Value-Driven Design

1

How Value-Driven Design eliminates the cause of weight and cost growth

Value-Driven Design

2

Extensive Attributes

Composition Function

Performance, Weight, Cost, and -ilities

Value-Driven Design

3

Analysis

Evaluate

Definition

Design Variables(Length, Displacement)

Attributes (Weight, Eff., Cost)

Configuration

Value

Design Optimization

Value-Driven Design = Optimization

ImproveObjective Function Optimizer

Physical Models CAD System

Value-Driven Design

4

Optimization

Extensive Attributes

ThrustDragEfficiencyWeightManufacturing CostMaint. CostReliabilityMaintainabilityRadar Cross Section

Objective Function

Value

Value-Driven Design

5

Engine Inlet

Status Gradient Value

Efficiency 90% 150,000 135,000Weight 700 -130 -91,000

Manufacturing Cost 700 -1 -700

Maintenance Cost 500 -0.5 -250

Reliability 1500 2.3 3,450

Design Value $ 43,478

Maintainability 7.8 -340 -2,652

Support Equipment 12 -15 -180Radar Cross-Section 0.1 -1200 -120

InfraRed Signature 1.4 -50 -70

VDD Vision: Pervasive use of Optimizationin Engineering Design

Technical detail on distributed optimization can be found at http://www.dfmconsulting.com/opt.pdf

What?

Value-Driven Design

6

Staus Quo: Requirements Flowdown

Turbine Design

TurbineBlade

Design

Propulsion Control System

TemperatureSensor Design

FADECDesign

ServovalveDesign

Wing Design Cockpit Design

Avionics Systems

Radar Design Heads-UpDisplay Design

Landing Gear Systems

Aircraft Systems

Requirements Methodpromises Functionality

Propulsion Systems

If each module meets its requirements, the overall system will meet its requirements

Value-Driven Design

7

VDD Vision: Distributed Optimal Design

Turbine Design

TurbineBlade

Design

Propulsion Control System

TemperatureSensor Design

FADECDesign

ServovalveDesign

Wing Design Cockpit Design

Avionics Systems

Radar Design Heads-UpDisplay Design

Landing Gear Systems

Aircraft Systems

Propulsion Systems

If each component is optimized,

the overall system will be optimized

If you design the best components,

you will realize the best system

Value-Driven Design

8

Distributed Optimal Design

• Overview

• Design Attribute Spaces

• Composition Function

• Objective Function

• Linearization and Decomposition

Value-Driven Design

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Distributed Optimal Design Overview

Status Gradient Value

Efficiency 90% 150,000 135,000Weight 700 -130 -91,000

Manufacturing Cost 700 -1 -700

Maintenance Cost 500 -0.5 -250

Reliability 1500 2.3 3,450

Design Value $ 43,478

Maintainability 7.8 -340 -2,652

Support Equipment 12 -15 -180Radar Cross-Section 0.1 -1200 -120

InfraRed Signature 1.4 -50 -70

Component Attributes

System Attributes

System Value

Composition Function

Value Model Effect of Component Attribute on System Value

Value-Driven Design

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• Coordinate Axes are Design Attributes

• Different Space for – Whole Product: x1, x2, ... xm

– Each Component: yk1, yk2, ... ykn (describes component k)

• Super attribute space composed of all attributes of all components: = [y11, y12, ... y21, ... ypn]

• describes whole product; describes all components

Uni

t Pro

fit

Horsepower Relia

bilit

y

x

z

z

z

Intake ManifoldWeight 6.0Cost 12.0Life 20000.0

Intake ValveWeight 0.1Cost 2.0Efficiency 0.9

Cylinder HeadWeight 0.5Cost 42.0Efficiency 0.9Life 10000.0

Design Attribute Spaces

Value-Driven Design

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• For distributed optimization,– h is the composition function

• Extensive attributes in affect collectively– no other attributes matter for global optimization

• Example elements:

x h z

z

x

Weightchassis

Weighttransmission

Weightengine

. . .

+

+= Weighttractor

component systemmodel

1 1

MTBF MTBFtractor component

The Composition Function

Value-Driven Design

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Objective Function (Value Model)

The objective function is for the whole system x

We want local objective functions, vj for components j = 1 to n

such that when v y v y y j x x xj j * *

x x* An optimum point is where for all

xx*

That is, when the components are optimized, the product is optimized

Value-Driven Design

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Objective Function with Local Attributes

• Since value = and , then value , a function of local attributes

• This gives us global value in terms of local attributes, but does not give an independent objective function for each component

• For independence, we must linearize

• Thus each component has its own goal

x

x h z h z

h z

Value-Driven Design

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Validity of Linearization

Given smoothness of and h, the linear approximation is reasonable for small changes (< 10% of whole system value) near the preliminary design

Value-Driven Design

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• Start with a reference design (preliminary design) with attributes x* and z*

• Generate the Taylor expansion of around z* :

• O2 represents second order and higher terms that we can ignore in the vicinity of z*

• Without O2, the Taylor series is linear

Linearizing the Objective Function

h z

h z x J z z Ox h z

* *

* *2 h z

Value-Driven Design

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Solving the Taylor Expansion

• is the gradient of

• Jh is the Jacobian Matrix of h:

x x x x1 2 3 4

, , , ,

x

z

x

z

x

z

x

zx

z

x

z

x

z

x

zx

z

x

z

x

z

x

z

x

z

x

z

x

z

x

z

p

p

p

m m m m

p

1

1

1

2

1

3

1

2

1

2

2

2

3

2

3

1

3

2

3

3

3

1

1 2 3

Value-Driven Design

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Solving the Taylor Expansion

h z h zx

x

zz z

i

i

ji

m

j

p

j j

* *

11

Objective functions are used for ranking—they are not changed by the addition or subtraction of a constant. Thus, the expression above can be simplified by dropping all terms that use the constant z*:

h zx

x

zz

i

i

ji

m

jj

p

11

Linear objective functions have the property that can be maximized by maximizing each zj term or any group of zj terms independently

Value-Driven Design

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Component Optimization

For a group of zj’s that correspond to a single component, we can relable them y1 though yn and determine the component objective function (in the vicinity of the preliminary design):

component

i

i

k xi

m

k

n

kx

x

yy

*11

Value-Driven Design

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Value landscape in parameter space

Value landscape in property space

Analysis

SearchEvaluate

Definition

Objective Function Optimizer$Parameters (Length, Displ.)

Properties (Weight, Eff., Cost)

Configuration

Value

Physical Models Design Drawing

“But you can’t DO that!”

Value-Driven Design

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Component Design Value is Commensurate

with System Design Value

Partial Derivatives of the Objective Function

Implementing Distributed Optimal Design

Engine Inlet

Status Gradient Value

Efficiency 90% 150,000 135,000Weight 700 -130 -91,000

Manufacturing Cost 700 -1 -700

Maintenance Cost 500 -0.5 -250

Reliability 1500 2.3 3,450

Design Value $ 43,478

Maintainability 7.8 -340 -2,652

Support Equipment 12 -15 -180Radar Cross-Section 0.1 -1200 -120

InfraRed Signature 1.4 -50 -70

Value-Driven Design

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Other Benefits of VDD

• Optimization Finds a Better Design

• Requirements Cause Preference Conflicts

Value-Driven Design

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Optimization Finds a Better Design

Requirements

< $30 M unit mfg cost

< 30,000 lbs. w

eight

Cost

Weight(0,0)

Best

Cost

Weight(0,0)

Increasing Score

Traditional Spec Method Optimal Design

Limit of Feasibility

Value-Driven Design

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Brake Material + $11,000 - 90 lbs.Rudder - $10,000 + 190 lbs.

Net Impact + $ 1,000 + 100 lbs.

Differences in revealed values within a design team lead to choices that, taken together, are clearly lose-lose

Requirements Cause Preference Conflicts

Value-Driven Design

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Design Potential

Distributed Optimal Design

Requirements Method

Val

ue A

Value B

Conflicts: Folding in Attribute Space

Value-Driven Design

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Extensions of VDD beyond Detailed Design

• Conceptual Design

– Develop a Value Model for system optimization

• Technology Development

– Develop a Value Model / Composition Function for technology insertion and evaluation

• Risk Management

– Quantitative valuation of consequences

• Test Planning

– Value of Information

Value-Driven Design

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Summary

• VDD can improve system value by tens of billions of dollars for complex aerospace systems– versus flowing down requirements for extensive attributes

• Value-Driven Design in a nutshell– Optimization is used to design all components

– Extensive variables are incorporated into the objective function

– Component objective functions are coordinated with the system objective function for distributed optimal design

• We must transition VDD to practice

Value-Driven Design

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Future Steps

• What is necessary to mature the VDD concept– pilot application

• University research project - simulated prototype

• Small DoD application (too small means low value, but proof of concept)

• evaluate scalability - to more complex systems and across life cycle

– test theory formally on an existing program• derive falsifiable hypotheses, collect data, assess hypotheses

• use the Abbas-Matheson model to quantify results

• three programs, working from small to large

• How should VDD be introduced into the Community?– Guidebook ...

• What needs to be done prior to PDR to make VDD feasible?– Value model development (need a process)

– Concept optimization (closer to practice)

• What does the govt need to do to make this happen?