the average cost per patient. a. Determine the decision tree for this problem. b. Determine the expected value at each decision node. c. Determine the expected value for the costs associated with treating each patient.Observations, Conclusions and Future ResearchIn the teaching of the cost analysis, mathematical procedures are involved. A common problemis that at times students may be able to find the numerical solution but fail to understand
., Biggers, S. B., Moss, W. F., Ohland, M. W., & Schiff, S. D. (2010). Student-centered active, cooperative learning in engineering. International Journal of Engineering Education, 26, 1097-1110.Bishop, J. L., & Verleger, M. A. (2013). The flipped classroom: A survey of the research. Proceedings of the ASEE Annual Conference & Exposition. June 23-26, 2013. Atlanta GA.Norman, S. and Wills D., (2015). Flipped Classrooms in Economic Instruction –It’s not all or nothing, National Conference on Teaching and Research on Economic Education, May 27 - May 29, 2015. Minneapolis MN.Lavelle, J. P., Stimpson, M. T., & Brill, E. D. (2013). Flipped out engineering economy: Converting a traditional class to
University in 1975, and his masters in civil engineering from UAA in 1999. Page 15.1375.1© American Society for Engineering Education, 2010 Why Engineering Economy Professors Should Teach Introductory Corporate FinanceAbstractBoth engineering economy and finance focus their introductory courses on the time value ofmoney. Yet, in spite of this shared foundation, those courses are very different. This paperdiscusses what these differences are, why they occur, and what the disciplines can offer eachother. The goal is to help textbook authors and classroom teachers in each field to do a better jobof
allow students to become familiar with the terminology and concepts. It also includes developing lab modules for appropriate courses. An example of such an effort was conducted in the fall semester of 2012 in IEGR363: Manufacturing Processes, an IE core course. The course was conducted as a theme-based class having the theme, ‘efficient energy use in manufacturing’. The course also had a hands-on laboratory that included modules in energy auditing.Level 2: Development of interdisciplinary courses This would allow the skills needed for energy engineers to be gained. These courses are: a) Power and Energy use and auditing offered by electrical engineering department. b) Smart Building Technologies
, was below average in class performance. This student had a terrific attitude and seemedto want to learn for the sake of gaining the knowledge, not just for the grade. Our strugglingStudent 3 (class rank 17) had the third highest number of views and finished almost at the bottomof the class (barely earning a B). Students 3 and 12 would likely not have been as successfulwithout the videos. Out of curiosity, we noted the students who mentioned the videos as beinghelpful to their learning in the discussion board. They are shown in red in Figure 6.While this is just one class of 18 students, the analysis of the viewing data, coupled with thewritten feedback on the class, revealed some interesting information on videos views andperformance. If we
3 $2,000,000 4 $2,200,000 5 $3,000,000(a) Computer the IRR for this investment using trial and error method.(b) Would you accept this investment at MARR = 20% (Show your work for why)?ConclusionsThe educational case study presented in this paper is designed to highly replicate a real-worldinland waterway disruption scenario. A solutions manual is available to engineering educators bysubmitting an email request to the authors. The significance of this developed case study istwofold. First, it provides the students with a real-world engineering problem to apply andpractice their engineering economy and decision analysis skills
Production Functions. Atlantic Highlands,NJ: Humanities Press International, 1987.5) Leontief, Wassily W. The Structure of American Economy, 1919-1939: An Empirical Application ofEquilibrium Analysis. New York: Oxford University Press, 1951. Page 13.503.86) Chenery, Hollis B. "Process and Production Functions from Engineering Data.” Studies in the Structure of theAmerican Economy. Ed. Wassily Leontief. White Plains, NY: International Arts and Sciences Press, 1953.7) Swann, G.M. Peter. Engineering Economics: A Feasibility Study. Report to Department of Trade and Industry:Innovation Economics, Statistics and Evaluation Division. November
identified in considering the most useful engagement of EE@SL. 1) Traditional engineering design focuses mainly on the acquisition phase of the system life cycle, with too little attention given to commitments that affect outcomes during operation. 2) Traditional capital budgeting does not fully accommodate evolving mutually exclusive design alternatives as capital investment opportunities incorporating design optimization. Powerful approaches utilizing modeling and indirect experimentation (simulation) may be used to help narrow the undesirable gap between commitment and system specific knowledge within EE@SL. During design synthesis, A-A’ and B-B’ may be reduced by effective integration and adequate iteration
, this author was surprised by the treatment of one engineering economy topic in anarea so essential to the development of the inputs to the economic analysis at the core ofengineering economy. This paper discusses these treatments and their implications for theengineering economy discipline.IntroductionThe intent of this paper is not to point fingers at specific authors for their treatment ofengineering economy topics. The intent is to start a discussion of what the discipline needs to doto encourage better treatment of these topics in order that students have a better appreciation ofthe how to apply engineering economy in the practice of engineering. The idea for this paper hasbeen a long time in bubbling up to the surface. The author has been
AC 2012-5553: QUO VADIS, ENGINEERING ECONOMICSDr. John H. Ristroph, University of Louisiana, Lafayette John Ristroph is an Emeritus Professor at the University of Louisiana, Lafayette. This summer will mark his 42nd year of teaching engineering economics. He maintains his passion for the subject and is actively developing a novel computer-aided instructional system to enhance the self-learning that should be part of an engineering student’s homework experience. Page 25.1094.1 c American Society for Engineering Education, 2012 Quo Vadis, Engineering Economics
Paper ID #5751Present Value Analysis of Traditional LoansDr. Robert C. Creese, West Virginia University Dr. Robert C. Creese is Professor of Industrial Engineering and Graduate Program Director in the Indus- trial and Management Systems Engineering Department in the Benjamin M. Statler College of Engineer- ing and Mineral Resources at West Virginia University. He obtained his B.S., M.S., and Ph.D. degrees from the Pennsylvania State University(1963), the University of California-Berkeley(1964) and the Penn- sylvania State University(1972). He is a life member of ASEE, AACE-International and AFS as well as a member of
Paper ID #31339Engineering Economy Taught Across Engineering Disciplines: Work inProgressDr. Brian Aufderheide , Hampton University Dr. Brian Aufderheide is Chairperson in Chemical Engineering at Hampton University. He completed his PhD in Chemical Engineering at Rensselaer Polytechnic Institute. His areas of expertise are in advanced control, design, and modeling of biomedical, chemical, and biological processes. He has consulted for both medical device and biotechnology companies. He was sole engineer and QC supervisor of a 40MM lb/yr custom extrusion company. He has over 15 years of experience in education developing over
AC 2012-3318: THIS VIDEOGAME IS JUST LIKE MY PLANT!Mr. Leonardo Rivera, Universidad Icesi Leonardo Rivera has a Ph.D. in industrial and systems engineering from Virginia Tech. He is Head of the Department of Industrial Engineering, Universidad Icesi, Cali, Colombia.Mr. Andrs Lpez, Universidad Icesi Andrs Lpez has a M.Sc. in society of information from Universitat Oberta de Catalunya, a M.B.A. from Universidad Icesi, and a B.Sc. in business administration from Universidad Icesi. He is Director of the specialist degree in environmental management at Universidad Icesi.Mr. Andrs Caldern, Universidad Icesi Andrs Caldern is a specialist in the teaching of history at the Universidad del Valle. He is also a Historian at
AC 2008-2956: CONTEXT-BASED PROBLEMS AND EXERCISES FORTEACHING ENGINEERING ECONOMYRajkamal Kesharwani, Virginia Polytechnic Institute and State University Rajkamal Kesharwani is an MS student in the Industrial and Systems Engineering Department at Virginia Tech. His interests include decision making in engineering design and design economics.Xiaomeng Chang, Virginia Polytechnic Institute and State University Xiaomeng Chang is a doctoral student in Industrial and Systems Engineering at Virginia Tech with an expected graduation in May 2008. Her research and teaching interests are primarily focused in the areas of engineering design, integration and knowledge environments.Janis Terpenny, Virginia Polytechnic
Paper ID #7050Evaluation of Perceptual Changes in an Engineering Sales ProgramDr. David Paul Sly, Iowa State University Dr. Dave Sly is a Professor of Practice within the Industrial and Manufacturing Systems Engineering department. He is a registered Professional Engineer with B.A., M.S. and Ph.D. degrees in Industrial En- gineering, as well as an M.B.A. in Marketing from Iowa State University. In addition to teaching, Dr. Sly is president of Proplanner, an Industrial Engineering software company located in the ISU Research Park. For the past five years, Dr. Sly has worked extensively with business and academia on the
Paper ID #34185Curriculum Element: Using the Wall Street Journal to Provide Nationaland Global Perspectives in an Engineering Economy CourseDr. James Burns, Western Michigan University Jim Burns, Ph.D. Assistant Professor Industrial and Entrepreneurial Engineering and Engineering Man- agement Department Bio: Jim Burns holds a Ph.D. in Industrial Engineering from Western Michigan University, and has more than 10 years industry experience in the manufacturing sector in a variety of roles including process engineering, operations management, and technical sales. His area of expertise centers on applying OR/MS and Simulation
AC 2008-267: DOES CLASS SIZE MATTER? REFLECTIONS ON TEACHINGENGINEERING ECONOMY TO SMALL AND LARGE CLASSESJoseph Hartman, University of Florida Joseph Hartman received his PhD in Industrial and Systems Engineering from Georgia Tech in 1996. He has served as Director of the Engineering Economy Division of ASEE and is currently Editor of The Engineering Economist. Page 13.449.1© American Society for Engineering Education, 2008 Does Class Size Matter? Reflections on Teaching Engineering Economy to Small and Large ClassesAbstractHaving recently transitioned from a small, private university
Education, 2007 Spreadsheet Techniques for Engineering Professors: The Case of Excel and Engineering EconomicsAbstractThis paper provides engineering professors with techniques for using spreadsheets to improveteaching. It focuses on how to use the software, rather than classroom dynamics, by explainingmethods for applying Excel to engineering economics that can be used in other disciplines. Itfirst discusses intrinsic functions, and then it develops custom functions that use notation familiarto a student, such as PF(i , n) for (P|F, i , n). Next it covers how to produce diagrams and graphicsvia the drawing toolbar and custom cut-and-paste libraries, as well as how to show all formulasand logic rather than just numeric
Paper ID #18126Case Studies Under Your Nose: Using Campus Projects as Case Studies forEngineering EconomyAimee T Ulstad P.E., Ohio State University Aimee Ulstad, P.E is an Associate Professor of Practice in the Integrated Systems Engineering Department at The Ohio State University. Prior to joining the faculty at Ohio State, Aimee was an industry professional in various field in engineering for over 30 years. Aimee received her degrees in Mechanical Engineering and Masters in Business Administration from Ohio State. She began her career as a packaging equipment engineer at Procter and Gamble, then moved to Anheuser-Busch