Mlesd Learning Objectives(1) 16888 MSDO Pedagogy (7)understand the concept of design for value and be familiar with ways to quantitatively assess the expected e.g. A1-Design of e.g. "Genetic Algorithms e.g. Dr Fenyes Experiments(DOE) lifecycle cost of a new system or product ecturesGM ( 8)sharpen their presentation skills, acquire critical Class reasoning with respect to the validity and fidelity of their A1-A5 Project Sessions MSDO models and experience the advantages and challenges of teamwork Reading e.g. "ISIGHT Have you achieved these learning objectives? e.g." STSTank MSDO e.g."Principles of Optimal Design Massachusetts Institute of Technology-Prof de Weck and Prof Wacox Massachusetts institute of Technology. Prof. de Weck and Prof. Willcox Mlesd Changes from 2002->2004 50 Mlesd Exploration and Optimization MSDO Framework Design Vector Simulation model Objective Vector Enrollment25÷40÷30(nc. listeners) Discipline A Discipline B Moved from Design Studio Eliminated Literature Review Sessions Discipline c iSIGHT- academic version to students Reduced guest speaker involvement Coupling Multiobjective Provided more canned projects Required final report in conference paper format Optimization Algorithms Methods Principles of Optimal Design"-Papalambros textbook Numerical Techniques Sensitivity direct and penalty method Analysis Heuristic Technique Coupling (SA, GA) performance Massachusetts Institute of Technology -. de Weck and Prof Wilcox Massachusetts Institute of Techmology.Prof de Weck and Prof willcox5 Massachusetts Institute of Technology - Prof. de Weck and Prof. Willcox Learning Objectives (III) Learning Objectives (III) (7) understand the concept of design for value and be familiar with ways to quantitatively assess the expected lifecycle cost of a new system or product (8) sharpen their presentation skills, acquire critical reasoning with respect to the validity and fidelity of their MSDO models and experience the advantages and challenges of teamwork Have you achieved these learning objectives ? 6 Massachusetts Institute of Technology - Prof. de Weck and Prof. Willcox MSDO Pedagogy MSDO Pedagogy Guest Lectures Readings Lab Sessions Class Project Assignments A1-A5 e.g. “Dr. Fenyes - GM” e.g. “iSIGHT Introduction” e.g. “Genetic Algorithms” e.g. “STSTank” e.g. A1 - Design of Experiments (DOE) Lectures e.g. “Principles of Optimal Design” MSDO 7 Massachusetts Institute of Technology - Prof. de Weck and Prof. Willcox Changes from 2002 Changes from 2002 -> 2004 • Enrollment 25 Æ 40 Æ 30 (incl. listeners) • Moved from Design Studio • Eliminated Literature Review Sessions • iSIGHT - academic version to students • Reduced guest speaker involvement • Provided more canned projects • Required final report in conference paper format • “Principles of Optimal Design” - Papalambros textbook 8 Massachusetts Institute of Technology - Prof. de Weck and Prof. Willcox Exploration and Optimization Exploration and Optimization MSDO Framework MSDO Framework Discipline A Discipline B Discipline C n I p u t O u t p u t Simulation Model Tradespace Exploration (DOE) Optimization Algorithms Multiobjective Optimization Numerical Techniques (direct and penalty methods) Heuristic Techniques (SA,GA) 1 2 n x x x ª º « » « » « » « » « » ¬ ¼ # Design Vector Coupling 1 2 z J J J ª º « » « » « » « » « » ¬ ¼ # Approximation Methods Coupling Sensitivity Analysis Isoperformance Objective Vector