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A Preliminary Method of Delivering Engineering Design Heuristics
Technical Paper
2020-01-0741
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
This paper argues the importance of engineering heuristics and introduces an educational data-driven tool to help novice engineers develop their engineering heuristics more effectively. The main objective in engineering practice is to identify opportunities for improvement and apply methods to effect change. Engineers do so by applying ‘how to’ knowledge to make decisions and take actions. This ‘how to’ knowledge is encoded in engineering heuristics.
In this paper, we describe a tool that aims to provide heuristic knowledge to users by giving them insight into heuristics applied by experts in similar situations. A repository of automotive data is transformed into a tool with powerful search and data visualization functionalities. The tool can be used to educate novice automotive engineers alongside the current resource intensive practices of teaching engineering heuristics through social methods such as an apprenticeship. The tool can do so by providing novices with powerful search and data visualization capabilities which will allow them to understand tradeoffs between vehicle attributes, to make assumptions from initial information, and to benchmark the vehicle design.
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Citation
Hussain, M. and Paredis, C., "A Preliminary Method of Delivering Engineering Design Heuristics," SAE Technical Paper 2020-01-0741, 2020, https://doi.org/10.4271/2020-01-0741.Also In
References
- Daly , S. , Yilmaz , S. , Seifert , C. , and Gonzalez , R. AC 2010-1032: Cognitive Heuristics Use in Engineering Design Ideation Journal of Engineering Education 2010
- Yilmaz , S. , Seifert , C. , and Gonzalez , R. Cognitive Heuristics in Design: Instructional Strategies to Increase Creativity in Idea Generation Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24 3 335 355 2010 10.1017/S0890060410000235
- Fu , K.K. , Yang , M.C. , and Wood , K.L. Design Principles: Literature Review, Analysis, and Future Directions Journal of Mechanical Design 138 10 101 103 2016 10.1115/1.4034105
- Lee , B.D. and Paredis , C.J.J. A Conceptual Framework for Value-Driven Design and Systems Engineering Procedia CIRP 21 10 17 2014 10.1016/j.procir.2014.06.147
- Daly , S.R. , Yilmaz , S. , Christian , J.L. , Seifert , C.M. et al. Design Heuristics in Engineering Concept Generation Journal of Engineering Education 101 4 601 629 2012 10.1002/j.2168-9830.2012.tb01121.x
- Lee , B. , Fillingim , K.B. , Binder , W.R. , Fu , K. et al. Design Heuristics: A Conceptual Framework and Preliminary Method for Extraction 2017
- Cross , N. Expertise in Design: An Overview Design Studies 25 5 427 441 2004 10.1016/j.destud.2004.06.002
- Dixon , R.A. Selected Core Thinking Skills and Cognitive Strategy of an Expert and Novice Engineer Journal of STEM Teacher Education 48 1 36 67 2011 10.30707/JSTE48.1Dixon
- Malak , R.J. Jr. , Aughenbaugh , J.M. , and Paredis , C.J.J. Multi-Attribute Utility Analysis in Set-Based Conceptual Design Computer-Aided Design 41 3 214 227 2009 10.1016/j.cad.2008.06.004
- Atman , C.J. , Adams , R.S. , Cardella , M.E. , Turns , J. et al. Engineering Design Processes: A Comparison of Students and Expert Practitioners Journal of Engineering Education 96 4 359 379 2007 10.1002/j.2168-9830.2007.tb00945.x
- Ahmed , S. , Wallace , K.M. , and Blessing , L.T. Understanding the Differences between how Novice and Experienced Designers Approach Design Tasks Research in Engineering Design 14 1 1 11 2003 10.1007/s00163-002-0023-z
- Gerd , G. and Engel , C. Heuristics and the Law Cambridge, MA MIT Press in cooperation with Dahlem University Press 2006
- Todd , P.M. and Gigerenzer , G. Mechanisms of Ecological Rationality: Heuristics and Environments that Make Oxford Handbook of Evolutionary Psychology 2007
- Curran , R. , Verhagen , W.J.C. , van Tooren , Michel , J.L. et al. A Multidisciplinary Implementation Methodology for Knowledge-Based Engineering: KNOMAD Expert Systems with Applications 37 11 7336 7350 2010 10.1016/j.eswa.2010.04.027
- Yilmaz , S. and Seifert , C.M. Creativity through Design Heuristics: A Case Study of Expert Product Design Design Studies 32 4 384 415 2011 10.1016/j.destud.2011.01.003
- Tversky , A. and Kahneman , D. Judgment under Uncertainty: Heuristics and Biases Science 185 4157 1124 1131 1974
- Design Heuristics: Analysis and Synthesis from jet Propulsion Laboratory’s Architecture Team ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference 2018
- Chi , M.T.H. Two Approaches to the Study of Experts’ Characteristics Ericsson , K.A. , Charness , N. , Feltovich , P.J. , and Hoffman , R.R. The Cambridge Handbook of Expertise and Expert Performance Cambridge University Press 2006 21 30
- Björklund , T.A. Initial Mental Representations of Design Problems: Differences between Experts and Novices Design Studies 34 2 135 160 2013 10.1016/j.destud.2012.08.005
- LaFrance , M. The Quality of Expertise: Implications of Expert-Novice Differences for Knowledge Acquisition ACM SIGART Bulletin 6 14 1989 10.1145/63266.63267
- Heyworth , R.M. Procedural and Conceptual Knowledge of Expert and Novice Students for the Solving of a Basic Problem in Chemistry International Journal of Science Education 21 2 195 211 1999 10.1080/095006999290787
- Dym , C.L. Design, Systems, and Engineering Education International Journal of Engineering Education 20 3 305 312 2004
- Dym , C.L. , Agogino , A.M. , Eris , O. , Frey , D.D. et al. Engineering Design Thinking, Teaching, and Learning Journal of Engineering Education 94 1 103 120 2005 10.1002/j.2168-9830.2005.tb00832.x
- Felder , R.M. , Woods , D.R. , Stice , J.E. , and Rugarcia , A. The Future of Engineering Education II. Teaching Methods that Work Chemical Engineering Education 34 1 26 39 2000
- US Government - Office of Energy Efficiency & Renewable Energy Fuel Economy Data - Datasets for all Model Years https://www.fueleconomy.gov/feg/download.shtml September 2019
- US Government - Office of Energy Efficiency & Renewable Energy FuelEconomy.gov https://www.fueleconomy.gov/feg/ws/index.shtml#vehicle September 2019
- TrueCar Auto Buying Service TrueCar - New Cars https://www.truecar.com/
- Publicly Available Sources AutoData.net - Wiki Automotive Catalog https://www.auto-data.net/en/
- https://openrefine.org/
- Groves , A. Beyond Excel: How to Start Cleaning Data with OpenRefine Multimedia Information and Technology 42 2 18 22 2016
- Delbridge , R. , Lowe , J. , and Oliver , N. The Process of Benchmarking: A Study from the Automotive Industry International Journal of Operations & Production Management 15 4 50 62 1995 10.1108/01443579510083604
- Hardman , S. , Steinberger-Wilckens , R. , and Horst , D.V.D. Disruptive Innovations: The Case for Hydrogen Fuel Cells and Battery Electric Vehicles International Journal of Hydrogen Energy 38 35 15438 15451 2013 10.1016/j.ijhydene.2013.09.088
- Gao , P. , Kaas , H. , Mohr , D. , and Wee , D. Disruptive Trends that Will Transform the Auto Industry McKinsey & Company 1 1 11 2016
- Linoff , G.S. Data Analysis Using SQL and Excel Indianapolis, IN John Wiley & Sons 2015
- https://protege.stanford.edu/