configuration.Taguchi Methods of optimization does not promise to outperform more traditionalmethods of optimization. However, applying these procedures is extremelystraightforward, and a true optimal solution is obtained. Numerous experiences havedemonstrated that Taguchi Methods are the most underutilized design tool.Bibliography1. Anderson, V. L. and McLean, R. A., Design of Experiments: A Realistic Approach, Marcel Dekker Inc., 1974.2. Barker, T. B., Quality by Experimental Design, Marcel Dekker Inc., 1985.3. Barker, T. B., "Quality Engineering By Design: Taguchi’s Philosophy," Quality Progress, December 1986, pp. 32-42.4. Box, G. E. P., W. G. Hunter, and J. S. Hunter, Statistics for Experimenters: An Introduction to Design, Data
andenrollment in courses, the university would not exist. So, why should the university own theirpatent rights?Based the above argument, two cases were established. Case I was student ownership of thepatent rights, and Case II was university ownership. For Case I, it was decided that ownershipof any patent evolving from student work submitted in fulfillment of academic requirementswould remain with the student inventor(s). Here the inventors would pay for the patentapplication and maintenance fees if the students elected Case I. The students who were takingthe New Product Development and Entrepreneurship courses were required to sign a copyrightand patent disclosure. Any discovery or invention would be disclosed to the University’sIntellectual Property
members have evenassisted in push back, ground handling, and taxing of 777’s, 747’s, 767’s, etc. Being able towork in the “live” environment that they are studying allows the student the chance to use theknowledge they have learned. The exposure to the world is something sitting in a classroom Page 6.905.3 Proceedings of the 2001 American Society for Engineering Education Annual Conference & Exposition Copyright 2001, American Society for Engineering Educationcan’t offer. Working from the “ground up” the students interact with frontline employees toStation Managers, all the way to Vice Presidents.Once the
Page 6.1110.3 Figure 1. MATLAB listings for Exercise 1 Proceedings of the 2001 American Society for Engineering Education Annual conference & Exposition Copyright 2001, American Society for Engineering Education Session 2793function fx = factdiv(m, n)% this function implements m!/n!, where m>=n% m!/n! = m * (m-1) * ...*(n+1)fx = 1;for i=(n+1):m fx = fx*i;end L istin g 1 . M A T L A B fu nctio n fa c td iv.m to co m pu te ratio o f tw o facto rialslambda = (1/2)*1/(60*60) %calls/s each userH = 3*60 % call duration in secondsAu = H*lambda;C=40;U=(2*C):(4*C):(100*C); %range on
enhanced by the opportunity to involve themselves in workwhich is not as directly related to their academic world (2,3). The ability to be away from thecampus setting can allow different views and interpretations of the topics normally pursued oncampus. Other reasons for a sabbatical leave include allowing the faculty member to becomepart of the industrial environment, allowing better correlation between topics which are taught inthe classroom and the knowledge actually used by graduates in industry (4,5).Criteria for a sabbaticalTypically the faculty member requesting a sabbatical leave must have been employed as afaculty member for a minimum of seven years, or have worked at least seven years since a priorsabbatical leave. S/he will make a
have attained these skills in a natural way. Yet thevast majority of us require(s) some training to develop proper problem solving skills. Providing thistraining is perhaps one of the most important responsibilities resting with our educators. All too oftenstudents ‘pick up’ problem solving skills through experience or as a bye product of doing exercises inmathematics or science classes. Watching the teacher or the textbook author plow through someproblem situations can also lead to some lasting spin-offs.” Herbert A. Hauptman, Nobel Laureate inChemistry. The reason Hauptman has been quoted for this paper is obvious. A medical theory of effectiveengineering and technology and problem solving will be discussed. The other objective of
given strategy supports, atleast to some extent, a particular outcome. Page 6.186.4Proceedings of the 2001 American Society for Engineering Education Annual Conference & ExpositionCopyright © 2001, American Society for Engineering Education Table 1. Relationship Between Strategies and Outcomes on ps am s ti
Session 2520 A Paced Web-Taught Course in Numerical Methods in Engineering William S. Duff, Devin Shunk Department of Mechanical Engineering Colorado State UniversityI. IntroductionIn fall semester 2000 we instituted a paced Internet taught sophomore level numerical methodscourse for engineers. This WebCT1 based course is taught completely on the Internet.The course is taught to an average of 60 students each semester. A number of prospectivetransfer students are located at several two-year feeder institutions that are over three hours
Session 1547 PLC Systems - University Course Material or Industrial Training Material ? Don Zeller Assistant Professor, Engineering Technology Department, Fenn College of Engineering, Cleveland State UniversityIntroductionIn the late 1960’s, a new electronic device made its debut, at the request of the automotiveindustry. It was called a programmable logic controller (PLC) and its function was to replace anexisting system of machine control logic. The existing system was based on an electro-mechanical device called a relay and the machine
reversible adiabatic machines. Thus 2I isthe discharge from an ideal or isotropic turbine and 4I is the discharge from an ideal pump. Proceedings of the 2001 American Society for Engineering Education Annual Conference & Exposition Copyright2001, American Society for Engineering Education A property table that is made much easier and accurate by the use of computer based property tables isdeveloped and presented in Table I. Table I Rankine Cycle Property TablePoint T(F) p(psia) h(Btu/lbm) v(ft^3/lbm) x (%) s(Btu/lbm R)1 900 800 1455.6 .964 superheat 1.64082I 100 .9504 913.9 285.5
Conference & Exposition Copyright © 2001 American Society for Engineering Education Session 2480AcknowledgementsThe above study was funded by The U.S. Department of Education under Title II, Part B –Dwight D. Eisenhower Professional Development Program to the District of Columbia. Theopinions expressed herein are those of the authors' and not necessarily those of the U.S.Department of Education or the District of Columbia.References1. Dede, C. (1999). The multiple-media difference. Technos, 8, 16 - 18.2. Bruner, J. (1963). The process of education. Cambridge. Harvard University Press.3. Papert, S. & Turkle, S
learned in class to novel situations. Through the use of an on-lineforum, the potential exists for students to achieve greater understanding and more meaningfulreflection. A study involving the role of individual learning styles in terms of students' use ofand students' benefit from the use of on-line discussion forums is needed. Further research onthe impact of on-line discussion forums to long-term understandings and perceptions as well as acomparison to more “traditional” methods of instruction is also warranted.References1. Edwards, V. B. (1997). Editor’s introduction in Education Week. Washington, DC: Editorial Projects in Education.2. Hein, T. L., and S. E. Irvine (1998). Assessment of student understanding using on-line
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Session 2248 Paper 902 Word Problems and Problems with Words: A Possible Solution Natalie D. Segal, Sallie S. Townsend S.I. Ward College of Technology at the University of HartfordAbstract: We began with a question: Why do our students have so much difficultysolving word problems in Math I? Another question followed: Why do our studentshave so much difficulty writing short (three-to-five paragraph), logical essays in EnglishI? One possible answer: Our students approach math and English problems as if theyrequired entirely different skills. However
Session 1330 On the Frequency and Causes of Academic Dishonesty Among Engineering Students Trevor S. Harding Kettering UniversityAbstractAccording to studies of self-reported academic dishonesty conducted over time, cheatingamong college students has been on the increase since at least the 1940’s. This isespecially true for engineering students who are now among the most likely to cheatcompared to other disciplines. This paper will present a synopsis of the literature onacademic dishonesty. In addition, the results of a pilot study on cheating
were notrequired in an effort to receive [honest, pertinent, relevant?] feedback. All students attendingclass were provided the survey and their names checked on a class roster for credit. The surveyincluded the following response items:1. I am a ____Freshman ____Sophomore ____Junior ____Senior2. What component(s) of this course interested you most?3. What component(s) of this course interested you least?4. List possible ways in which the course could be improved.5. List topics and/or labs you would like to have covered in class (that were not covered).Students were asked to check their status based upon completion of courses in the ABEcurriculum, not based upon credit thresholds.V. Survey ResultsThirty-one students (86%) completed the survey
. 5) were providedby the industry partner. Cost per SLA is determined by volume and surface area. In somecases rough tooling costs were provided. This gave the students real quantitative data toassist in redesign. A digital camera and scanner are used to create image files of thesketches, models, field trips and detail drawings. These images are then inserted into thePPt. Presentation. The presentation is to be used by the students at the end of thesemester in a seminar. This seminar is open to the entire campus while some engineeringand technology classes are required to attend. V = .8385 cu. In. S = 8.6398 sq. in
mathematical calculations in order to verify procedures of me-chanical, electric or structural resistance. It was a time without drawings or colors and mostlywithout man’s inter-activity with the computer, with restrict interest just for the engineeringprofessionals, but not for the students, even because the equipments high costs restricted verymuch their application at schools, unless in specific computing education courses. From decade beginning at 80’s, with the starting production of personal computers withmore appropriated technical characteristics, mostly those relative to the images generation, thecomputers were almost immediately applied from the pure numeric calculation to drawings gen-eration and, following, for the creation of the
York Times, p. A12. (20April 1998).2. Astin, A. W. What matters in college? San Francisco: Jossey-Bass Publishers. (1993).3. Attinasi, L. C., Jr. Mexican Americans’ perceptions of university attendance and the implications forfreshman year persistence. Journal of Higher Education, 60, (3) . 247-277. (1989).4. Bers, T. H., & Smith, K. E. Persistence of community college students: The influence of student intentand academic and social integration. Research in Higher Education, 32. (5). 539-556. (1991).5. Bogdan, R. C., & Biklen, S. K. Qualitative research for education. Boston: Allyn and Bacon. (1998).6. Braxton, J. M. , Sullivan, A. V. S. , & Johnson, R. M. Appraising Tinto’s theory of college studentdeparture. In Higher education
1968.KATHLEEN A. HALLKathleen Hall is a Professor of Mathematics at Southern Polytechnic State University. She received the B. S. degreein Mathematics from Loyola University, New Orleans in 1970 and the M. S. degree in Mathematics from ClemsonUniversity in 1972. She spent several years working in finite element analysis with the Lockheed AeronauticalSystems Company. Page 6.653.5 Proceedings of the 2001 American Society for Engineering Education Annual Conference & Exposition Copyright © 2001, American Society for Engineering Education
thermodynamically consistent and rate constants are given by k = AT n exp(− E RT )Heterogeneous Yang and Hougen form:Catalytic CrC s k C Aa C Bb − R S − rA = K 1 + ∑ K i Ciγ i This form includes Langmui-Hinshelwood, Eley-Rideal and Mars-van Krevelen etc.Simple Rate α β C Rϕ C Sγ rA = − k f C A C B − in which K eq is predicted from K eq
periods of months. The schedules are allowed to bedictated to a large extent by the academic demands placed on the student experimenters.Planning also anticipates the need to go back for further data acquisition after initial analysis ofthe data from the first set of tests in such facilities. These are all luxuries seldom affordablewithin the schedule and cost constraints of major facilities.In the 1980s and early 1990s, the Experimental Aerodynamics Group at Georgia Institute ofTechnology (GIT)’s School of Aerospace Engineering developed measurement systems to dealwith the complex, unsteady flow environment of rotary wing vehicles1. These diagnostictechniques were initially developed using high-power lasers, which are extremely fragile,expensive
" "ID ",1 "Type ","Waveform" "Date ",11/28/00 "Time ",2:21:30 PM "X Scale ",2.000000E-04 "X At 0% ",-4.000000E-04 "X Resolution ",2.500000E+01 "X Size ",512 "X Unit ","s" "X Label ","200 us/Div" "Y Scale ",5.000000E-01 "Y At 50% ",4.000000E-02 "Y Resolution ",2.500000E+01
; ExpositionCopyright © 2001, American Society for Engineering Education Figure 10. Futon FrameReferences:1. URL: http://www.krev.com/; MSC.Working Knowledge, a division of MSC Software.2. Felder and Silverman “How Students Learn: Adapting Teaching Styles to Learning Styles,”Proceedings of ASEE/IEEE Frontiers in Education Conference, Santa Barbara, CA., p. 489,1988.3. Wang, S-L., Mechanism Simulation in a Multimedia Environment, as a supplement to Designof Machinery, 2nd ed., New Media Version, by Norton, R., McGraw-Hill, 2001.4.Beer F. and Johnston E. R., Vector Mechanics for Engineers, Sixth Edition, New MediaVersion, McGraw-Hill, 1997.5. Erdman, A.G. Sandor, G.N., and Kota, S. Mechanism Design: Analysis and Synthesis
Behavior and Human Performance, October 1983, pp. 66-86.3. Byrne, J.A. Deliver – or else, Business Week, Marc 27, 1996, p. 36.4. McClelland, D.C. The Achieving Society. New York: Van Norstrand Reinhold, 1961.5. Shellenbarger, S. Data gap, Wall Street Journal, June 21, 1993, p. 6.6. Caudron, S. The top 20 ways to motivate employees, Industry Week, April 3, 1995, p. 14.CYNTHIA L. TOMOVICDr. Cynthia L. Tomovic is a professor and acting department head in the Department of Organizational Leadershipand Supervision, Purdue University. In addition to her administrative duties, she teaches courses in organizationalbehavior and human resource management. She has published extensively on issues pertaining to qualityimprovement and assessment in higher
Session 3630 Cooperative Learning in a Course on Teaching Engineering Phillip C. Wankat, Frank S. Oreovicz Purdue UniversityAbstractGraduate classes can be improved by reducing lecture and increasing active learningapproaches. Group work, in particular, in class and on projects should be encouraged. Itis especially important that professors and other presenters use a number of cooperativegroup exercises and other active learning approaches in courses and workshops on“Improving the Teaching of Engineering.” New professors are much more likely to usecooperative group and other active learning
and environmental safety in the design ofchemical processes. This concern also served as a driving force for thedevelopment of this course.This course is divided into five parts: the problem(s), accidents, health risk,hazard risk, and hazard risk analysis. Part I, an introduction to HS&AM, presentslegal considerations, emergency planning, and emergency response. This Partbasically serves as an overview to the more technical topics covered in theremainder of the course. Part II treats the broad subject of accidents—discussingfires, explosions and other accidents. Parts III and IV provide introductorymaterial to health and hazard risk assessment, respectively. Part V examineshazard risk analysis in significant detail. This final Part
, and comparison of differentinstitutions and student populations.Bibliography1. Baartmans, B. G. & Sorby, S. A. (1996). Introduction to 3-D Spatial Visualization. Prentice Hall2. Battista, M. T. (1980). Interrelationships between Problem Solving Ability, Right Hemisphere Processing Facility, and Mathematics Learning. Focus on Learning Problems in Mathematics, 2, 53–60 Page 6.394.6 Proceedings of the 2001 American Society for Engineering Education Annual Conference & Exposition Copyright 2001, American Society for Engineering Education 3. Battista, M. T., Wheatley, G. H., & Talsma, G. (1982). The
6.405.4combination of factor levels. The sample mean is calculated from the response values: _ n Y = Σ Yi /n (1) i=1where Yi is the sample value and n is the number of replications. The standard deviation iscalculated using the relation: n _ S= Σ(Yi - Y)2/(n-1) (2) i=1According to statistical theory, the sample means are approximately normally distributed, but thesample standard deviations are not. To solve this problem, often sample standard deviations aretransformed by taking their logarithms. The logarithms of the standard
and educational experiences in science, engineeringscience, engineering analysis and engineering design. Prior to the Grinter report engineeringeducation in the United States emphasized design with an insufficient mixture of science,engineering science, and engineering analysis.3 Engineering programs significantlyincreased the content of science and analysis courses over the last 50 years to provide astronger analytical base for engineering practice.Literature in the 1980's and 1990's includes articles recommending increased exposure forundergraduate engineering students in the area of design and creativity.4 Peterson arguedthat engineering sciences and engineering analysis had been segregated from engineeringdesign to the extent that