Скачать презентацию Aerospace Systems Engineering The Fuzzy Front End Dr Скачать презентацию Aerospace Systems Engineering The Fuzzy Front End Dr

40cde67731094afb584299b18650b0b6.ppt

  • Количество слайдов: 78

Aerospace Systems Engineering The Fuzzy Front End Dr. Daniel P. Schrage Professor and Director, Aerospace Systems Engineering The Fuzzy Front End Dr. Daniel P. Schrage Professor and Director, CASA, CERT, & PLMC Dr. Dan De. Laurentis Asst. Professor, ASDL School of Aerospace Engineering Georgia Institute of Technology Atlanta, GA 30332 -0150 Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Presentation Outline • Introduction to Systems Engineering, the Systems Engineering Process and Systems Analysis Presentation Outline • Introduction to Systems Engineering, the Systems Engineering Process and Systems Analysis • Modern Systems Engineering and the Quality Revolution • The Five Lean Principles as Guiding Principles for Modern Systems Engineering • Integrated Product/Process Development (IPPD) through Robust Design Simulation (RDS) for the Fuzzy Front End to Identify Customer Value and the Value Stream • The Goal for Perfection through creation of a Virtual Stochastic Life Cycle Design Environment (VSLCDE) • A Robust Design Simulation (RDS) Example Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Systems Engineering • Systems Engineering has been defined as an interdisciplinary engineering management process Systems Engineering • Systems Engineering has been defined as an interdisciplinary engineering management process to evolve and verify an integrated, life cycle balanced set of system solutions that satisfy customer needs (SE Fundamentals, DSMC, 1999) • Systems Engineering methods and tools were developed in the early 1960 s to decompose and breakdown complex Aerospace Systems, e. g. Ballistic Missile, Launch Vehicles, Aircraft • These methods and tools contributed greatly to winning the “Space Race” and the “Cold War” • However, a Modern Approach to Systems Engineering must reflect the Quality Revolution which has driven industry for the past 20 years Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

The Systems Engineering Process • As developed for the Department of Defense (Do. D) The Systems Engineering Process • As developed for the Department of Defense (Do. D) the Systems Engineering Process includes three major elements: – Requirements Analysis – Functional Analysis and Allocation – Synthesis • Systems Analysis and Control include the techniques and tools to analyze and control the Systems Engineering Process • The Systems Engineering Process is applied to each stage of life cycle development, one level at a time Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

The Do. D Systems Engineering Process (SE Fundamentals, DSMC, 1999) P R O C The Do. D Systems Engineering Process (SE Fundamentals, DSMC, 1999) P R O C E S S I N P U T Requirements Analysis System Analysis and Control (Balance) Requirements Loop Functional Analysis Allocation Design Loop Verification Synthesis PROCESS OUTPUT Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

The Systems Engineering Process Input • Customer Needs/Objectives/ Requirements - Missions - Measures of The Systems Engineering Process 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 System Analysis & Control (Balance) Requirement Loop 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 • Trade-Off Studies • Effectiveness Analysis • Risk Management • Configuration Management • Interface Management • Performance Measurement - SEMS - TPM - Technical Reviews Design Loop Synthesis Verification • Transform Architectures (Functional to Physical) • Define Alternative System Concepts, Configuration Items & System Elements • Select Preferred Product & Process Solutions • Define/Refine Physical Interfaces (Internal/External) Related Terms: Customer = Organization responsible for Primary Functions = Development, Production/Construction, Verification, Deployment, Operations, Support Training, Disposal Systems Elements = Hardware, Software, Personnel, Facilities, Data, Material, Services, Techniques Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Process Output • Development Level Dependant - Decision Data Base - System/Configuration Item Architecture - Specification & Baseline CASA/CERT/PLMC

Why Systems Analysis? • Systems Analysis is a scientific process, or methodology, which can Why Systems Analysis? • Systems Analysis is a scientific process, or methodology, which can best be described in terms of its salient problemrelated 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, Do. D, 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 Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Lean Principles for Modern Systems Engineering • Systems Engineering developed in the early 1960 Lean Principles for Modern Systems Engineering • Systems Engineering developed in the early 1960 s for a top down hardware decomposition approach • Systems Analysis and Control used to track and evaluate implementation • Work Breakdown Structure (WBS) identified work packages for pulling in the complete supply chain • Software Engineering was developed in 1980 s along a parallel path • Quality Revolution of the 1980’s revealed the need for a quality emphasis, e. g. Concurrent Engineering, IPPD, JIT Six Sigma and Lean Manufacturing • Quality Emphasis has cumulated into a set of Lean Principles , as first identified in the Womack and Jones Book on Lean Thinking • Modern Systems Engineering should start with the Lean Principles as Guiding Principles Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Evolution of Systems Engineering and Software Engineering Standards Application of standards is the realm Evolution of Systems Engineering and Software Engineering Standards Application of standards is the realm of Systems Engineers Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Systems Source: INCOSE CASA/CERT/PLMC Engineering Handbook

Quality Revolution - Where Competition is Today Cost Advantage Cheap Labor Hi Volume, Lo Quality Revolution - Where Competition is Today Cost Advantage Cheap Labor Hi Volume, Lo Mix Production Quality Statistical Process Control Variability reduction Customer Satisfaction Time-to-Market Cycle time Comparison (JIT) Integrated Product/Process Development Product/Process Simulation Hi Skill adaptable Workforce Manufacturing Enterprise Flexibility Product Variety Cost Independent of Volume Agile and Lean Commercial/Military Integration Virtual Companies Company Goodness Environment 1960 1970 1980 1990 2000 NCAT Report, 1994 Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Japanese Auto Industry Used Concurrent Engineering To Make Design Changes Earlier Than U. S. Japanese Auto Industry Used Concurrent Engineering To Make Design Changes Earlier Than U. S. Auto Industry with Reduced Cycle Time Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

The Quality Engineering Process provides Recomposition Knowledge Feedback Customer Seven Management and Planing Tools The Quality Engineering Process provides Recomposition Knowledge Feedback Customer Seven Management and Planing Tools Off-Line • Needs Quality Function Deployment Off-Line • Identify Important Items Robust Design Methods (Taguchi, Six Sigma, DOE) Off-Line • Variation Experiments • Make Improvements Statistical Process Control On-Line • 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 Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Lean Principles as Guiding Principles for Modern Systems Engineering • Establish and Specify value: Lean Principles as Guiding Principles for Modern Systems Engineering • Establish and Specify value: Value is defined by customer in terms of specific products & services, preferably as a Benefits to Cost Ratio (BCR) • Identify the value stream: Map out all end-to-end linked actions, processes and functions necessary for transforming inputs to outputs to identify and eliminate waste (Value Stream Map or VSM) • Make value flow continuously: Having eliminated waste, make remaining value-creating steps “flow” • Let customers pull value: Customer’s “pull” cascades all the way back to the lowest level supplier, enabling justin-time production • Pursue perfection: Pursue continuous process of improvement striving for perfection Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Source: James Womack and Daniel T. Jones, Lean Thinking (New York: Simon & Schuster, 1996). CASA/CERT/PLMC

Relationship of Lean Principles to Systems and Quality Engineering Activities • Value is established Relationship of Lean Principles to Systems and Quality Engineering Activities • Value is established based on Systems Engineering activities, such as requirements definition and functional analysis and allocation, and Quality Engineering activities, such as use of the seven management & planning tools and Quality Function Deployment (QFD) to Define the Problem and Establish Value, through the identification of an Overall Evaluation Criterion (OEC) • The Value Stream is next determined through system synthesis & analysis for Generating and Evaluating Alternatives for establishing customer focused life cycle activities along a timeline, often domain or agency specific • Make Value Flow through decision-making to track, system analyze and control the OEC periodically along the life cycle process, e. g. earned Value, • Let Customers Pull Value to apply the Lean Principles throughout the System Work Breakdown Structure (WBS) to sub-contractors, vendors and suppliers, e. g. the Supply Chain Integration • Pursue Perfection is to apply robust design and 0 ptimization approaches for Process Improvement toward attaining Six Sigma, which is accomplished by shifting the mean to the target and variability reduction , e. g. Statistical Process Control techniques Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

The Relationships between Requirements, Do. D Acquisition, RDTE, and Industry Design Processes MNS Operational The Relationships between Requirements, Do. D Acquisition, RDTE, and Industry Design Processes MNS Operational Req’ts. Documents Mission Area Analyses (MAAs) Do. D Acquisition Process Phases } Phase 0 Phase I Concept Exploration ORD Program Definition & Risk Reduction M. S. I M. S. 0 Phase III Engineering and Manufacturing Development M. S. II Production, Deployment and Operational Support Demilitarization & Disposal M. S. III Advanced Concept Technology Demonstrations (ACTDs) Manufacturing Technology Advanced Technology Demonstrations (ATDs) S&T Categories and RDT&E 6. 1 Basic Research 6. 2 Exploratory Development 6. 3 Advanced Development (7. 8) 6. 4 Engineering Development Industry Design Phases Product Design Phases Conceptual Design Preliminary Design Detailed Design Increasing Fidelity of Analysis and Test Process Design Stages System Design Parameter Design Tolerance Design Off Line Quality Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Statistical Process Control On Line Quality CASA/CERT/PLMC

Interaction Between the Defense Acquisition System, the Requirements Generation System, and the PPBS (Latest Interaction Between the Defense Acquisition System, the Requirements Generation System, and the PPBS (Latest Do. D 5000. 2) Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

NASA’s Life Cycle Process Model (2 nd Generation RLV Risk Reduction Solicitation) Dr. Daniel NASA’s Life Cycle Process Model (2 nd Generation RLV Risk Reduction Solicitation) Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

A Value Example: Military Transport Aircraft Overall Evaluation Criterion (OEC) S i = 1 A Value Example: Military Transport Aircraft Overall Evaluation Criterion (OEC) S i = 1 - P DP H P K Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu LCC = RDTE + PC + O&S +DC CASA/CERT/PLMC

Coninuous RDS along the System Life Cycle to link the “fuzzy front end” to Coninuous RDS along the System Life Cycle to link the “fuzzy front end” to the “process capability approaches” Continuous Product Improvement / Innovation Uncertainty Overall Evaluation Criterion (OEC) Risk Management/Reduction Fuzzy Front End Upper Specification Response OEC Target Lower Bring the Development Process Under Control, C p =1 Define Distributions System Definition & Tech. Development (Conceptual/System) Traditional C System Design (Preliminary/Parameter) p and C pk Specification Approach Six-Sigma, 1

The VSLCDE- Key Characteristics The purpose of VSLCDE is to facilitate design decisionmaking over The VSLCDE- Key Characteristics The purpose of VSLCDE is to facilitate design decisionmaking 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. Q Design. . . Implies that the environment’s main role is to provide knowledge for use by decision-makers, especially for finding robust solutions Q Environment. . . Implies the support of geographically distributed analyses and people through collaboration tools and data management techniques Q Q Q Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Concept Exploration M N S MS 0 Dr. Daniel P. Schrage Georgia Institute of Concept Exploration M N S MS 0 Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Alternative Concepts Analysis of Alternatives System Level Requirements Tech Review O R D MS 1 CASA/CERT/PLMC

What is IPPD? • Integrated Product/Process Development (IPPD) is a management methodology that incorporates 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 1980 s • The Do. D has required IPPD and the use of IPTs where practical throughout the Do. D Acquisition Process for Major Systems (Do. D 5000. 2 R) • Conduct of IPPD requires Product/Process Simulation using Probabilistic Approaches Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Traditional Design & Development Using only a Top Down Decomposition Systems Engineering Process Dr. Traditional Design & Development Using only a Top Down Decomposition Systems Engineering Process Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Life Cycle Cost Gets Locked In Early for Complex Systems using only Systems Engineering Life Cycle Cost Gets Locked In Early for Complex Systems using only Systems Engineering Decomposition Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Concurrent vs Serial Approach Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA Concurrent vs Serial Approach Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

IPPD Requires the Computer Integration of Product and Process Models and Tools for System IPPD Requires the Computer Integration of Product and Process Models and Tools for System Level Design Trades and Cycle Time Reduction CONCEPTUAL DESIGN (SYSTEM) SYSTEM PROCESS RECOMPOSITION SYSTEM FUNCTIONAL DECOMPOSITION Process Trades Product Trades PRELIMINARY DESIGN (PARAMETER) COMPONENT PROCESS RECOMPOSITION Process Trades PRELIMINARY DESIGN (PARAMETER) INTEGRATED PRODUCT PROCESS DEVELOPMENT DETAIL DESIGN (TOLERANCE) COMPONENT FUNCTIONAL DECOMPOSITION Product Trades DETAIL DESIGN (TOLERANCE) Process Trades Product Trades PART PROCESS RECOMPOSITION PART FUNCTIONAL DECOMPOSITION MANUFACTURING PROCESSES Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Georgia Tech Generic IPPD Methodology Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, Georgia Tech Generic IPPD Methodology Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Georgia Tech Generic IPPD Methodology • Methodology provides a procedural design (trade-off iteration) approach 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) – – Top Down Design Decision Process Flow (Provides the design – • Quality Engineering Methods and Tools (Process design driven, Computer Integrated Design Environment(Information nondeterministic, recomposition approaches; MDO is usually based on experimental design approach) trade-off process required for Complex Systems) Technology driven to provide a collaborative interactive environment) Methodology has been implemented through Robust Design Simulation (RDS) for a number of applications Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Georgia Tech Graduate Program in Aerospace Systems Design & Analysis • Initiative kicked of Georgia Tech Graduate Program in Aerospace Systems Design & Analysis • Initiative kicked of in the early 1990 s based on IPPD Approach • Education executed in the School of Aerospace Engineering and research program executed through the Center for Aerospace Systems Analysis (CASA) and its two major Laboratories, The Aerospace Systems Design Laboratory (ASDL) and The Space Systems Design Laboratory (SSDL) • Currently has approximately 140 graduate students with over 80 % U. S. citizens – top students from top universities • Research Program currently at approximately $6 M per year including four faculty and 15 research engineers, plus 100 GRAs • Program is built on probabilistic approaches for implementing IPPD through Robust Design Simulation • Goal is to develop, verify and validate, in collaboration with industry and government, a Virtual Stochastic Life Cycle Design Environment (VSLCDE) Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

A System Integration and Practice-Oriented M. S. Program in Aerospace Systems Design & Analysis A System Integration and Practice-Oriented M. S. Program in Aerospace Systems Design & Analysis Semester II Design Methods/Techniques Aerospace Systems Engineering Applied Systems Design II Design Advanced Design Methods I Propulsion Systems Design Disciplinary Electives Summer ISE/PLMC Development Special Project Applied Systems Design II Advanced Design Methods II Safety By Design Product Life Cycle Management Internship Design Tools/Infrastructure Mathematics (2 Required) Legend: Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Other Electives Core Classes Elective Classes CASA/CERT/PLMC

Aerospace Systems Design Integrated Education & Research Philosophy Industry Government Partners: ONR NASA AFRL Aerospace Systems Design Integrated Education & Research Philosophy Industry Government Partners: ONR NASA AFRL NRTC • Methods Formulation • Supports Basic Research • Implementation of Methods Funding Relevant Problems Data & Tools Funding Partners: GEAE RRA LMTAS Boeing Sikorsky Aerospace Systems Design Laboratory Methods Students Classroom Implementation Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Complex System Formulation initially taught In Aerospace Systems Engineering using an Integrated Set of Complex System Formulation initially taught In Aerospace Systems Engineering using an Integrated Set of Simple Tools Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Current Complex System Formulation Projects in Aerospace Systems Engineering Course (Fall 2003) 1. AIAA Current Complex System Formulation Projects in Aerospace Systems Engineering Course (Fall 2003) 1. AIAA Graduate Student Missile Design Competition “Multi Mission Cruise Missile Design” 2. AHS Student Design Competition for “Design Certification Mountain Rescue Helicopter” 3. NASA Identified Complex System of Systems Problem: “Future Air Transportation Architecture - A System of Systems Problem” 4. NASA Specific Complex System Problem: “Space Shuttle Derivative: What it takes to make it Safe and Flyable” 5. NASA Identified Complex System Problem: “Two Stage Turbine Based Combined Cycle (TBCC) Space Access Launch Vehicle” 6. NASA Aerospace Vehicle Systems Technology Office Student Design: “Quiet Supersonic Business Jet and Transport” Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Current Complex System Formulation Projects in Aerospace Systems Engineering Course (Fall 2003) 7. Homeland Current Complex System Formulation Projects in Aerospace Systems Engineering Course (Fall 2003) 7. Homeland Security and Coast Guard Initiative: “Feasibility of Accelerating the Integrated Deepwater System (IDS): A Network Centric Complex System” 8. Missile System Technical Committee: “Long Range Liquid Target Vehicle (LRLTV)” 9. University Student Design Competition: “International Micro Aerial Vehicle (MAV) Competition” 10. Complex System Formulation for: “Boeing 7 E 7 “Dreamliner” Commercial Transport” 11. Complex System Formulation for : “Morphing UCAV Aircraft” 12. NASA Aerospace Vehicle Systems Technology Office Student Design Competition for: “Unmanned Air Vehicle Systems and Technologies: Replacement for Helios” Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Roadmap to Affordability Through Robust Design Simulation Subject to Technology Infusion Physics. Based Modeling Roadmap to Affordability Through Robust Design Simulation Subject to Technology Infusion Physics. Based Modeling Activity and Process. Based Modeling Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Robust Solutions Design & Environmental Constraints Objectives: Synthesis & Sizing Simulation Economic & Discipline Uncertainties Operational Environment Economic Life-Cycle Analysis Impact of New Technologies. Performance & Schedule Risk Schedule Budget Reduce LCC Increase Affordability Increase Reliability. . . Customer Satisfaction CASA/CERT/PLMC

Synthesis & Sizing is the key for translating Mission into Geometry Safety Aerodynamics Geometry Synthesis & Sizing is the key for translating Mission into Geometry Safety Aerodynamics Geometry Economics Synthesis & Sizing Mission S&C Manufacturing Integrated Routines Table Lookup Structures Conceptual Design Tools Approximating Functions Direct Coupling of Analyses Performance Manufacturing Increasing Sophistication and Complexity (First-Order Methods) Propulsion Structures Performance Preliminary Design Tools (Higher-Order Methods) Propulsion Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Aircraft Life Cycle Cost Analysis (ALCCA) including Economic Cash Flow Analysis PA PR SC Aircraft Life Cycle Cost Analysis (ALCCA) including Economic Cash Flow Analysis PA PR SC ODU HE CT DU IO LE N AIRCRAFT WEIGHTS ENGINE THRUST & WGHT. LABOR RATES PRODUCTION QUANTITY YM E NT AIRL SC INE HE DU LE RDT & E COSTS AIRCRAFT MANUFACTURING COSTS LEARNING CURVES UNIT COSTS CALCULATE MANUFACTURER CASH-FLOW ROI YES MANUFACTURER ROI VS PRICE AVERAGE COST NO AIRCRAFT MISSION PERFORMANCE FUEL, INSURANCE DEPRECIATION RATES LABOR & BURDEN RATES Airline Yield AIRLINE OPERATING COST ROI PRICE DIRECT COSTS INDIRECT COSTS CALCULATE AIRLINE ROI Production Quantity TA RE VE N YES UE XR AT E AIRLINE RETURN ON INVESTMENT AIRLINE ROI VS PRICE NO Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu TOTAL OPERATING COST ON ITI UIS ULE Q AC HED C S NT ME DS AY CHE EP S PR PR. E &D CASA/CERT/PLMC

Risk & Uncertainty are Greatest at the Front Known Unknowns correspond to Risk and Risk & Uncertainty are Greatest at the Front Known Unknowns correspond to Risk and Known Probability Distribution KNOWNS KNOWN-UNKNOWNS UNKNOWN-UNKNOWNS CONCEPT VALIDATION FULL PRODUCTION DEVELOPMENT SCALE DEVELOPMENT Un. Known Unknowns correspond to Uncertainty and Unknown Probability Distribution Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

The Five Step RDS Process 1 Design Space Model Determine System Feasibility Constraint Fault The Five Step RDS Process 1 Design Space Model Determine System Feasibility Constraint Fault Tree P(feas) Xi = Design Variable Ci = Constraint FPI(AIS) or Monte Carlo AND C 1 C 2 C 3 C 4 3 N P(feas) < esmall Y x 1 5 Decision Making x 2 • MADM Techniques • Robust Design Simulation • Incorporate Uncertainty Models x 1 x 2 x 3 Problem Definition Identify objectives, constraints, design variables (and associated side constraints), analyses, uncertainty models, and metrics x 3 Constraint Cumulative Distribution Functions (CDFs) Examine Feasible Space Design Space Model 2 P FPI(AMV) or Monte Carlo Relax Y Constraints? P P C 1 C 2 C 3 4 Technology Identification/Evaluation/Selection (TIES) • Technology Selection • Resource Allocation • Robust Design Solution • Identify Technology Alternatives • Collect Technology Attributes • Form Metamodels for Attribute Metrics through Modeling & Simulation • Incorporate Tech. Confidence Shape Fcns. • Probabilistic Analysis to obtain CDFs for the Alternatives Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Obtain New CDFs P Relax Active Y Constraints ? N Ci Old Tech. New Tech. CASA/CERT/PLMC

Interactive RDS Environment FPI / MC Dr. Daniel P. Schrage Georgia Institute of Technology Interactive RDS Environment FPI / MC Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Two Examples on Application of IPPD Through RDS System of Systems: CDSE Process for Two Examples on Application of IPPD Through RDS System of Systems: CDSE Process for FCS FST Team in Phase I Derivative Program: F-18 C Conversion to F-18 E/G Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

FST Process Methodology for FCS Phase I Concept Development & Systems Engineering Methodology Incorporates FST Process Methodology for FCS Phase I Concept Development & Systems Engineering Methodology Incorporates IPPD Principles, QFD, Analysis, Engineering Simulation, Systems Engineering Tools, and Force-on. Force Simulation (This presentation does not reflect the current thinking of the FCS LSI) Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

The Full Spectrum Team(FST): One of Four Teams in FCS Phase I SBA/SMART Soldier The Full Spectrum Team(FST): One of Four Teams in FCS Phase I SBA/SMART Soldier Systems O&O Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu C 4 ISR FCS Weapons/ Platforms 2408 W-C 07 Robotics Deployment / Sustainment Working Closely With Government Labs CASA/CERT/PLMC A 0042

Network Centric System Design of a Lethal Brigade The FST Brigade is designed to Network Centric System Design of a Lethal Brigade The FST Brigade is designed to fight with precision fires and high lethality • Diverse, overlapping fires and sensor coverage at all echelons • Near and far fires with area and precision effects • Multiple layered sensor coverage Typical Vehicle Sensors EO/IR sensor/sight laser detectors glint detectors Command Vehicle Tethered UAV RSTA Vehicle Sensor systems Command Vehicle HQ External augmentation Brigade echelon Command Vehicle MM Radar Tethered UAV Command Vehicle NLOS BDE Air Defense MM Radar Scout Vehicle ARV Marsupial UGV NLOS BG Net. Fires Medium UAV RSTA Battle Group Marsupial RSTA Vehicle UGV Command Vehicle Scout Marsupial UGV Infantry Carrier Soldier Systems Small UAV Vehicle Command Vehicle omitted Net. Fires ARV NLOS Mortar Weapon systems Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu 9 ton variants Battle Group echelon RSTA Battle Unit ARV Stinger Blk. IIE Soldier HUMMWV SUV command vehicles Systems NLOS Mortar LOS/BLOS Assault Battle Unit echelon Vehicles Objective Crew Served Weapon ARV Common Missile Objective Crew Served Weapon CASA/CERT/PLMC External augmentation

Concept Development & Systems Engineering (CDSE) Process • Incorporates key aspects of modern systems Concept Development & Systems Engineering (CDSE) Process • Incorporates key aspects of modern systems engineering approaches, and lends itself to iteration – – Requirements Flowdown Engineering Trades / Analysis Force Effectiveness Modeling and Simulation Risk Mitigation • Allows full exploration of need identification and problem definition, concept development, and concept selection—prior to system definition and design • Facilitates group work and utilizes modern software based tools • Allows full incorporation of increasingly detailed simulationbased analyses and designs • Smoothly extends throughout engineering and manufacturing phases Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Integration of QFD, Morph and Pugh Products Into CDSE Process HOWs QFD 1 -4 Integration of QFD, Morph and Pugh Products Into CDSE Process HOWs QFD 1 -4 HOWs criteria alt. concepts Tech. Alternative Identification 1 st Option 2 nd Option Engine Type MFTF 3 Stage Mid-Tandem Fan 2 Stage Turbine Bypass Fan Pugh Evaluation Matrix Baseline No Fan Combustor Conventional RQL LPP Nozzle Conventional + Acoustic Liner Circulation Control Mixer Ejector Nozzle Hybrid Laminar Flow Control Aircraft Technologies None Morphological Matrices Weights QFD “Context” Rationale Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Multi Attribute Decision Methodology Subjective Evaluation (through expert opinion, surveys, etc. ) Best Alternative Preliminary CASA/CERT/PLMC

Full Spectrum Team FCS Concept Development & Systems Engineering (CDSE) Process 7 Recomposition Force Full Spectrum Team FCS Concept Development & Systems Engineering (CDSE) Process 7 Recomposition Force Effectiveness Simulations 3 Design Guidance n Organizational n Operational n Engineering Alternative 1 O&O 6 Force Concepts Alternatives 1 Pugh Force Concepts Selection Matrix 2 Guidance - QFD (2 -4) n Missions n Tasks n Functions n Capabilities Systems Capabilities Morph Matrices Selection of Consistent Sets of Systems and Technologies 5 Systems Set 1 Legend Products Decision Systems Concept IPT Technology IPT Dr. Daniel P. Schrage Requirements IPT Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu All IPTs Process is Parallel and Iterative 4 Concept 2 Technology / Characteristics 1 Concept Subsystems Characteristics Options Missions / Scenarios Technology Trees CASA/CERT/PLMC A 0031 t Decomposition Pugh Force Concepts Selection Matrix 1 Selected Force End Start Guidance - QFD 1 Iteration Concepts n AUTL n TRADOC Docs MOEs n MNS

t es B System Capabilities Determine Force Characteristics to Perform Functions Technologies System Capabilities t es B System Capabilities Determine Force Characteristics to Perform Functions Technologies System Capabilities How What CDSE ITERATION 2 Incorporate Four Detailed Mission Scenarios Candidate Concepts Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu How QFD 4 Co-Owned with Concepts IPT Commander Centric Functions AUTL Combat Tasks How What AUTL Missions How Requirements IPT Criteria / MOEs Commander Centric Warfare Functions AUTL Combat Tasks What AUTL Missions What National Imperatives / Army Vision Focus on Requirements Flowdown through QFD Morphological Matrix Select Technologies and Combine into Candidate Concepts Best Concepts Determined in Process That Trades Technologies, Concepts and Requirements CASA/CERT/PLMC

Representative FCS Trade Studies • Communications Trades – – Peer-to-Peer and Client-Server Islands and Representative FCS Trade Studies • Communications Trades – – Peer-to-Peer and Client-Server Islands and Backbones Frequency Bands and Bandwidth Qo. S (Latency, Availability, Bandwidth) • C 2 Trades – – Legacy, New, Organic, Joint Initiative and Control • Platform Trades – – – – Tracks and Wheels Weight Studies (16 t, 9 t, 6 t) Modularity and Commonality Studies Hybrid and Conventional Propulsion Turbine and Diesel Wheel and Body Motors Active and Passive Suspension • Force Trades – UAVs and UGVs – Manned and Unmanned – Mounted snd Dismounted – BLOS / NLOS / LOS Mix – Dr. Daniel P. Schrage BU Size and Composition Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu • Weapons Trades – – – Guns and Missiles 105 and 120 BLOS/LOS Precision and Area Fires • Sensor Trades – – Radar, EO/IR, and Ladar Systems (UAV, UGV, Mast, Tethered) On Board and Off Board Fusion ATR and Clutter (False Alarms) • Survivability Trades – – – Active and Passive Collective and Individual Links and Nodes • HMI Trades – – – Autonomy, Responsibility, Workload Commonality, Simplicity Motion and Maneuver • Logistics – – – OPTEMPO and Sustainment Deployment (Weights, Times, Pulses) Prognostics, Distribution, Log Support CASA/CERT/PLMC

The Trade Space is Defined by a Full Spectrum of Scenarios Environment Sensitivity analysis The Trade Space is Defined by a Full Spectrum of Scenarios Environment Sensitivity analysis will help drive to “The FCS Solution” pe rfo rm an ce ? Scenario 1 Solution W ha ti s th e in “The FCS Solution” Scenario 3 Solution Mission Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Potential FCS Solution Scenario 2 Solution Threat CASA/CERT/PLMC

Scenario Driven OMS/MP Development FST Scenarios: Forcing Function for Full Spectrum Force Development Bosnia Scenario Driven OMS/MP Development FST Scenarios: Forcing Function for Full Spectrum Force Development Bosnia Scenario Korean Desert Storm Scenario Chad Scenario Initial Force Concepts 1&2 Four Scenario Initial Specific OMSMPs OMS/MP Inputs Full Spectrum Force Concepts FST concept robustness is tested against a broad range of missions & scenarios which gain validity from extensive quantitative & qualitative wargaming & analysis Tabletop MAPEX Operational JANUS Examination Wargaming CASTFOREM Wargaming Scenario Weighting Force Concept Composite OMS/MP (Version 4. 1) (Scenario Specific Consolidation) Wargaming Feedback Force Concept Was Developed Iteratively & in Parallel With OMS/MP CASA/CERT/PLMC Refinements Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu

Evolution of FCS Force Concepts Concept 1 Concept 2 Heavy reliance on NLOS range Evolution of FCS Force Concepts Concept 1 Concept 2 Heavy reliance on NLOS range engmts / UAVs l FUE l Significantly more payload volume l Mostly 18 -ton vehicles l Peer-to-peer information architecture l l Based on Small Unit Operations comms l tech Baseline l New software services l Blending of Concept 1 and 2 --Robotics and NLOS engmts l 6 -ton ARVs, 9 -ton CVs, 16 -ton max vehicle weight 2012 FUE l Helo vertical envelopment with smaller vehicles l 16 ton limit for C-130 deployment on unimproved runways l Hybrid information architecture l Peer-to Peer with communication islands l Based on Small Unit Operations comms BLK I / BLK II technology l BLK I - Employ available weapons systems l New software services - Most vehicles manned 2008 FUE BLK I - 9 -ton vehicles become 16 ton 2013 FUE BLKl. IIBLK II – Employ advanced weapons systems - Many advanced robotic systems Dr. Daniel P. Schrage Georgia Institute of Technology l Same information and comms arch. as Baseline CASA/CERT/PLMC l Heavy reliance on robotic ground vehicles l More RSTA and assault Deployable by current rotary wing aircraft 2012 l Max vehicle weight 10 tons Client-server information architecture Evolutionary comms and software systems Atlanta, GA 30332 -0150 www. asdl. gatech. edu l

Concept Baseline Alternatives Summary Sensors Information Concept 2 Concept 1 • • Smaller Number Concept Baseline Alternatives Summary Sensors Information Concept 2 Concept 1 • • Smaller Number of UAVs Large Number of Modestly Capable Ground Sensors (ARVs) • • Larger Number of UAVs Small Number of Highly Capable Ground Sensors (RSTA Vehicle) • • Client Server Evolutionary Software • • Peer-to-Peer Distributed, Dynamic Deciders • Highly Automated Commander-Centric (Unit/Group) • Highly Automated Commander -Centric (Group/Brigade) Actors • Full Spectrum, but Weighted for the Red Zone Robotic ARV, DF, Netfires, NLOS Manned C 2, CV, and Infantry Carrier CH-47 Transportable (<10 tons) Many Dispersed 4, 6, and 9 Ton Vehicles (~650) • Full Spectrum, but Weighted for Beyond the Red Zone Robotic Netfires, Small UGV Manned C 2, Infantry Carrier, Direct Fire, RSTA and Short Range NLOS C-130 Transportable (<18 tons) • • Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu • • Common Chassis with Modules (~340) CASA/CERT/PLMC

Baseline 2012 Concept Network Centric Functional Overview Sensors Info System Soldier Organic UAVs, UGVs Baseline 2012 Concept Network Centric Functional Overview Sensors Info System Soldier Organic UAVs, UGVs (EO/IR, Fo. Pen, SAR, MTI) Organic Manned R&S with Tethered Sensors Aided Target Recognition Augmenting UAVs and Satellites Organic Multi-Layer Peer-to-Peer Coms Opportunistic Ground, UAV, and Satellite Links Integrated Software/Hardware Open Architecture Distributed Warfighter Services Deciders Brigade, Battle Group, Battle Unit Common Relevant Operating Picture Decision and Planning Aids Actors Net Fires Soldier System Armed Reconnaissance Vehicles 105 NLOS 120 mm Mortar NLOS Dr. Daniel P. Systems Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu 105 LOS / BLOS Infantry Carrier / C 2 / CV Precision and Area NLOS Fires Precision BLOS / LOS Weapons OCSW on all Combat Vehicles Mix of Manned and Unmanned Platforms Infantry / Soldier Systems Large Number of Stowed Kills CASA/CERT/PLMC

FCS Phase I Results • Talented team pulled together through a generic IPPD methodology FCS Phase I Results • Talented team pulled together through a generic IPPD methodology extended to address the ‘system of systems’ problem for FCS CDSE • An integrated set of simple tools proved useful for the first iteration through the process • Success of the Concept Development and Systems Engineering (CDSE) Process developed and utilized is summarized by the rankings by the government’s independent assessment team • Elements of the process are being continued by the Boeing-SAIC Lead System Integrator (LSI) through the current FCS Phase Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Future Combat System (FCS) Government Independent Assessment Team’s Phase 1 competitive scores (awarded Nov Future Combat System (FCS) Government Independent Assessment Team’s Phase 1 competitive scores (awarded Nov 2001) Full Gladiator Focus. Visio CONCEPT CATEGORY Spectru Boeing (Lockheed n (GDLS/ m Team / TRW) Raytheon) Deployment 1 st 2 nd (tie) Situational 1 st 4 th 3 rd (tie) Understanding Lethal Effects 1 st 2 nd (tie) Protection 1 st (tie) 4 th 1 st (tie) 2 nd Sustainability 1 st 2 nd (tie) 4 th Transition to New 1 st 4 th 2 nd 3 rd Mission OVERALL 1 st 4 th 2 nd 3 rd Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

F/A-18 Example Application • Link the appropriate aircraft sizing/synthesis and economic tools plus probabilistic F/A-18 Example Application • Link the appropriate aircraft sizing/synthesis and economic tools plus probabilistic methods to create testbed environment; model the F/A-18 C (using substantiation data for validation) • With F/A-18 E/F requirements (Ref. AIAA Paper 98 -4701) as drivers, look at relation of technology metrics on requirements mathematically Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Expanding Missions: The F/A-18 E/F Maritime Air Superiority F-14 D NATF Air Combat Fighter Expanding Missions: The F/A-18 E/F Maritime Air Superiority F-14 D NATF Air Combat Fighter Escort Recce Close Air Support Air Defense Suppression Day/ Night Attack F/A-18 A/B/C/D All Weather Attack A-6 F F/A-18 E/F Ref. Young, et. al. AIAA-98 -4701, 1998. How can such multi-role vehicles be examined as potential solutions for the war -fighter with respect to technologies, requirements, and design constraints ? Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Process The traditional process of identification of an overall objective to be optimized is Process The traditional process of identification of an overall objective to be optimized is replaced by the following process: 1) Using Response Surface Method to mathematically represent combined requirements-technology-configuration space 2) search for alternatives (configuration changes plus technology infusion) that satisfy requirements and constraints (TIES method) 3) simultaneously, optimize on desirements within this feasible space (continuous) or set (discrete) then, perform sensitivity studies to show the perturbation of the solution due to possible changes in requirements and design variables. Thus, the customer/decision maker has information with regards to the choice between tolerating a relaxation in requirements or accepting achievable performance levels Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

F/A-18 C Basic Geometry Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA F/A-18 C Basic Geometry Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Primary Mission- Fighter Escort Intermediate Thrust Climb 42, 550 ft Actual Modeled ( ) Primary Mission- Fighter Escort Intermediate Thrust Climb 42, 550 ft Actual Modeled ( ) Cruise at Optimum Mach and Altitude (39, 910 ft) (40, 000 ft) 41, 300 ft (37, 796 ft) 39, 300 ft (38, 904 ft) 38, 100 ft Reserves: 20 minutes Loiter at S. L. plus 5% of T/O Fuel Start & Taxi, Accelerate to Climb Speed 4. 6 minutes at Intermediate Thrust, SLS Combat at 10, 000 ft 2 minutes at Maximum Thrust Mach 1. 0 (missiles retained) Combat Radius =311 nmi Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Alternate Missions- Addressing Multi-role Capability • Requirements can include performance against a wide variety Alternate Missions- Addressing Multi-role Capability • Requirements can include performance against a wide variety of missions Metrics/Objectives Constraints D Responses • Vehicle sizing proceeds based on a primary mission and then fallout performance of the sized vehicle on alternate missions is computed and tracked Primary Mission Responses Alternative Mission Responses Example: Given a vehicle sized for Air Superiority (A-S) mission, compute the performance for Interdiction mission as A-S requirements change Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Constraints Requirements, Vehicle Chars. , or Technologies CASA/CERT/PLMC

Alternate Mission: Hi Hi Hi Actual Modeled ( ) Intermediate Thrust Climb Cruise at Alternate Mission: Hi Hi Hi Actual Modeled ( ) Intermediate Thrust Climb Cruise at Optimum Mach and Altitude 43, 200 ft (40, 000 ft) 38, 550 ft 40, 600 ft (37. 911 ft) (40, 000 ft) Reserves: 20 minutes Loiter at S. L. plus 5% of T/O Fuel Start & Taxi, Accelerate to Climb Speed 4. 6 minutes at Intermediate Thrust, SLS Combat at Best Altitude 5 minutes at Maximum Speed Mach 1. 0 (missiles retained) Combat Radius =505 nmi Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Correlation of Drag Polars for Varying Mach Numbers Altitude = 36, 089 ft Cl Correlation of Drag Polars for Varying Mach Numbers Altitude = 36, 089 ft Cl Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Propulsion Modeling F 404 -GE-402 Augmented Turbofan Engine • The F 404 -GE-402 is Propulsion Modeling F 404 -GE-402 Augmented Turbofan Engine • The F 404 -GE-402 is an increased performance derivative of the F 404 and is used in the F/A-18 C • Features a dual-spool mixed flow turbofan architecture, 3 X 7 X 1 X 1 turbomachinery configuration • F 404 Engine performance deck based on installed engine data for the F/A-18 C • Engine performance data source: “F/A-18 C Substantiating Performance Data with F 404 -GE 402 Engines” Report MDC 91 B 0290 Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu General Specifications: • Thrust: 17, 700 lb • SFC (max A/B): 1. 74 lbm/lbf-hr • SFC (IRP): 0. 81 lbm/lbf-hr • Airflow (SLS): 146 pps • Weight: 2, 282 lb • Length: 159 in • Diameter: 35 in CASA/CERT/PLMC

Weight Breakdown- Validation • Sizing/Synthesis Code Used: FLight OPtimization System (FLOPS) • F/A-18 C Weight Breakdown- Validation • Sizing/Synthesis Code Used: FLight OPtimization System (FLOPS) • F/A-18 C Baseline Modeled in FLOPS calibrated against actual substantiation data from manufacturer • Highly accurate model (errors in weights less than 1%) Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Economic Assumptions • MALCCA (Military Aircraft Life Cycle Cost Analysis) in-house code used to Economic Assumptions • MALCCA (Military Aircraft Life Cycle Cost Analysis) in-house code used to determine notional aircraft economics • Baseline File created starting with defaults based on the military aircraft assumptions (primarily sourced from F-15 and F-16 data) Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Wind Over Deck Recovery Wind Over Deck Launch Wind Over Deck Aircraft Touchdown Speed Wind Over Deck Recovery Wind Over Deck Launch Wind Over Deck Aircraft Touchdown Speed Wind Over Deck Arresting Gear Performance Aircraft Weight Wind Over Deck Cat Plus A/C Thrust Airspeed Required Speed • Aircraft Touchdown Speed = 1. 05 * Vapp • Airspeed Required = Calculated Liftoff Speed • Arresting Gear Performance Calculated at Limit Capacity Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Example Responses: Metrics/Objectives R 1 Gross Weight Probability of Survival Lethality O+S Acquisition Cost Example Responses: Metrics/Objectives R 1 Gross Weight Probability of Survival Lethality O+S Acquisition Cost R 2 R 3 R 4 R 5 Constraints DResponses/Desirements Responses and Top Level Requirements Approach Speed (constraint) TOFL (constraint) R 6 R 7 Req. 1 Range Req. 2 Req. 3 Payload PS Req. 4 Req. 5 Req. 6 Req. 7 tloiter turn rate f. W wt. W Req. 8 Mach T/W and W/S may belong in either the requirements or the responses section - depending on how the programs are set up Top Level Requirements This approach de-emphasizes the geometry of an aircraft, and instead focuses on the mission requirements. However, it does require a baseline aircraft configuration. Geometry and Technologies are fixed, while Requirements vary. Each vector of top level requirements maps to a specific mission. Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Requirement RSEs for Notional F/A-18 C Performance Takeoff Approach Landing Field Takeoff Field Wind Requirement RSEs for Notional F/A-18 C Performance Takeoff Approach Landing Field Takeoff Field Wind Over Length Deck Speed (ft) (ft/s) Takeoff Gross Operation & Weight Support Cost (lbs) (mil. $/yr) First Unit Cost (mil. $) Life Cycle Cost cents #AC * hr * lb RDT&E Cost (mil. $) +40% -5% +10% 0 500 1000 -5% +10% -5% +40% -10% Ult. Load Fact. Combat Mach # Radius Area Thrust Payload (lbs) +30% 0 2244 4488 -15% 0% Specific # Aux. Tanks Fuel Consumption (lbs) 500 1000 0 stealth (lbs) Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC 4897. 278 4380. 113 0. 866574 3777. 587 0. 792245 72. 927 0. 749297 53. 187 62. 87922 5885. 437 5330. 668 55799. 5 4841. 269 31626. 8 42958. 04 36214. 7 23727. 3 45. 0536 Empty Weight (lbs) -7. 06871 42. 98329 -0. 99871 9345 -39. 8082 4184. 198 5776 2708 3137 4088. 045 182. 8 128. 9 152. 8745 16241 9072 11844. 52 4. 891 2. 732 3. 746093 1014. 9 510. 8 740. 7152 1787. 6 1364. 336 40. 3 1062. 1 37. 03584 1. 088 33. 67 0. 666 0. 841592 137. 2 95. 89077 68. 1 Landing Wind Over Deck (ft/s) 30061. 56 Combat Turn Radius (ft) Economics Weights 17. 36432 Alternate Combat Specific Combat Wing Loading Thrust/Weight Wing Span Mission Range Excess Power Turn Rate (lb/ft 2) (ft) (nm) (deg/s) (ft/s) Capabilities

Requirements Exploration: F/A-18 C Design Contours Response contours may be set here Horiz Vert Requirements Exploration: F/A-18 C Design Contours Response contours may be set here Horiz Vert Factor Radius ULF Cmb. Mach DPayld Thrust Area DStealth Auxtnk SFC Response O&S TOGW LDWOD TOWOD Vapp Ps Alt. Rng Current X Grid Density Update Mode -0. 8888 20 x 20 Immediate 0 0 -1 -0. 8888 -0. 857 -1 -1 1 Contour Current Y Lo Limit Hi Limit 5500 5031. 4066 ? 5500 40000 37137. 19 ? 40000 15 4. 8129793 ? 15 0 -20. 93512 ? 0 153 152. 42056 ? 153 695 700. 21755 695 ? 920 1238. 6386 920 ? 21420 Slide bars control variable values Constraints are set here Vapp Takeoff Wind Over Deck Thrust (lbs. ) Ps Landing Wind Over Deck TOGW 14535 360 Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Area (ft^2) White area indicates available design space, while filled areas indicate areas which violate set constraints CASA/CERT/PLMC 520

Effects of Increase in Combat Radius Req. Vapp 21, 420 TOWOD Thrust LDWOD Ps Effects of Increase in Combat Radius Req. Vapp 21, 420 TOWOD Thrust LDWOD Ps TOGW Decreasing Feasible Space 14, 535 380 Area 520 21, 420 Vapp TOWOD Thrust LDWOD Ps Increasing Combat Radius Reqmt. TOGW 14, 535 380 Area 520 21, 420 Vapp TOWOD Thrust LDWOD Ps TOGW 14, 535 380 Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Area 520 CASA/CERT/PLMC

Horiz Vert Factor Current X Radius 0. 964 ULF Grid Density Update Mode 20 Horiz Vert Factor Current X Radius 0. 964 ULF Grid Density Update Mode 20 x 20 Immediate 0. 71 Cmb. Mach 0 DPayld -1 Thrust 0. 88888 Area 0. 857 DStealth -1 Auxtnk -1 SFC 0. 3333 Response Contour O&S Current Y Lo Limit Hi Limit ? 5130 TOWOD ? 47224. 344 ? ? 30 LDWOD 5475. 7833 45000 TOGW 26. 563468 ? 30 15 10828. 741 ? ? 4. 0987387 ? ? 807. 60615 780 ? 1540 Alt. Rng 151 780 Ps 15 ? 3. 8115 t_Rate ? 150. 2058 12656. 5 t_Radius 13. 613377 151 Vapp 1545. 1224 1540 Exploring the Space: Capturing the F/A-18 E/F ! ? 21420 TOWOD Vapp Ps Alternate Range Turn Radius Turn Rate TOGW Thrust (lbs. ) O&S 14535 380 Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu Area (ft^2) CASA/CERT/PLMC 520

RDS Example: TOGW Req. for Notional F/A-18 (1) Scenario 1: Conservative tech. improvements gives RDS Example: TOGW Req. for Notional F/A-18 (1) Scenario 1: Conservative tech. improvements gives low confidence of meeting requirement k_CDo k_CDi k_Fus. Wt k_HTWt Achieved TOGW k_Wing. Wt k_VTWt Probability of Satisfying TOGW Req. =~1% Anticipated TOGW Req. Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

RDS Example: TOGW Req. for Notional F/A-18 (2) Scenario 2: Aggressive tech. improvements gives RDS Example: TOGW Req. for Notional F/A-18 (2) Scenario 2: Aggressive tech. improvements gives higher confidence of meeting requirement k_CDo k_Fus. Wt k_CDi k_Wing. Wt k_HTWt k_VTWt Achieved TOGW Probability of Satisfying TOGW Req. =~45% Anticipated TOGW Req. 0 Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

RDS Example: O&S $ as an Anticipated Requirement (1) Scenario 1: Conservative tech. improvements RDS Example: O&S $ as an Anticipated Requirement (1) Scenario 1: Conservative tech. improvements gives low confidence of meeting requirement k_CDo k_CDi k_Wing. Wt k_Fus. Wt k_HTWt k_$O&S P(Achieved-Anticipated) Achieved $O&S Probability of Satisfying $O&S Req. =~2% Anticipated $O&S Req. 0 Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Example: $O&S as an Anticipated Requirement (2) Scenario 2: Aggressive tech. improvements gives higher Example: $O&S as an Anticipated Requirement (2) Scenario 2: Aggressive tech. improvements gives higher confidence of meeting requirement k_CDo k_Fus. Wt k_CDi k_Wing. Wt k_HTWt k_$O&S P(Achieved-Anticipated) Achieved $O&S Probability of Satisfying $O&S Req. =~50% Anticipated $O&S Req. Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC

Summary and Conclusions • Systems Engineering has its roots in Aerospace • Modern Systems Summary and Conclusions • Systems Engineering has its roots in Aerospace • Modern Systems Engineering must reflect the Quality Revolution • The Five Lean Principles should serve as guiding principles for a Modern Systems Engineering Approach • Integrated Product and Process Development (IPPD) required in the Fuzzy Front End to Establish Value for subsequent principle implementation: Value Stream, Process Flow, Customer Pull, and Perfection • Georgia Tech has developed an IPPD through Robust Design Simulation (RDS) environment that allows a Probabilistic Approach for the Fuzzy Front End • The transition of the IPPD through RDS to a Virtual Stochastic Life Cycle Design Environment is necessary for full implementation of the Five Lean Guiding Principles Dr. Daniel P. Schrage Georgia Institute of Technology Atlanta, GA 30332 -0150 www. asdl. gatech. edu CASA/CERT/PLMC