dr. daniel p. schrage professor and director center of excellence in rotorcraft technology (cert)

CERT/CASADr. Daniel P. SchrageGeorgia Institute of TechnologyAtlanta, GA 30332-0150www.asdl.gatech.edu

Aerospace Systems Engineeringas an Integrating Function

for the Georgia Tech Graduate Program in Aerospace Systems

DesignDr. Daniel P. SchrageProfessor and Director

Center of Excellence in Rotorcraft Technology (CERT)Center for Aerospace Systems Analysis (CASA)


Presentation Outline• Overview of the Graduate Program

Aerospace Systems Design Program

• The Evolution from an IPPD to an IPPD through RDS to a Modern Aerospace Systems Engineering Approach

• Description of the Graduate Course in Aerospace Systems Engineering

• Opportunities for Collaboration with the School of ISYE


Georgia Tech School of AE

• School of Aerospace Engineering– One of original six Guggenheim Schools of Aeronautics– 34 full time faculty– ~600-700 undergraduate students (AE majors)

– ~250 -300 graduate students– Highest Rated Public Aerospace School (Overall: UG – 2nd to

MIT;GR-3rd to MIT & Stanford, U.S. News & World Report)

• Six Disciplinary Groups (Full A.E. School)

• Aerodynamics and Fluid Mechanics

• Structural Mechanics and Materials

• Propulsion and Combustion

• Flight Mechanics and Controls

• Structural Dynamics and Aeroelasticity

• System Design and Optimization


Graduate Program in Aerospace Systems Design

• Includes core and elective courses to:– Provide a Practice-oriented M.S. Program– Provide a Integrated-Discovery Focused Ph.D program

• Includes a combination of disciplinary, methods and synthesis courses for System Design of Complex Systems:– Aircraft and Rotorcraft– Missiles and Space– System of Systems: Army/DARPA FCS; FAA/NASA NAS

• Integrates Research and Education– Two active research laboratories, ASDL and SSDL– Approx. 100 students (~80 supported)– Approx. 15 research engineers

• Uses an IPPD through RDS Approach and a modern Aerospace Systems Engineering Course as an Integrating Function for the Program


Evolution of the Georgia Tech Aerospace Systems Design Program

CE/IPPD CE/IPPD

RSM forAdvanced Synthesis

RSM forAdvanced Synthesis

RDSRDS

FPIFPI

CASA CASA

‘94

‘96

‘97

‘98

Focus: Affordable Aerospace Systems Design Methodology; ASDL Estab.

Focus: Pioneering Research into Response Surface Methodology (RSM) for advanced sizing/synthesis

Focus: Addressing Economic Uncertainty & Viability results in Robust Design Simulation

Focus: Efficient Probabilistic Analysis through Fast Probability Integration (FPI)

Focus: Systems & Systemof Systems Analysis forComplex Systems andMovement toward a ModernApproach to Systems Engineering

Aero + Structures

FLOPS-IMAGE-RSE Interface developed

• Morphological

Matrices• Pugh Diagram

CustomerRequirements

Establishthe Need

FPI

Sizing

Econ.

x2

x1 xn

y1

y2 yn

Probabilistic Feasibility AND

Viability

x1

x2

$/RPM

Target

Pro

bab

ilit

y

$/RPM

DesiredSolution

FeasibleSolution

BaselineMean

‘84 - Graduate Rotorcraft Design Program Established

‘92 - Graduate, CE/IPPD Fixed-Wing Design Program Established w/ NASA’s USRA ‘89 - Intro to Concurrent Engineering (CE) & Design for LCC courses

Graduate Program Development

‘94- NASA MDA Fellowship Grant

and New Approaches to MDO Grant

‘95-’96 Space Systems Design

Laboratory (SSDL) Established

‘97- NRTC Center of Excellence

Renewal

‘98- Center for Aerospace Systems Analysis (CASA)

Initiated

‘99- Boeing Awards GTAE/CASA

Faculty Chair in Aerospace Systems

Analysis’00 GEAE USA

‘95


Why it is Unique?• Is the Only Formal Graduate Aerospace Systems Design Program in

the U.S., and probably throughout the world• Addresses the System Design of Complex Systems (Not Conceptual

Design) utilizing a Generic IPPD Methodology, as a modern approach for Systems Engineering

• Provides an engineering approach to Risk Based Management through Robust Design Simulation (RDS) environment for Implementing the IPPD Methodology at the “Front End” that can be continued for Process Improvement and Merging with Six Sigma methods

• Provides a practical way of incorporating “lean” and other initiatives into the front end of a complex system’s life cycle

• Has spun off various methods, tools, and techniques from this IPPD through RDS approach for a variety of customers

• Have moved to address “System of Systems” problems such as FCS and air transportation architectures for the NAS


Who are the Primary & Supporting Faculty?• School of A.E.:Primary Faculty

– Dr. Dimitri Mavris, Director of ASDL and Boeing Chair Professor in Advanced Aerospace Systems Analysis

– Dr. John Olds, Associate Professor and Director of SSDL– Dr. Jim Craig, Professor and Co-Director of CASA– Dr. Dan Schrage, Professor and Director, CASA & CERT– Two recruitments: Lewis Chair in Space Systems Technologies;

Junior Faculty in Design Methodology & ToolsSupporting Faculty: Dr. Amy Pritchett (AE/ISYE), Dr. Eric Johnson, &

Dr. JVR Prasad

• Some Participation from the School of M.E.– Dr. Farokh Mistree, Professor and Director of SRL– Dr. Bob Fulton, Professor

• Some Participation from the School of E.C.E– Dr. George Vachtsevanous, Professor and Director of the Intelligent

Control Laboratory


Overview of Center for Aerospace Systems Analysis (CASA)

• Established in1998 based on successful development of the ASDL from 1992 and the successful development of the SSDL from 1995; Serves as oversight for these labs

• Through its laboratories provides the primary research support to the graduate program in Aerospace Systems Design which currently has ~ 100 students of which over 80 % are U.S. citizens

• Research support provides over $5M per year in sponsored research and supports ~ 80 students & 15 research engineers

• Provides a modern approach to systems engineering based on an Integrated Product/Process Development (IPPD) methodology executed through Robust Design Simulation (RDS)


Why Systems Analysis?• Systems Analysis is a scientific process, or methodology,

which can best be described in terms of its salient problem-related elements. The process involves:– Systematic examination and comparison of those alternative

actions which are related to the accomplishment of desired objectives– Comparison of alternatives on the basis of the costs and the

benefits associated with each alternative– Explicit consideration of risk

• NASA, DoD, and Industry are realizing that more emphasis must be placing on enhancing systems analysis at the front end of the life cycle using modern systems engineering approaches


CASA’s Laboratories

Aerospace Systems Design Labwww.asdl.gatech.edu

Aerospace Systems Design Labwww.asdl.gatech.edu

B.S.A.E. - M.S. - Ph.D DegreesB.S.A.E. - M.S. - Ph.D Degrees

Space Systems Design Labwww.ssdl.gatech.edu

Space Systems Design Labwww.ssdl.gatech.edu

Design Frameworks Lab

Flight Sim Lab

IPERT Lab Uninhabited Aerial VehicleResearch Facility

Design, Build, Fly Lab


An Integration and Practice-Oriented M.S.Program in Aerospace Systems Design

Legend: Core Classes Elective Classes

SummerSemester IISemester I

Design Methods/Techniques ISE/PLMCDevelopment

SpecialProject

Safety By Design

Aerospace Systems

Engineering

DisciplinaryElectives

PropulsionSystemsDesign

SystemsDesign I

AppliedDesign I

SystemsDesign II

AppliedDesign II

Design Tools/Infrastructure

ModernDesign

Methods I

Modern Design

Methods II

ProductLife Cycle

Management Internship

Mathematics (2 Required) Other Electives


Classroom Implementation

Aerospace SystemsDesign Laboratory

MethodsMethods StudentsStudents

Aerospace Systems Design Education & Research Philosophy

Funding

• Methods Formulation• Supports Basic Research• Implementation of Methods

Partners:ONRNASAAFRLNRTC

Government Industry

RelevantProblems

Data & Tools

Partners:GEAERRA

LMTASBoeing

SikorskyFunding


Design Process Paradigm Shift(Research Opportunities in Engineering Design, NSF Strategic Planning Workshop Final Report,

April 1996)

100%

50%

0%

Today’s Design Process Future Design Process

Kno

wle

dge

Abo

ut D

esig

n D

esig

n Fr

eedo

m

Cos

t Com

mitt

ed

Con

cept

Pre

limin

ary

Des

ign

Analysis and Detail

Design

Prototype Development

Redesign Product Release

• A paradigm shift is underway that attempts to change the way complex systems are being designed

• Emphasis has shifted from design for performance to design for affordability, where affordability is defined as the ratio of system effectiveness to system cost +profit

• System Cost - Performance Tradeoffs must be accommodated early

• Downstream knowledge must be brought back to the early phases of design for system level tradeoffs

• The design Freedom curve must be kept open until knowledgeable tradeoffs can be made


What is IPPD?

• Integrated Product/Process Development (IPPD) is a management methodology that incorporates a systematic approach to the early integration and concurrent application of all the disciplines that play a part throughout a system’s life cycle (Technology for Affordability: A Report on the Activities of the Working Groups to the Industry Affordability Executive Committee, The National Center for Advanced Technologies (NCAT), January 1994)

• IPPD evolved out of the commercial sector’s assessment of what it took to be world class competitive in the 1980s

• The DoD has required IPPD and the use of IPTs where practical throughout the DoD Acquisition Process for Major Systems (DoD 5000.2R)

• Conduct of IPPD requires Product/Process Simulation using Probabilistic Approaches


Quality Revolution - Where Competition is Today

Cost Advantage

Statistical Process Control Variability reduction Customer Satisfaction

Quality

Cheap LaborHi Volume, Lo Mix Production

Cycle time Comparison (JIT)Integrated Product/Process DevelopmentProduct/Process SimulationHi Skill adaptable Workforce

Time-to-Market

Cost Independent of VolumeAgility Commercial/Military Integration Virtual Companies

Product Variety

Company Goodness

Environment

1960 1970 1980 1990 2000

Manufacturing Enterprise Flexibility

NCAT Report, 1994


Japanese Auto Industry Made Changes Earlier Than U.S. Auto Industry

90% Total Japanese

Changes Complete

U.S. Company

Japanese Company

20

-24

M

on

ths

14

-17

M

on

ths

1-3

M

on

ths

Job

#1

+3

M

on

ths

Nu

mb

er

of

En

gin

eeri

ng

Pro

du

ct

Ch

an

ges

Pro

cess

ed

Japanese/U.S. Engineering Change Comparison


Concurrent vs Serial Approach

Design & Development

Test & Production

Supporthigh

low

Nu

mb

er

of

De

sig

n C

ha

ng

es

Time

Cost of Change

Serial Approach

Concurrent Engineering

Approach

IPPD Focus


Traditional Design & Development Using only a Top Down Decomposition Systems Engineering Process


IPPD Requires the Computer Integration of Product and Process Models and

Tools for System Level Design Trades and Cycle Time Reduction

SYSTEMPROCESS

RECOMPOSITION

SYSTEMFUNCTIONAL

DECOMPOSITION

COMPONENTFUNCTIONAL

DECOMPOSITION

COMPONENTPROCESS

RECOMPOSITION

PARTPROCESS

RECOMPOSITION

PARTFUNCTIONAL

DECOMPOSITION

ProductTrades

ProcessTrades

ProductTrades

ProcessTrades

PRELIMINARYDESIGN

(PARAMETER)

PRELIMINARYDESIGN

(PARAMETER)

DETAILDESIGN

(TOLERANCE)

DETAILDESIGN

(TOLERANCE)

MANUFACTURINGPROCESSES

CONCEPTUALDESIGN

(SYSTEM)

ProcessTrades

INTEGRATEDPRODUCTPROCESS

DEVELOPMENT

ProductTrades


Integrated Product and Process Development Modeling Flow (Aircraft Example)

Top-Down Aircraft

LCC Model

ComponentCost Modeling

AircraftSynthesis(Sizing)

FiniteElementAnalysis

wingplanformgeometry

bottom-upwing costestimate

KBSProcessModeling

cust. requirements

perf. requirements

materials

loads

labor rates

learning curves

cost model

req’d inputs

weights

labor hoursmaterial costs

ENGINEERING MODELSProduct Decomposition

MULTI-LEVEL LCC MODELProcess Recomposition

IntegratedDesign

Environment

costmetrics

performancemetrics

productmetrics

processmetrics

structural concepts

alternative processes

re-designdecision


Wing Point Design Regions

• Representative structure at each location– upper and lower panels

– rib and spar structure

William J. Marx

Aft wing box–variable chordwise load

intensities due to wing bending

–high spanwise load intensities

Forward wing box–low load intensities with respect to

wing bending

–minimum gage region

Wing tip box–stiffness critical due to

aeroelastic effects

–high load intensities

HSCT Integrated Design & Manufacturing Ph.D Thesis (W. Marx, 1997)


Aircraft Life Cycle Cost Analysis (ALCCA) - including Economic Analysis

AIRLINERETURN ON

INVESTMENT

AIRLINEOPERATING

COST

CALCULATEAIRLINE ROI

MANUFACTURERCASH-FLOW

ROI

AIRCRAFTMANUFACTURING

COSTS

CALCULATEMANUFACTURER

CASH-FLOW

AIRCRAFTWEIGHTS

LABORRATES

LEARNINGCURVES

PRODUCTIONQUANTITY

RDT & ECOSTS

UNITCOSTS

AVERAGECOST

YES

NO

PRODUCTION

SCHEDULE

AIRLINE

PAYMENT SCHEDULE

MANUFACTURERROI VS PRICE

AIRCRAFT MISSIONPERFORMANCE

FUEL, INSURANCEDEPRECIATION RATES

LABOR & BURDENRATES

YES

NO

DIR

EC

T

CO

ST

S

IND

IRE

CT

CO

ST

S

TOTALOPERATING

COST

AIRLINEROI VS PRICE

REVENUE

TAX RATE

ACQUISITION

SCHEDULE

PREPAYMENT

& DEPR. SCHEDS

ENGINETHRUST & WGHT.

ROI

PRICE

AirlineYield

ProductionQuantity


Component WeightsEngine Thrust and

WeightLabor Rates

Production QuantityLearning Curves

Component CostsUnit CostsRDT&E CostsAvg. Costs

AircraftManufacturing

Costs

AircraftManufacturing

Costs

Previous MfgCost Module

Labor RatesProduction

QuantityLearning Curves

Component Weights

Engine Thrust

Manufacturing Hours Quality Assurance Hours

Tooling Hours(Raw Material Costs)(Buy-To-Fly Ratios)

Material CostsMaterial Breakdown

Mfg. Labor RateQual.Assur. Labor RateMaterial Burden Rates

Mfg. Labor L. CurveQA Labor L. Curve

Tooling L. CurveMaterial L. Curve

fromCLIPS

newALCC

Ainput

Aircraft Manufacturing Costs

New Wing Production Module

WingProduction

PBC

Module

WingProduction

PBC

Module

TheoreticalFirst Unit

Cost

TheoreticalFirst Unit

Cost

Non-Recurring

& RecurringProduction

Non-Recurring

& RecurringProduction

Component CostsUnit Costs

RDT&E CostsAverage Unit Costs

Wing TFUCManufacturing Hours & CostQuality Assur. Hours & CostTooling Hours & CostMaterial CostsCost/Time Analysis

NewALCCA

output

Aircraft Process Based Manufacturing Cost Model


Cost Time Analysis for Theoretical Production

[Source: MIL-HDBK-727]

FinishingOperations

Material Cost

Cumul. time

Cost / Unit

Production

Setup

DesignTools

PurchaseMaterial

Tool Design Cost

SetupCost

Production Cost Largest Run

Finishing Operations Cost Largest Run Production Cost Smallest Run

Finishing Operations Cost Smallest Run

Cost/Time Curve

End Points for WideRange of ProjectedLot Sizes

Largest Run

Smallest Run

Theoretical First Unit Cost

(TFUC)


Cost/Time Constraint Curve for Candidate Selection

[Ref. MIL-HDBK-727]

TIME

Process AEnd Point

UNIT COST

Process BEnd Point

Process CEnd Point

Process DEnd Point

Cost/Time Curve

Process E


[Ref. MIL-HDBK-727]

FinishingOperations

Material Cost

Production

Setup

DesignTools

PurchaseMaterial

Tool Design Cost

SetupCost

Production Cost Largest Run

Finishing Operations Cost Largest Run Production Cost Smallest Run

Finishing Operations Cost Smallest Run

End Points for WideRange of ProjectedLot Sizes

Largest Run

Smallest Run

Cumul. time

Cost / Unit

Cost/Time Curve

Theoretical First Unit Cost

(TFUC)

Probabilistic Cost/Time Production Analysis


Georgia Tech Generic IPPD Methodology

• Methodology provides a procedural design (trade-off iteration) approach based on four key elements:

– Systems Engineering Methods and Tools (Product design driven, deterministic, decomposition approaches; MDO is usually based on analytic design approach)

– Quality Engineering Methods and Tools (Process design driven, nondeterministic, recomposition approaches; MDO is usually based on experimental design approach)

– Top Down Design Decision Process Flow (Provides the design trade-off process)

– Computer Integrated Design Environment(Information Technology driven)

• Methodology has been implemented through Robust Design Simulation (RDS) for a number of applications


Georgia Tech Generic IPPD Methodology

COMPUTER-INTEGRATED ENVIRONMENT

PR

OD

UC

T D

ES

IGN

DR

IVE

NP

RO

CE

SS

DE

SIG

N D

RIV

EN

REQUIREMENTS & FUNCTIONAL

ANALYSIS

SYSTEM DECOMPOSITION &

FUNCTIONAL ALLOCATION

SYSTEM SYNTHESIS THROUGH MDO

SYSTEM ANALYSIS &

CONTROL

ESTABLISH THE NEED

DEFINE THE PROBLEM

ESTABLISH VALUE

GENERATE FEASIBLE ALTERNATIVES

EVALUATE ALTERNATIVE

7 M&P TOOLS AND QUALITY FUNCTION DEPLOYMENT (QFD)

ROBUST DESIGN ASSESSMENT & OPTIMIZATION

ON-LINE QUALITY ENGINEERING &

STATISTICAL PROCESS

MAKE DECISION

SYSTEMS ENGINEERING METHODS

QUALITY ENGINEERING METHODS

TOP-DOWN DESIGN DECISION SUPPORT PROCESS


The Systems Engineering ProcessProcess Input• Customer Needs/Objectives/ Requirements - Missions - Measures of Effectiveness - Environments - Constraints• Technology Base• Output Requirements from Prior Development Effort• Program Decision Requirements• Requirements Applied Through Specifications and Standards

Requirements Analysis• Analyze Missions & Environments• Identify Functional Requirements• Define/Refine Performance & Design Constraint Requirement

Functional Analysis/Allocation• Decompose to Lower-Level Functions• Allocate Performance & Other Limiting Requirements to All Functional Levels• Define/Refine Functional Interfaces (Internal/External)• Define/Refine/Integrate Functional Architecture

Synthesis• Transform Architectures (Functional to Physical)• Define Alternative System Concepts, Configuration Items & System Elements• Select Preferred Product & Process Solutions• Define/Refine Physical Interfaces (Internal/External)

System Analysis& Control(Balance)

Verification

Requirement Loop

Design Loop

• Trade-Off Studies• Effectiveness Analysis• Risk Management• Configuration Management• Interface Management• Performance Measurement - SEMS - TPM - Technical Reviews

Process Output• Development Level Dependant - Decision Data Base - System/Configuration Item Architecture - Specification & Baseline

Related Terms: Customer = Organization responsible for Primary Functions Primary Functions = Development, Production/Construction, Verification, Deployment, Operations, Support Training, DisposalSystems Elements = Hardware, Software, Personnel, Facilities, Data, Material, Services, Techniques


Aerodynamics Economics

Propulsion

Safety

Aerodynamics

S&C

Propulsion

Performance

Manufacturing

Economics

Safety

Structures

Manufacturing

Structures Performance

Conceptual Design Tools (First-Order Methods)

Synthesis & Sizing

Preliminary Design Tools (Higher-Order Methods)

Geometry

Mission

Increasing Sophistication and

Complexity

Approximating Functions Direct Coupling of Analyses

Integrated Routines Table Lookup

Modeling and Simulation:Varying Fidelity of Synthesis and Sizing

S&C


The Quality Engineering Process provides Recomposition Methods & Tools

CustomerQuality Function

Deployment

Off-Line

Quality Function

Deployment

Off-Line

Seven Managementand Planing

ToolsOff-Line

Seven Managementand Planing

ToolsOff-Line

Statistical Process Control

On-Line

Statistical Process Control

On-Line

RobustDesign Methods(Taguchi, Six -Sigma, DOE)

Off-Line

RobustDesign Methods(Taguchi, Six -Sigma, DOE)

Off-Line

Knowledge Feedback

•Needs• Identify Important Items

•Variation Experiments

•Make Improvements

•Hold Gains

•Continuous Improvement

Having heard the “voice of the customer”, QFD prioritizes where improvements are needed; Taguchi provides the mechanism for identifying these improvements


CoVE: Collaborative Visualization Environment

for Complex Systems Design

Funded by the

Defense University Research Instrumentation Program (DURIP)

February 2003


CoVE Objectives• A semi-immersive, very high resolution, Collaborative

Visualization Environment (CoVE). • Used to investigate the use of semi-immersive virtual

environments in collaborative design processes. • Basic concept for the CoVE is a large, high resolution

display wall similar to those developed for media companies and operations centers.

• It will allow us to apply emerging probabilistic design methods to problems at an industrial scale.

• It is expected to promote new research in design, visualization and usability with other leading centers on campus.


CoVE Features

• A single CoVE with a 25 M-pixel resolution curved data wall measuring 20 ft wide by 12 ft tall.

• Seating for up to 12 participants, each with their own computers and local displays.

• The basic design will be configured so that it can be used with another CoVE to execute distributed collaborative design with another team at a remote location.

• The CoVE will include both single person and group video conferencing capabilities.

• Project budget: $630k


Examples


PRICE $K

ROIA

Den

sity

Criterion 1

Cri

teri

on 2

Alternative 1

Alternative 3Alternative 2

Area ofInterest

z1maxz1min

z2min

z2max

3K

FB

(lb

)6

K F

B (

lb)

Ra

ng

e (

nm

i)E

ng

eW

t (lb

)F

an

Dia

(in

)S

FC

(1

/hr)

ZOPRD ZPQD25 ZTH41 ZSDE12 ZSDE2 ZSDE25 ZSDE41 ZSDE49 ZSWC41 ZSWC42 WT_ADDEROPRD PQD25 TH41(R)

Fan Boost CPR HPT LPT HPT Ch.(%W25)

HPT NCh.(%W25)

Wt. Adder(lbs)

Technology MetricsDesign Variables

Ou

tpu

t C

TQ

s

1X

6-1

Torpedo Length

Torpedo Velocity

Torpedo Range

Torpedo Noise

-1 X8 1

Defi ne the

Problem

Defi ne Concept Space

Modeling and

Simulation

I nvestigate Design Space

Feasible or

Viable?

I dentif y Technologies

Evaluate Technologies

Select Technologies

1 2 3 4 5 6 7 8Defi ne

the Problem

Defi ne Concept Space

Modeling and

Simulation

I nvestigate Design Space

Feasible or

Viable?

I dentif y Technologies

Evaluate Technologies

Select Technologies

1 2 3 4 5 6 7 81 2 3 4 5 6 7 8

50,000 ft.

1. Taxi & T.O.F.L.=11,000 ft.

3. CruiseM=0.9

8. Abort3000 ft.

10. LandF.L.= 11,000 ft.

7. LoiterM=0.6

9. ReserveM=0.6

2. Climb

67,000 ft.

35,000 ft.

4. Climb

5. CruiseM=2.4

6. Descent

200 nm100 nm750 nm50 nm5,000 nm

Technology Space Mission Space

R

esp

on

ses

Mission Requirements

Snapshot 1

R

esp

on

ses

Technology Dials

Snapshot 3

Vehicle Attributes

Snapshot 2

Concept Space

(Vehicle Attributes)

Baseline +

Fixed Geometry, Technology SetFixed Requirements, Geometry

Fixed Requirements, Technology Set

Res

po

nse

s

R

esp

on

ses

(Technology Dials)(Mission Requirements)

Installed Power [SLS,MCP]

Empty Weight

Alpha = .052Beta = .0076Scale = 1.145

Beta Distribution

Normal Distribution

Mean = 1.0

Std Dev = .007

JPM(lines of constantprobability)

EDF(plottingsample data)

Area of Interest

JPDM

Video Conference

RAM Model

CFD Visualization

Morphological Matrix Unified Trade-off Environment

QFD

Technology Impact Matrix

Constraint AnalysisMission Profile

CDF

Technology Profiles

Example ASDL Application


STAIR CIR/15B/235

CIR/5C/305

STAIR

DOWN

CLS

APPROXIMATE SCALE:

2D

2D

CIR/5D/820LOUNGE - 6/700

2D

CLS

2D

2D

DOWNCIR/5E/305

STAIR

CLS

STAGE

5A/460/0

PROJECTION RM.

5/2440/90

LECTURE RM.

DOWN

CLS

CIR/5A/235STAIR

UP

DN.

PROJECTION RM.

4/2440/90

LECTURE RM.

CLS

PROJECTION RM.

3/2440/90

LECTURE RM.

1

STAGE/3A/460/0

DOWN

0 2 4 6 8 10

3/2440/90

LECTURE RM.

CLS CLS

CoVE Conceptual Layout

Weber 2nd Floor SiteOperations

Video Conferencing

Observers

Data Wall

Participants


CoVE Tentative Schedule• Award announcement: February 2003

• Final specifications: April 2003

• Site preparations: May 2003

• Construction & Installation: July 2003

• Testing: September 2003

• Acceptance: October 2003


Aerospace Systems Engineering Course: AE 6370

• Introduces new graduate students to Aerospace Systems Engineering and a methodology for Implementing it through IPPD through Robust Design Simulation (RDS)

• Consists of covering traditional systems engineering methods and tools; introduces quality engineering methods and tools; introduces multi-attribute decision methods; and introduces the need for a computer integrated environment

• Course consists of a mid-term exam and team projects (~5 students per team) addressing the concept formulation for complex systems or system of systems

• Utilizes a simple set of integrated tools to allow the teams to conduct the first iteration through a complex system design

• Will be offered as a distance learning course for the first time in Fall 2003


Aerospace Systems Engineering Taught using an Integrated Set of Tools

Baseline 1 st Option 2 nd Option

Engine Type MFTF Mid-TandemFan

Turbine Bypass

Fan 3 Stage 2 Stage No Fan

Combustor Conventional RQL LPP

Nozzle Conventional Conventional +Acoustic Liner

Mixer EjectorNozzle

AircraftTechnologies

None CirculationControl

Hybrid LaminarFlow Control

a lt. c o n c e p ts

crite

ria

H O W s

M o rp h o lo g ic a l M a tr ix

B e s tA lte rn a tiv e

T e c h . A lte rn a t iv eId e n tif ic a t io nQ F D

M A D MM A D M

W e ig h ts

P u g h E v a lu a tio n M a tr ix

S u b je c t iv e E v a lu a t io nS u b je c t iv e E v a lu a t io n( th ro u g h e x p e r t o p in io n ,( th ro u g h e x p e r t o p in io n ,

s u rv e y s , e tc .)s u rv e y s , e tc .)


Ten Complex System Formulation Projects from AE6370, Fall 2002

• AIAA Graduate Student Missile Design Competition: “Future Target Delivery System(Missile Multipurpose Target”

• RFP for a “High Firepower Payload for Missile Defense (Missile Interceptor)

• NASA Sponsored University Competition for the “Conceptual Design of a Titan (Saturn’s largest moon) Vertical Lift Aerial Vehicle”

• AHS/NASA Student Design Competition for “VTOL Urban Disaster Response Vehicle”

• NASA “Personal Air Vehicle Evaluation Program: to identify VTOL and ESTOL Concepts”

• RFP for a “Quiet Supersonic Business Jet” in conjunction with Gulfstream Aerospace Company

• DoD Potential Joint Program for an “Air Maneuver & Transport Concepts for the Objective Force”

• AIAA Student Competition for “Subsonic Commercial QuEST”• AUVS International Aerial Robotics Competition and DARPA Project:

“Intelligent Uninhabited Aerial Vehicle (UAV) using Software Enabled Control (SEC)”

• Army Aviation Recapitalization Program: “Technology and Risk Assessment for the Army’s UH-60M Helicopter Improvement Program”


What is IPPD Through RDS

• Integrated Product/Process Development (IPPD) means applying Concurrent Engineering at the front end of a system’s life cycle where design freedom can be leveraged and product/process design tradeoffs conducted in parallel at the system, component, and part levels

• Implementation of IPPD requires moving from a deterministic point design approach to a probabilistic family design approach to keep the design space open and from committing life cycle cost before the system life cycle design trade-offs can be made

• Robust Design Simulation (RDS) provides the necessary simulation and modeling environment for executing IPPD at the System level

• Continuation of RDS along the system life cycle implies the creation of a Virtual Stochastic Life Cycle Design Environment

• An Overall Evaluation Criterion (OEC) based on System Affordability should be identified early and its variability tracked along the life cycle time line


Roadmap to Affordability Through RDS

Objectives:ScheduleBudgetReduce LCCIncrease AffordabilityIncrease Reliability. . . . .

Customer Satisfaction

Synthesis & Sizing

Technology Infusion

Physics-Based

Modeling

Activity and Process-

Based Modeling

Technology Infusion

Physics-Based

Modeling

Activity and Process-

Based Modeling

Subject to

Economic & Discipline

Uncertainties

Economic & Discipline

Uncertainties

Impact of New Technologies-Performance & Schedule Risk

Impact of New Technologies-Performance & Schedule Risk

Robust Solutions

Robust Design SimulationRobust Design Simulation

Simulation Operational Environment

Economic Life-Cycle Analysis

Design & Environmental Constraints

Design & Environmental Constraints


Interactive RDS Environment

Aero

Structures

Weights

Etc.

DISCIPLINARY RSEs

SYNTHESIS & SIZING

FPI

RSEs

Objective0%

100%

Pro

babi

lity

Criterion 1or Requirement 1

Cri

teri

on 2

or R

equi

rem

ent 2

R

esponse

s R

esponse

sM

etrics/

Obje

ctives

Metrics/

Obje

ctives

Cons

train

tsCons

train

ts

R

esponse

s R

esponse

sM

etrics/

Obje

ctives

Metrics/

Obje

ctives

Cons

train

tsCons

train

ts

R

esponse

s R

esponse

sM

etrics/

Obje

ctives

Metrics/

Obje

ctives

Cons

train

tsCons

train

ts

Concept Space

Technology Space Requirements

Space

1

TWR

-1

² %$/ RPM

TOFLm odSLNm od

-1 SW 1

CDF

JPDM

DynamicContourPlots

FPI / MC


Risk & Uncertainty are Greatest at the Front

KNOWN-UNKNOWNS

UNKNOWN-UNKNOWNS

KNOWNS

CONCEPT VALIDATION FULLSCALE

DEVELOPMENT

PRODUCTION DEVELOPMENT


OverallEvaluationCriterion

(OEC)Response

Time

OEC Target

System Design (Preliminary/Parameter)

System Integration (Detail/Tolerance)

Manufacturing (On-Line Quality)

Uncertainty Risk Management/Reduction

OEC Target

Initial Distribution

System Definition &

Tech. Development (Conceptual/System)

Reduced Variability and Improved Mean Response

Traditional C p and C p k Approach for Continuous, On-line Process Improvement

Continuous Product Improvement / Innovation

Fuzzy Front End

Upper Specification

Lower Specification

Define Distributions

Bring the Development Process Under Control, C p = 1

Approach Six-Sigma, 1 < C p < 2

Upper Specification

Lower Specification

Six-Sigma Achieved, C p = 2

OverallEvaluationCriterion

(OEC)Response

Coninuous RDS along the System Life Cycle to link the “fuzzy front end” to the “process capability approaches”


The VSLCDE- Key Characteristics

The purpose of VSLCDE is to facilitate design decision- making over time (at any level of the organization) in the

presence of uncertainty, allowing affordable solutions to be reached with adequate confidence. It is a research testbed.

Virtual . . . Simulation-based system life-cycle prediction Stochastic . . . Time-varying uncertainty is modeled; temporal decision-making Life-Cycle . . . the design, engineering development, test, manufacture, flight test,

operational simulation, sustainment, and retirement of a system. The operational simulation includes virtual testing, evaluation, certification, and fielding of a vehicle in the existing infrastructure, and tracking of its impact on the economy, market demands, environment.

Design . . . Implies that the environment’s main role is to provide knowledge for use by decision-makers, especially for finding robust solutions

Environment . . . Implies the support of geographically distributed analyses and people through collaboration tools and data management techniques


Some Opportunities for Collaboration between the Schools of AE and ISYE

• Integration of ISYE Logistics with AE Aerospace Systems Design Program for a variety of customers (Industry and Government)

• With Lockheed Martin on a Modern Systems Engineering Approach (addressing Product Life Cycle tradeoffs from the Outset) based on the Joint Strike Fighter (JSF) Development Approach successes and Lessons Learned (POC: Bill Kessler, LM Lean Enterprise Mgr and Tom Burbage, LM JSF VP)

• With OSD/DOD/USAF New Focus on Systems Engineering Education and Research

• With USAF – GT(CEE) Initiative in taking over the Lean Sustainment Initiative from MIT

• With NASA Langley National Institute of Aerospace (NIA) and with NASA Ames Engineering of Complex Systems (ECS) programs

• Others?

dr. daniel p. schrage professor and director center of excellence in rotorcraft technology (cert)

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