SGER A Framework for Adapting Decision-Based Scientific Principles in Engineering Design

Proposal to The National Science Foundation Directorate for Engineering Division of Design, Manufacture and Industrial Engineering Engineering Design Program by Sven K Esche Constantin Chassapis Assistant Professor Associate Professor Department of Mechanical Engineering Stevens Institute of Technology SGER: A Framework for Adapting DecisionBased Scientific Principles in Engineering Design June 25, 2002 Requested Program Start: September 1, 2002 Requested Program End: August 31, 2004 Requested Amount: $100,000 Approved by: _ Professor Bernard Gallois Dean, School of Engineering Stevens Institute of Technology Department of Mechanical Engineering Stevens Institute of Technology Castle Point on Hudson Hoboken, NJ 07030 Tel.: (201) 216-5559 Fax: (201) 216-8315 E-Mail: sesche@stevens-tech.edu Introduction While   modern   engineering   curricula   should reflect   the   emerging   view   that   engineering design   involves   decision   making   under conditions   of   uncertainty   and   risk,   student exposure   to   these   concepts   is   virtually   non existent   in   current   educational   programs   A pilot project is proposed, which will establish an   information­based   approach   as   the emerging   paradigm   in   engineering   design education by demonstrating in two mechanical engineering   courses   that   concepts   of   data uncertainty,   decision   theory   and   optimization can   be   integrated   effectively   into undergraduate engineering curricula Vision Engineering   design   represents   a   process   of decision   making   under   conditions   of   uncertainty and   risk,   but   today’s   undergraduate   engineering curricula rarely include any principles of decision theory.1  Even   though   value   or   utility   theory   are crucial   components   of   the   decision   making process,   these   subjects   are   typically   heavily underrepresented   in   engineering   curricula   and often   treated   incorrectly   by   the   engineering community   at   large   Probability   theory,   which establishes the basic mathematical tools needed for the proper assessment of uncertainty and risk, is often not put into learning­enhancing context such as   engineering   design   This   unsatisfactory situation calls for a revolutionary shift in design education where practical examples of real design cases are used to illustrate the application of sound scientific principles This program will prompt a strategic initiative for the development, implementation and assessment of   novel   approaches   in   engineering   design education   at   Stevens   Institute   of   Technology (SIT). Starting with a thorough feasibility study in two courses taken in the junior year by mechanical engineers,   it   will   be   demonstrated   that   the concepts   of   uncertainty   in   data,   decision   theory and optimization can be integrated effectively into undergraduate engineering design education. Upon successful   completion   of   this   pilot   project,   this approach   will   be   implemented   immediately   into the   capstone   design   sequence   in   the   mechanical engineering   department   Later,   it   will   be propagated to the entire engineering curriculum at SIT   through   a   major   revision   of   the   entire curriculum Current State SIT is a private technological university dedicated to study and research. Founded in 1870, SIT offers baccalaureates,   master's   and   doctoral   degrees   in engineering,   science   and   management   It   has earned   an   excellent   reputation   for   its   pioneering broad­based engineering curriculum 2 Based on its history,   SIT   provides   a   fertile   ground  for   future curricular innovations. SIT has often been an early adopter of emerging pedagogical approaches and educational   technologies   (e.g.,   student­owned PC/laptop,   fully   networked   campus, WebCampus.Stevens distance learning program 3), and   major   funding   was   committed   to   the development   of   state­of­the­art   design laboratories   Recently,   SIT   implemented   a   new undergraduate   engineering   curriculum   This curriculum   is   designed   to   reflect   the   nationwide trend towards enhancement of traditional lecture­ based courses with a significant design thread that propagates   through   the   entire   undergraduate educational   program.4  Each   design   laboratory   is integrated   with   one   of   the   major   engineering courses as outlined in Table 1 Currently, ME 322: Engineering Design VI, is the first   discipline­specific   design   course   in   the mechanical engineering curriculum. It embraces a holistic   view   of   design  that   encompasses   design activities spanning the entire product development cycle   The   topics   covered   include   product conception,   identification   of   customer   needs, product   specifications,   concept   generation, concept   selection,   concept   testing,   product architecture,   industrial   design,   design   for manufacturing   and   product   development economics   The   associated   course,   ME   345: Modeling   and   Simulation,   introduces   modeling and simulation methodologies and tools including model­block building, logical and data modeling, validation with applications in simulating product performance,   assembly,   process   and manufacturing modeling and entity flow modeling including   conveyors,   transporters   and   guided vehicles Table 1: Integrated design spine Term Design Course E 121 Design I: design concepts, product dissection, professional practice E 122 Design II: design of structures, design for environment, aesthetics E 231 Design III: design of energy conversion systems and chemical reactors 232 Design IV: design of filters, amplifiers and embedded controllers E 321 Design V: openended design projects on processing of materials to produce products ME 322 Design VI: discipline-specific integrated product & process design 7/8 ME 423/424 Design VII/VIII: disciplinespecific capstone design project Accompanying Course E 120 Engineering Graphics: projections, dimensioning, tolerances E 126 Mechanics of Solids: particle statics, force analysis, stress, strain E 234 Thermodynamics & Energy Conversion: heat & work, 1st & 2nd law, processes & cycles E 246 Electronics & Instrumentation: signal acquisition & processing, sensors, micro-controllers E 344 Materials Processing: engineering properties of materials, scientific understanding of properties and methods of controlling them ME 345 Modeling and Simulation: methodologies and tools, applications ME 421 Engineering Economics: economic analysis, project management, marketing of products Plan of Action Over   a   span   of   two   years,   the   two   mechanical engineering   courses   taught   concurrently   in   the junior year will be completely redesigned to serve as a test bed for the development, implementation and   assessment   of   this   novel   approach   to engineering design education. A variety of design examples   will   be   developed   that   can   be   used effectively   to   introduce   concepts   of   decision making in the presence of uncertainty and risk as well as probability theory and optimization in the context of real design scenarios This  project  will  involve  the  tight  integration of the two course syllabi. ME 322 will introduce the theoretical   concepts   in   the   framework   of   a comprehensive group design project, and ME 345 will focus on the use of pertinent software tools MS   Excel   will   be   used   for   data,   regression   and economic   analyses   as   well   as   optimization Various   MATLAB®  programs   will   be implemented, which will be used by the students for the statistical analysis of data, the probabilistic modeling using the Monte Carlo method and the consideration of broad ranges of system options by optimization techniques Objectives and Outcomes Using two mechanical engineering courses as test   bed,   this   project   will   demonstrate   that methods   for   handling   uncertainty   in   data, decision   making   based   on   value   theory   and optimization   techniques   can   be   integrated effectively   into   undergraduate   engineering curricula. The educational materials developed and   the   experiences   gained   herein   will   form the   basis   for   more   comprehensive   curricular changes   and   cross­fertilization   of   related research programs at SIT Strategic Objectives Successful completion of this program will prompt a   strategic   initiative   that   aims   at   generating   a heightened awareness of the probabilistic nature of engineering   design   attributes   and   establishing science­based   engineering   design   practices   in undergraduate   education   Through   the development,   implementation   and   assessment   of educational   modules   utilizing   rigorous   science­ based techniques, this initiative will promote the application   of   sound   scientific   principles   in   the engineering design process. It will thus form the basis   for   a   fundamental   paradigm   change   in undergraduate   engineering   design   education   and encourage   similar   curriculum   developments   at institutions nationwide Project Objectives Significance This project is to be understood as a catalyst for more comprehensive curricular changes at SIT and later   dissemination   to   other   institutions   It   will initially   be   of   limited   scope   Examples   and methods for handling uncertainty in data, decision making   based   on   rigorous   value   theory   and optimization techniques will be implemented into two  undergraduate  courses  These  topics   will  be placed into the context of the engineering design process   that   has   traditionally   been   more experience­based and problem­solving oriented. A successful   implementation   of   this   focused approach   will   demonstrate   that   the   above mentioned concepts can be effectively presented to and   successfully   applied   by   undergraduate engineering students The   activities   proposed   herein   take   into consideration   the   special   character   of   the educational   philosophy   at   SIT,   which   clearly reflects a strong awareness for the importance of design   skills   for   engineering   practitioners   In particular,   this   project   will   form   the   framework and   foundation   for   a   wide   range   of   future improvements of the engineering education at SIT by   providing   practice­relevant   context   to   fairly theoretical   concepts   In   addition,   the   project objectives hold strong potential for synergies with the PI’s ongoing and planned research activities on modeling systems with uncertainty.5,6,7,8,9,10 Project Outcomes Upon  completion  of   the  project,  two  junior­year courses in mechanical engineering will have been carefully redesigned and appropriate instructional materials and tools will have been developed. The proposed   changes   include   the   reduction   or replacement of some of the currently taught topics and the close integration of the syllabi These two courses will provide the justification for comprehensive curricular revisions throughout the mechanical   engineering   program   and   across   all engineering disciplines at SIT. Additional external funding   for   these   initiatives   will   be   solicited   ­ possibly   from   NSF   ­   based   on   the   experiences gained   in   the   process   of   course   development, implementation and piloting Significance and Justification The activities proposed herein are well aligned with   the   educational   philosophy   at   SIT   and hold   strong   potential   for   synergies   with ongoing and planned research activities. While the   testing   of   the   underlying   educational hypothesis represents a high­risk proposition, successful   project   completion   offers   strong potential   for   catalyzing   rapid   and   innovative advances in design education Justification Engineering   design   practice   based   on   decision making strategies that resort to utility theory and take into account the probabilistic nature of design attributes   represents   an   emerging   paradigm Corresponding   pedagogical   approaches   suitable for teaching these scientific concepts effectively in the   undergraduate   engineering   curriculum   have not been developed and assessed yet. While this lack   of   precedence   renders   the   proposed exploratory project  a high­risk proposition, upon its successful completion it offers strong potential for   catalyzing   rapid   and   innovative   advances   in engineering   design   education   with   significant impact on engineering design practice thereafter Plan of Work Project Phases Phase I of this two­year project will be devoted to   the   detailed   project   planning   and development   of   the   educational   materials   In Phase II, the two courses will be piloted and the project outcomes assessed. In Phase III, the follow­on   project   for   the   propagation   of   the approach   to   the   entire   SIT   engineering curriculum will be planned and corresponding funding solicited This two­year project will be carried out in three phases (see Table 2 for an estimated timeline) Phase I: Project Planning and Materials Development In   Phase   I,   the   detailed   planning   of   this exploratory   project   will   be   conducted   Detailed course syllabi for the two courses will be created and a complete listing of the educational materials to  be  developed  in support  of  the pilot  program will   be   compiled   Furthermore,   these   materials will   be   reviewed   and   improved   on   the   basis   of discussions   and   visitations   with   other   experts   in the field such as   Professor   Saari 11  and  Professor Howard12, two world­renowned specialists  in the field of decision theory Table 2: duration Project schedule for two­year project  Tasks Au Sp Su Au Sp Su 02 03 03 03 04 04 I-1 Detailed Project Planning I-2 Educational Materials Development I-3 Reporting/Dissemination II-1 Pilot Courses II-2 Assessment of Project Outcomes II-3 Reporting/Dissemination III Planning/Proposal for Follow-on Project The   educational   materials   to   be   developed   will include:  lecture   notes   for   the   two   courses,   which synthesize the current state of the art in decision and utility theory at a level that is appropriate for   undergraduate   education   and   relate   to specific design/product development activities,  realistic examples that will place the theoretical concepts into practical context,  small   student   projects   that   will   allow   for exploration­based learning modes in ME 345,  a comprehensive design project for ME 322,  homework problems and pertaining solutions,  MATLAB® scripts (basic statistical analysis and graphical   representation   of   data,   Monte   Carlo algorithms   for   probabilistic   modeling   of engineering systems, modeling of decision event trees   and   modeling   of   a   comprehensive   case study, optimization)  MS   Excel   scripts   (data   analysis,   regression analysis, financial analysis, optimization) Phase I will be concluded by writing the progress report   to   the   program   manager   and   preparing initial   presentations   on  this   project   at   the   ASEE Conference   and   Exposition   and   at   the   ASME Design Conference Phase II: Pilot Courses and Outcomes Assessment In   Phase   II,   the   two   courses   will   be   taught concurrently   The   course   outcomes   will   be assessed   according   the   following   metrics:   (i) student satisfaction as measured by questionnaires and   attitudinal   surveys   and   (ii)   student performance   as   measured   by   grades   in   the   pilot courses   as   well   as   in   the   capstone   design   The student   feedback   will   be   collected   using   online forms implemented with D*cide ™, an assessment software application developed at Stevens.13 Phase II will be concluded by disseminating the project results through presentations at the ASEE and ASME Design Conference, as well as through preparation   of   peer­reviewed   publications   in   the ASEE   Journal   of   Engineering   Education14  and ASME Journal of Mechanical Design.15 Phase III: Planning of Follow-on Project In Phase III, the possibility for the propagation of this   novel   approach   to   design   engineering education into the entire curriculum at SIT will be analyzed   Potential   collaborators   from   other engineering   departments   will   be   sought   to carefully   plan   more   comprehensive   curricular implementations   at   SIT   At   the   same   time, prospective   external   funding   sources   for   the corresponding   developments   such   as   the Educational Materials Development (EMD) track of the NSF­CCLI program16 will be reviewed and targeted with proposals Implementation Two existing  mechanical  engineering courses will   be  redesigned  with  a   focus   on   decision­ based design engineering. They will include a comprehensive   design   project   covering   the main phases of product development as well as a   laboratory   component   on   related   software tools   Collaborative   learning   through   self­ discovery will be the preferred learning mode ME   322:   Engineering   Design   VI   and   ME   345: Modeling and Simulation were selected as a test bed   for   the   novel   approach   to   design   education proposed, in which the traditional teaching mode based on problem­solving is replaced by a focus on   decision   making  taught   through   collaborative student   self­discovery   These   mechanical engineering courses are taken concurrently in the junior year for 2 and 3 credits, respectively. Both classes include a lecture component, but while ME 322 features a comprehensive semester­long group design   project   covering   the   main   phases   of   the engineering   design   process   from   product conception to economic analysis, ME 345 features an accompanying laboratory session with a series of smaller projects assigned to student teams with   to     group   members   Engineering   reports   and group presentations will complement the exams as assessment methods for student performance Compared   with   the   current   course implementations, coverage of the following topics will   be   reduced   significantly   or   discontinued completely: product architecture, industrial design, assembly and production modeling and entity flow modeling   These   educational   modules   will   be replaced by the topics listed in columns 2 and 3 of Table 3,   which   are   integrated   with   the   design activities   listed   in   column     The   primary textbooks17,18  selected for the two courses will be supplemented   by   material   from   the   sources referenced in the table Key Personnel and Success Measures This project will be carried out by Dr. Esche and   Dr   Chassapis   with   the   support   of   one graduate student. Its success will be measured based   on   pedagogical   metrics   as   well   as funding, publications and peer recognition Key Personnel Dr. Esche, Assistant Professor, will be the PI of the project who will be in charge of the plan of work   described   above   Dr   Chassapis,   Associate Professor and Department Director, will act as Co­ PI   and   work   in   an   advisory   function   He   is   the Director   of   the   Integrated   Product   Development Program19  and Associated Director of the Design and Manufacturing Institute.20  In addition to their experience   in   teaching   various   design   courses, Drs   Esche   and   Chassapis   also   have   a   strong record   in   collaborating   on   the   development, implementation   and   administration   of   new courses,   educational   programs   and   student laboratories   at   SIT   They   are   members   of   the undergraduate   curriculum   committee   of   the mechanical engineering department and have been instrumental in a variety of strategic initiatives to adapt   innovative   pedagogical   approaches   and techniques   such   as   project­based   learning, 21,22,23 assessment   methodologies,24,25  remote laboratories26,27,28,29,30 and their implementation into the mechanical engineering curriculum at SIT Table 3: Topics and tools to be integrated into ME  322 and ME 345 Design Subject Product conception ME 322 Topic ME 345 Topic Decision making, design options31,32,33,34 Statistics Sets, probability, review distributions, Bayes’ formula37,38 Identification Forecasting41 of customer needs Model building, logical and data modeling35,36 Data analysis with MATLAB39 and MS Excel40 Regression analysis with MATLAB42 and MS Excel43 Product Rationality, utility Monte Carlo specs, functions,44 Arrow’s simulation of concept theorem,45,46,47 probabilistic generation & decision making in models with selection presence of risk, MATLAB,51 48,49 Borda Count, von optimization with NeumannMS Excel, Morgenstern utility50 MATLAB52 Concept Decision Monte Carlo testing53 analysis54,55,56,57 simulation of decision event trees with MATLAB58 Product Discounting, present Monte Carlo development value, interest, simulation of economics inflation/deflation59 case study with MATLAB,60 financial analysis with MS Excel61 Measures of Success The   success   of   this   exploratory   project   will   be measured according to the following metrics: (i) student   performance   and   student   satisfaction during the pilot project and in the capstone design sequence   following   directly   thereafter,   (ii)   early indications   that   other   faculty   will   adopt   the proposed   pedagogical   approach   and   the   related educational materials in their courses (iii) number of   conference   presentations   and   publications   in conference   proceedings   and   peer­reviewed journals,   and   (iv)   follow­on   funding   by   external sponsors   (e.g.,   non­profit   foundations,   corporate sources,   governmental   agencies)   for   additional educational   developments   or   cross­fertilized research activities SGER: A Framework for Adapting Decision-based Scientific Principles in Engineering Design Submitted to NSF on June 25, 2002 by S Esche & C Chassapis, Stevens Institute of Technology LIST OF REFERENCES Goals of the Engineering Design Program, URL: http://www.eng.nsf.gov/dmii/Message/EDS/ED/ed.htm Stevens Institute of Technology, URL: http://www.stevens-tech.edu/history/ WebCampus.Stevens, URL: http://attila.stevens-tech.edu/gradschool/distance_learning/ Sheppard K & Gallois, B (1999) The design spine: revision of the engineering curriculum to include a design experience each semester, Proceedings of the 1999 ASEE Annual Conference and Exposition, Charlotte, North Carolina, June 1999 Yu, Q & Esche, S K (2002) Modeling of grain growth kinetics with Read-Shockley grain boundary energy by a modified Monte Carlo algorithm Accepted for publication in Materials Letters Yu, Q & Esche, S K (2002) A new perspective on the normal grain growth exponent obtained in two-dimensional Monte Carlo simulations Submitted for publication in Modeling and Simulation in Materials Science and Engineering Yu, Q & Esche, S K (2002) A Monte Carlo algorithm for single phase normal grain growth with improved accuracy and efficiency Submitted for publication in Computational Materials Science Esche, S K., Chassapis, C & Manoochehri, S (2001) Concurrent product and process design in hot forging Concurrent Engineering: Research and Applications, Vol 9, No 1, pp 48-54 Esche, S K., Fidan, I., Chassapis, C & Manoochehri, S (2000) Knowledge-based part and process design for metal forging SAE Transactions - Journal of Materials and Manufacturing, Vol 108, No 5, pp 92-99 10 Esche, S K., Hadim, H & Chassapis, C (2002) Prototype for a wireless web-based building services monitoring and control system Proposal submitted to NSF-ESS program 11 Saari, D G., University of California at Irvine, Department of Mathematics, URL: http://www.math.uci.edu/faculty/dsaari.html, http://www.math.nwu.edu/~d_saari/ 12 Howard, R A., Stanford University, Department of Management Science and Engineering, URL: http://www.stanford.edu/dept/MSandE/faculty/rhoward/ 13 D*cide for Educational Assessment™ by Choice Logic Corporation, URL: http://www.choicelogic.com/ 14 ASEE Journal of Engineering Education, URL: http://www.asee.org/publications/jee/ 15 ASME Journal of Mechanical Design, URL: http://www-jmd.engr.ucdavis.edu/jmd/ 16 NSF Course, Curriculum, and Laboratory Improvement (CCLI) Program, URL: http://www.ehr.nsf.gov/due/programs/ccli/ 17 Ulrich, K T & Eppinger, S D (2000) 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Pochiraju, K & Chassapis, C (2001) Implementation of assessment procedures into the mechanical engineering curriculum Proceedings of the 2001 ASEE Annual Conference and Exposition, Albuquerque, New Mexico, USA, June 24 - 27, 2001 25 Esche, S K (2002) Assessment of an open laboratory approach using experimental stations with remote access Abstract submitted for presentation at the Second ABET National Conference on Outcomes Assessment for Program Improvement, Pittsburgh, Pennsylvania, USA, October 31 - November 1, 2002 26 Esche, S K (2002) On the integration of remote experimentation into undergraduate education Submitted for publication in ASEE Journal of Engineering Education 27 Esche, S K., Chassapis, C., Nazalewicz, J W & Hromin, D J (2002) A scalable system architecture for remote experimentation Accepted for presentation at the 32nd ASEE/IEEE Frontiers in Education Conference, Boston, Massachusetts, USA, November - 9, 2002 28 Esche, S K (2002) Remote experimentation - one building 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Systems engineering: a new framework for engineering design ASME DSC, Vol 60, pp 39-46 34 Hazelrigg, G A (1999) Framework for decision-based engineering design Journal of Mechanical Design, Vol... 50 Hazelrigg, G A (1996) Systems Engineering: An Approach to Information-based Design, Ch Prentice Hall, 1996 51 Hazelrigg, G A (1996) Systems Engineering: An Approach to Information-based Design, ... information­based   approach   as   the emerging   paradigm   in   engineering   design education by demonstrating? ?in? ?two mechanical engineering   courses   that   concepts   of   data uncertainty,