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Conference on Quality in Space and Defense Industries

Conference on Quality in Space and Defense Industries. Conference on Quality in Space and Defense Industries 2008. Probabilistic Technology The Army Culture Change Program . Robert J. Kuper Certified, Lean Six Sigma Black Belt Dean, Reliability Engineering Competency

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Conference on Quality in Space and Defense Industries

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  1. Conference on Quality in Space and Defense Industries Conference on Quality in Space and Defense Industries 2008 Probabilistic Technology The Army Culture Change Program Robert J. Kuper Certified, Lean Six Sigma Black Belt Dean, Reliability Engineering Competency Program Manager, Reliability for the Future Force

  2. Evolving the Army’s PT Culture Change “Background” • 1988 Identified the Emerging Value of Probabilistic Technology • 1993 Probabilistic Technology research initiated • 1994-1996 Technology Demonstrated in Tech Base • Won National Award – “First Insensitive Munitions Container Design” – • Design Process Enhancement – A Real Culture Change - A New Paradigm for the Design Process “Physics-based Probabilistic M&S from Conceptual Design thru Verification & Validation • 2003 Initiated General Application type Training in PT • 2004 Re-energized the PT thrust – Congressional Interest Program • 2005 Demo T&E cost reduction via adv’d PT M&S – “Black Powder”. • 2005-2006 XM982 Characterized internal ballistic loading profiles on complex MEMS IMU components • 2006 Solved Mortar Fin cracking problems PT-Physics-based analysis • 2006 Demonstrated PT as value-added R&D Design tool “APOBS” • 2006 Developed “Probabilistic Lean Six Sigma” • 2007 Probabilistic Technology Community – National Agenda for Enhanced Competitiveness • 2007 Initiated PT LC Enhancements to Tools/Processes

  3. PT-Enhanced DFLSS Influencing the Product Life Cycle C/I D O V DMAIC/DMALC Early, Upfront Investment in Probabilistic Technology: Drives Identification & Elimination of Failure Mechanisms Prioritizes Investment Focuses Design and Process Approach Yields “Better, Cheaper, and Faster”

  4. Integration of Probabilistic Technology with DFLSS Army Plan for PT Critical Role for Probabilistic Technology: “Enhancing Decision-making structures across the LC • Integration with DFLSS, Program Mgt & System Engineering • DFLSS built into Product Development Process (PDP) • PT Becomes a Key Component of LSS – LC Process Focus • PT- Enhanced DFLSS: Innovation and Conceptual Design – “Rapid Innovation” • PT- Enhanced DFLSS: Robust Design, Reliability-Based Design Optimization, Axiomatic Design • PT- Enhanced DMAIC/DMALC: Process and Product Improvement Integration

  5. Technology Base Reliability Enhancement Thrust Areas • MEMS Critical Component Reliability Enhancement Initiative • Embedded PT on a SMARTChip • Composite Technology Maturation & Design for Ultra-Reliability & Service Life • Probabilistic, Physics-based Integrated M&S Architecture • “Rapid Innovation” -Tech Base Processes, Tools, Methods & Best Practices Initiative: Integration of world experts BOK, state of the art tools, methods and processes to provide a world class tech base system. • Advanced Physics-based tools • Seamless Integration of Stochastic/Probabilistic Methods • World class Optimization tools and methods • Phase/Gate: I2DOV & CDOV Process and Axiomatic Design • EM Gun system platform demonstration project

  6. “Rapid Innovation” • Tech Base Processes, Tools, Methods & Best Practices Initiative to develop World Class Technology Maturation System • Addressing actions by the Assistant Secretary of the Army for Acquisition, Logistics & Technology. Providing Probabilistic, Physics-based tools and advanced process management of the tech base • Supported by World Experts: • Dr. Khalessi – Probabilistic Physics-based Tools, Methods; Uncertainty Quantification (UQ); Quantitative Risk; Optimization. • Dr. Skip Creveling – DFLSS I2DOV and CDOV processes • Dr. Basem Haik – Axiomatic Design • NASA HQ and Centers • ARDEC LSS Deployment Director: Paul Chiodo • APO Lead: Bob Kuper • Deliverables: DOD Standard and Guidebook for Technologists Implementation

  7. PT Principles, Tools & Products for TRL 2-4 Maturity Achievement in Early Tech Base x1 Safe Domain g1 g2 g3 PL 1 2 4 5 6 Analyzing Results g4 Failure Domain Variable Models (force, time, etc.) • Probabilistic • Analysis • FORM • SORM • SM • ISM • RSM • MVBM System x2 System Definition & Data Gathering x MPP Probability Predictive Models g=(all. Resp.)-(Est. Resp.) Mean Point PH 3 Subsys. 1 Subsys. 2 Subsys. K-2 Subsys. K-1 Subsys. K Process Models (stress, life, etc.) Sensitivity c: Define safe and failure domains Comp. 1 Comp. 2 Comp. J-1 Comp. J Innovation & Conceptual Design Approach • Results of M&S, Advanced Physics Tools • Concepts & Technology emerge • Bayesian Approaches; Prediction • Model concepts • Concepts Simulated in war fight • Derive Performance Reqts • Apply Probabilistic Physics in Notional applications • Determine RMS Drivers • Determine Limit state functions • Early KPP evolution • LC Cost Modeling/implications Notional System M&S Bayesian Physics Probabilistic Analyses

  8. Principles, Tools & their Productsfor RMS TRL 5-8 Maturity Achievement Performance level = C1 • TRLs 5-8: Framework for identifying RMS Drivers – defined Operational Environments, imposed stresses, desired performance, define reqts for RMS • Best Practices for component/technology research begin with Advanced Physics-based Probabilistic and multi-physics M&S. • Tools: • Finite Element Analyses • Computational Fluid Dynamics • Dynamic Simulations • Multi-Body Physics • Thermal and Fatigue Analyses • Probabilistic Analyses • Reliability/RMS Analytics Products of Tools Most probable points IMPACT of Tools • Identify Most Likely Failure Modes/Mechansims • Determine Uncertainty/Risk in ALL parameters • Model the multi-physics of all Performance • Quantitative Risk Assessments of all failure prob. • Understand Sensitivities of all key parameters • Quantitative TRL maturity measures • “Design-in”better inherent performance & RMS

  9. Related Initiatives - Composite Materials and Structures - • Objective: Developing Reliability-Based Design Optimization system for all Composites Technology Programs. • Phase I SBIR – transitioning to Phase II Fast Track Program in FY08. • Understand, characterize and micromechanically model these damage modes based on rigorous mechanics and predictive framework. • Interfacial fiber/matrix de-bonding • Inter-laminar penny-shaped delamination micro-cracks, • Matrix micro-cracking (in-plane or transverse) • Fiber breaking, buckling, and crushing • Failure models will be used in Phase 2 and 3 to develop a Probabilistic, Physics-based Design Optimization • Key Partnerships • Technical Excellence Initiative & Pilot Programs with NASA on Return to Moon Heavy Lift Vehicle (ARES). • Working with World Experts at PredictionProbe, Inc., UCLA, NASA, and others • Pursuing partnerships and leveraging with Homeland Security and Army Corps of Engineers

  10. SmartChip™ Technology Provides For Highly Reliable Diagnostics & PrognosticsDecision-making SmartChip™ Updates Reliability Model at A , based on sensor data SmartChip™ Recommends Part Replacement at B & Upgrades Reliability upon Part Replacement Reliability, R(t) Minimum AcceptableReliability Planned Repairs by SmartChip™ Reliability Without Part Replacement No Failure Observed B A Time (t) SmartChip™ Technology Allows for the Evaluation of System Reliability on The Fly • SmartChip™ Technology maximizes system availability by providing for properly timed/planned downtime and eliminating unexpected failures

  11. Related Initiatives- Probabilistic M&S - Structural FEA ANSYS Solid Modeling PRO-E Propulsion IBHVG Aero-ballistics PRODAS Integrated Physics Environment for Armaments Knowledgebase Notebook Eqns. and Rules of Thumb Dynamic M&S LS-DYNA Intermediate Calculations & Simulations Matlab, Excel Probabilistic Environment Distributed Simulation Environment Effectiveness Environment Business Process Environment Cost Environment Logistics Environment Integrated Probabilistic Computational Environment Requirements Environment Manufacturing Environment Reliability, Safety, Optimization & Risk Environment Initial Focus “Physics Environment”

  12. Probabilistic Technology Enhancement to DFLSS Probabilistic Technology Certification Program – Independent 3rd party ASQ LSS Infrastructure Implementation In Army Programs Lean Six Sigma Deployment Strategy Design For Lean Six Sigma DFLSS Integrating PT Awareness ARMY Probabilistic Technology BOK, Training & Sustaining System Prob. Technology Standards ASQ/PTC Guidelines Feedback & Success Stories 4 Level Probabilistic Technology Certification Program BOK

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