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

Evolving the Army’s PT Culture Change “Background”  1988 Identified the Emerging Value of Probabilistic Technology  1993 Probabilistic Technology research initiated  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”.  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

OVDMAIC/DMALCDC/I PT-Enhanced DFLSS Influencing the Product Life Cycle Early, Upfront Investment in Probabilistic Technology: Drives Identification & Elimination of Failure Mechanisms Prioritizes Investment Focuses Design and Process Approach Yields “Better, Cheaper, and Faster”

Integration of Probabilistic Technology with DFLSS 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 Army Plan PT for

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: I 2 DOV & CDOV Process and Axiomatic Design EM Gun system platform demonstration project

“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 I 2 DOV 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

PT Principles, Tools & Products for TRL 2-4 Maturity Achievement in Early Tech Base MPP Probability Sensitivity Analyzing Results Variable Models (force, time, etc.) Process Models (stress, life, etc.) Predictive Models g=(all. Resp.)-(Est. Resp.) Probabilistic Analysis FORM SORM SM ISM RSM MVBM System Definition & Data Gathering PL PH System Subsys. K Subsys. K-1 Subsys. K-2 Subsys. 2 Subsys. 1 Comp. JComp. J-1Comp. 2Comp. 1 Notional System c: Define safe and failure domains Safe Domain x Mean Point x2x2 x1x1 Failure Domain g4g4 g3g3 g1g1 g2g2 M&S Bayesian Physics Probabilistic Analyses 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 Innovation & Conceptual Design Approach

Principles, Tools & their Products for RMS TRL 5-8 Maturity Achievement 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 Performa nce level = C1 Products of Tools IMPACT of Tools Most probable points 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

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

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

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

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