ESD.71 | Fall 2008 | Graduate

Engineering Systems Analysis for Design


The primary text for the class consists of draft chapters from the new text that Prof. de Neufville is preparing in collaboration with Prof. Stephan Scholtes, his collaborator at the University of Cambridge.

This material is supplemented by chapters from:

de Neufville, Richard. Applied Systems Analysis. New York, NY: McGraw-Hill, 1990. ISBN: 9780070163720.

Textbook chapters from Applied Systems Analysis can also be found here.

Readings by Session

The following table shows the schedule of readings from Applied Systems Analysis.

Introduction to course
L1 Motivation: paradigm shift from best outcome to moving distribution of outcomes to right  
Part 1: basics, recognition of uncertainty, valuation fundamentals, and timing issues
Conventional valuation and recognition of uncertainty

Discounted cash flow and present value

Criteria for valuation

Chapters 10, 11, 13
L3 Uncertainty recognition  

Choice of discount rate

Opportunity cost, weighted average cost of capital, capital asset pricing model

Chapter 12
Timing of development
Basic issue: build now or later?

Asphalt vs. concrete highways

Basic system model: production function, economies of scale

Chapter 2
L6 Optimum expansion size deterministic case  

Determining economies of scale from cost function

Constrained optimization and marginal analysis


Sources of flexibility

“On” systems-timing

“In” systems-timing and function

Case examples

Part 2: uncertainty modeling and flexibility valuation methods
Decision analysis
L9 Uncertainty assessment Chapter 15

Primitive models

Introduction to decision analysis

Chapter 16

Practical issues

Solutions by “folding back”

Flaw of averages


Distribution of outcomes for decision analysis

Value at risk and gain, multiple value metrics

L13 Benefits of waiting: value of information Chapter 17
L14 Decision analysis examples: oil platform, wind energy, silicon wafer plant, Tokyo/Haneda runway  
L15 Mid-semester review  
L16 Midterm exam  
Lattice analysis

Lattice model to represent uncertainty

Regression to determine trend and variability (μ and σ)

L18 Dynamic programming: systematic solution by “folding back” Chapter 7

Valuation of lattice by dynamic programming

Satellite case study


Combining lattice and decision analysis

Case studies: aqua line tunnel

L21 Conceptual valuation and application  
L22 Comparing decision analysis and lattice analysis  

Definition and analysis of “hotspots” using change propagation analysis

Path dependency

Comments on draft application portfolio

Case studies: car platforms, hydroelectric dam, mini unmanned aerial vehicle

L24 Perspective on flexibility in design and real options analysis (Part 1)  
L25 Perspective on flexibility in design and real options analysis (Part 2)  
L26 Review for final exam