Mohammad Khalessi, Ph.D. CEO/President PredictionProbe, Inc.

Slides:



Advertisements
Similar presentations
Five to Ten Year Vision for CBM by: John S. Mitchell for: ATP Fall Meeting -- Condition Based Maintenance Workshop November 17, 1998, Atlanta Georgia.
Advertisements

Assessing Uncertainty when Predicting Extreme Flood Processes.
Design of Experiments Lecture I
Mission Success Starts with Safety The Similarities and Differences of Reliability Engineering and Probabilistic Risk Assessment RAMS VII Workshop November.
DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION Copyright 2010 Phoenix Integration, Inc. All rights reserved. Grant Soremekun Business.
February Offerred by: C.E. Brockway Brockway Engineering Jim Brannon Leonard Rice Engineers, Inc John Koreny HDR Inc Willem Schreuder Principia.
Supply Chain Logistics Management
Probabilistic Analysis using FEA A. Petrella. What is Probabilistic Analysis ‣ All input parameters have some uncertainty ‣ What is the uncertainty in.
Structural Reliability Analysis – Basics
GoldSim 2006 User Conference Slide 1 Vancouver, B.C. The Submodel Element.
©GoldSim Technology Group LLC., 2004 Probabilistic Simulation “Uncertainty is a sign of humility, and humility is just the ability or the willingness to.
19 Linear Programming CHAPTER
University of Minho School of Engineering Territory, Environment and Construction Centre (C-TAC), DEC Uma Escola a Reinventar o Futuro – Semana da Escola.
SOFTWARE PROJECT MANAGEMENT Project Quality Management Dr. Ahmet TÜMAY, PMP.
Advanced Manufacturing Laboratory Department of Industrial Engineering Sharif University of Technology Session #22.
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 7-1 Chapter 7 Confidence Interval Estimation Statistics for Managers.
8/27/20151NeST Controlled. 2 Communication Transportation Education Banking Home Applications.
CURRENT RESEARCH AND INDUSTRIAL APPLICATIONS OF INTEGRATED SRA AND QRA MODELS Philip Smedley.
Assessment of Model Development Techniques and Evaluation Methods for Binary Classification in the Credit Industry DSI Conference Jennifer Lewis Priestley.
Don Von Dollen Senior Program Manager, Data Integration & Communications Grid Interop December 4, 2012 A Utility Standards and Technology Adoption Framework.
SynGenics Corporation 72 E Granville Road Worthington OH ©2003 SynGenics Corporation. All rights reserved. The Use.
VTT-STUK assessment method for safety evaluation of safety-critical computer based systems - application in BE-SECBS project.
CRESCENDO Full virtuality in design and product development within the extended enterprise Naples, 28 Nov
WHAT IS SYSTEM SAFETY? The field of safety analysis in which systems are evaluated using a number of different techniques to improve safety. There are.
GOLD Guaranteed Operation and Low DMC SEAMLESS AIRCRAFT HEALTH MANAGEMENT FOR A PERMANENT SERVICEABLE FLEET Birmingham (UK) December 05, 2007.
Probabilistic Mechanism Analysis. Outline Uncertainty in mechanisms Why consider uncertainty Basics of uncertainty Probabilistic mechanism analysis Examples.
Paul E. Chiodo Deployment Director, Lean Six Sigma Certified Lean Six Sigma Master Black Belt US Army Armament Research, Development & Engineering Center.
Application of the Direct Optimized Probabilistic Calculation Martin Krejsa Department of Structural Mechanics Faculty of Civil Engineering VSB - Technical.
Chapter 8 Managing Project Risk Copyright 2012 John Wiley & Sons, Inc. 8-1.
NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy operated by the Alliance for Sustainable.
Planning and Analysis Tools to Evaluate Distribution Automation Implementation and Benefits Anil Pahwa Kansas State University Power Systems Conference.
FAULT TREE ANALYSIS (FTA). QUANTITATIVE RISK ANALYSIS Some of the commonly used quantitative risk assessment methods are; 1.Fault tree analysis (FTA)
Industry & Research: Issues, needs and conclusions from the US IMPACT Investigation of Extreme Flood Processes & Uncertainty Workshop at HR Wallingford,
National Aeronautics and Space Administration From Determinism to “Probabilism” Changing our mindsets, or why PTC isn’t an easy sell - yet.
PRIVÉ ET CONFIDENTIEL © Bombardier Inc. ou ses filiales. Tous droits réservés. SMART TESTING BOMBARDIER THOUGHTS FAA Bombardier Workshop Montreal
PRIVÉ ET CONFIDENTIEL © Bombardier Inc. ou ses filiales. Tous droits réservés. PROBABILISTIC APPROACHES BOMBARDIER THOUGHTS FAA Workshop Montreal
7. Reliability based design Objectives Learn formulation of reliability design problem. Understand difference between reliability-based design and deterministic.
Predicting Earthquakes By Lois Desplat. Why Predict Earthquakes?  To minimize the loss of life and property.  Unfortunately, current techniques do not.
Copyright  2003 by Dr. Gallimore, Wright State University Department of Biomedical, Industrial Engineering & Human Factors Engineering Human Factors Research.
Jennifer Lewis Priestley Presentation of “Assessment of Evaluation Methods for Prediction and Classification of Consumer Risk in the Credit Industry” co-authored.
BSBPMG504A Manage Project Costs 7.1 Estimate Costs Adapted from PMBOK 4 th Edition InitiationPlanning ExecutionClose Monitor Control The process of developing.
5-1 ANSYS, Inc. Proprietary © 2009 ANSYS, Inc. All rights reserved. May 28, 2009 Inventory # Chapter 5 Six Sigma.
Selective Overview of R&D to Improve Energy Simulation Philip Haves LBNL CPUC Workshop: Energy Modeling Tools and their Applications in Energy Efficiency.
Machine Design Under Uncertainty. Outline Uncertainty in mechanical components Why consider uncertainty Basics of uncertainty Uncertainty analysis for.
I2 U Intelligent Supply Chain Management Course Module Seven: Inventory Planning.
Reservoir Uncertainty Assessment Using Machine Learning Techniques Authors: Jincong He Department of Energy Resources Engineering AbstractIntroduction.
“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Sensitivity and Importance Analysis Charles Yoe
Page 1 of 14 Modern RAMI Method Capabilities ARIES 2011 Quarter #2 Review July, 2011; Gaithersburg, Maryland Tom Weaver Counter CBRNE DEW Platform.
Advanced Manufacturing Laboratory Department of Industrial Engineering Sharif University of Technology Session #14.
RLV Reliability Analysis Guidelines Terry Hardy AST-300/Systems Engineering and Training Division October 26, 2004.
Conference on Quality in Space & Defense Industries CQSDI ‘08 Probabilistic Technology Panel: What Is Probabilistic Technology? Mohammad Khalessi, Ph.D.
Using Modelling to Address Problems Scientific Enquiry in Biology and the Environmental Sciences Modelling Session 2.
Uncertainty and Reliability Analysis D Nagesh Kumar, IISc Water Resources Planning and Management: M6L2 Stochastic Optimization.
Structural & Multidisciplinary Optimization Group Deciding How Conservative A Designer Should Be: Simulating Future Tests and Redesign Nathaniel Price.
“ Building Strong “ Delivering Integrated, Sustainable, Water Resources Solutions Uncertainty & Variability Charles Yoe, Ph.D.
EKT 314/4 WEEK 2 : CHAPTER 1 INTRODUCTION TO EI ELECTRONIC INSTRUMENTATION.
Introduction It had its early roots in World War II and is flourishing in business and industry with the aid of computer.
Presented by: Kumar Magi. ( 2MM07EC016 ). Contents Introduction Definition Sensor & Its Evolution Sensor Principle Multi Sensor Fusion & Integration Application.
Probabilistic Slope Stability Analysis with the
Simulation Modelling A Tool to Inform and Support Decisions In Iron Ore Mining Dr Steven Richardson.
P5 : Advanced Performance Management. B1: External Influences on Organisational Performance B1. Changing business environment B2. Impact of external factors.
Using Data Analytics to Support Knowledge Based Weather Decision Support Systems in the ATM Don Berchoff, VP for Advanced Weather Programs FPAW Summer.
Project Management Institute
OPERATIONS RESEARCH.
Project COMP10: Designing for Blade Aeromechanical Integrity
CPM, PERT & Schedule Risk Analysis in Construction
Probabilistic Methods: Theory and Application to Human Anatomy
Robust and Reliability Based Optimization using
A New Concept for Laboratory Quality Management Systems
Optimization under Uncertainty
Presentation transcript:

Mohammad Khalessi, Ph.D. CEO/President PredictionProbe, Inc. Conference on Quality in Space & Defense Industries CQSDI ‘08 Probabilistic Technology Panel: What Is Probabilistic Technology? Mohammad Khalessi, Ph.D. CEO/President PredictionProbe, Inc.

Probabilistic Technology * 07/16/96 Probabilistic Technology Y1, Y1, … Probabilistic Technology is a set of advanced predictive methods that allow for integration of uncertainties into process models and evaluation of the effects Input X1, X2, …. PROCESS Y = f (X1, X2,…) Output Y1, Y2, … Step 1 Step 3 Step 4 Step 2 l Utilizes physics laws, process rules, or empirical modeling techniques to construct process/output models Utilizes probability law to construct statistical models for Input Variables  2007, PredictionProbe, Inc. All rights reserved. * 9 17

Probabilistic Technology Optimizes Design, Performance, Number of Tests and More Probabilistic Technology provides 3 metrics to quantitatively evaluate design early in the decision process when no data is available 1. Most-Probable-Points Safety control systems Certification tests Reliability demonstration tests Critical combination of parameters Most likely failure points Many more Performance level = C1 Performance level = C2 2. Probability Information Reliability, risks, failure prob. Critical failure modes ID Performance range Most-likely performance value Safety-factor calibration Many more 3. Process Sensitivity Measures Key process variables & uncertainties Guidelines to develop test plans Guidelines for inspection & repair planning Guidelines to develop improvement plans Guidelines to develop control plans Guidelines to develop monitoring plans Many more  2007, PredictionProbe, Inc. All rights reserved.

Probabilistic Technology Allows for Safer and Lighter Designs Uncertainties significantly impact the prediction accuracy. Probabilistic Technology can accurately identify the failure location and the magnitude of failure probability. Press COV = 10% Axial Load COV=5% Failure Prob. = 1.4% Press COV = 5% Axial Load COV=20% Failure Prob. = 3.5% Press COV = 5% Axial Load COV=5% Failure Prob. = 0.7% Finite element model of a fuel tank  2007, PredictionProbe, Inc. All rights reserved.

Probabilistic Technology Eliminates or Minimizes Costly Changes * 07/16/96 Probabilistic Technology Eliminates or Minimizes Costly Changes  2007, PredictionProbe, Inc. All rights reserved. * 57 65