Relex Reliability Software “the intuitive solution Relex Reliability Software “the intuitive solution!” Relex Software Corporation 1

What is Relex? A Powerful Reliability Software Tool… performs efficient reliability analysis uses multiple analysis techniques provides advanced features

Relex Is Uniquely Qualified Reliability Engineering Experience Commercial Military Software Development Experience

Relex Reliability Software “the intuitive solution Relex Reliability Software “the intuitive solution!” Relex Software Corporation

Introduction to Reliability Prediction

Reliability Predictions What is a Reliability Prediction? Calculation of failure rate (MTBF) How is it Calculated? Based on established reliability model

Sample Relex Reliability Prediction calculation results Reliability Measures Failure Rate () Mean Time Between Failures (MTBF) Reliability Availability Sample Relex Reliability Prediction calculation results

Failure Rate Defined As: Units: Rate of Occurrence of Failures Number of Failure in Specified Time Period Units: Failures per Million Hours Failures per Billion Hours (FIT Rate)

MTBF Defined As: Units: Mean Time Between Failures Number of Hours to Pass Before a Failure Occurs Inverse of Failure Rate* Units: Typically expressed in Hours *Constant Failure Rate Systems

Reliability Defined As: Units: The probability that an item will perform a required function without failure under stated conditions for a stated period of time Units: Probability Value (0-1)

Availability Defined As: Units: The probability that an item is in an operable state at any time Units: Probability Value (0-1)

Reliability “Summary” Failure Rate -- number of failures in time MTBF -- average time between failures Reliability -- takes into account mission time Availability -- accounts for repairs (MTTR) and downtime

The Bathtub Curve and Reliability

The Bathtub Curve Represents failure rate tendencies for the lifespan of an item Failure rate varies in different phases of life

Three Phases of Life Infant Mortality Region Wear-Out Region Constant Failure Rate Region

Bathtub Curve Graph of Failure Rate vs. Time Considers three phases of life Represents lifespan of item (i.e. 15 years for a car)

Bathtub Curve –Illustration– Infant Mortality Wear Out Constant Failure Rate Failure Rate Time 17

Reliability Models

Influences to reliability / Model-parameters Production maturity Design & construction Storage conditions Production factors Transport conditions Material- selection Electronic component Application- temperature Operating conditions Application factors electrical stress mechanical stress Climatic environment

Relex Prediction Models MIL-HDBK-217 (FN1, FN2 ) Telcordia (Telcordia 1, Bellcore 4,5,6) Prism: RAC model (Process Grades, Bayesian) NSWC-98/LE1: mechanical model HRD5: British telecomm model CNET 93: French telecomm model 299B: Chinese standard Relex allows the user to use multiple models within one project and use functionality across models (i.e. use Prism process grade factors on 217 predicted failure rates, use Bellcore methods on 217 calculations, etc.)

MIL-HDBK-217 Original standard for reliability Reliability math models electronic devices Used commercially & in the defense industry Currently at Revision F Notice 2

Parts Count A section of MIL-HDBK-217 Provides simpler reliability math Typical Uses: Used early in the design process Used to acquire a rough estimate of reliability

Telcordia (Bellcore) Originally developed at AT&T Bell Labs “Modified” MIL-HDBK-217 equations New equations represented what their equipment was experiencing in the field

Telcordia (Bellcore) (cont.) New model with new feature Account for “real data” Burn-in, Field, Laboratory testing data Popular standard for commercial companies

Mechanical Based on the Handbook of Reliability Prediction Procedures for Mechanical Equipment, NSWC-98/LE1 Provides models for various types of mechanical devices including springs, bearings, seals, etc. New and unique standard

CNET & HRD5 Used in Europe Reliability models for telecommunications Current Versions: HRD - 5 CNET - 93

Bellcore vs. 217 Recognition & Acceptance Concentration Calculations & Equations Consideration of Test Data Multiplier Parts Environments Quality Levels

Accuracy of MTBF Assessments Stage I: Parts count method, assuming constant failure rates Stage II: Variation of failure rates according to part families Stage III: Taking into account of operational parameters Stage IV: Consideration of failure modes, time influences, different failure distribution for each part, etc. Accuracy Time spent for the analysis

PRISM Reliability Model Developed by the Reliability Analysis Center (RAC) Accounts for the effect of process related variability on system failure rate Inherent failure rate based on base failure rate and environmental conditions (RAC Rates model) Failure rate may then be modified by: Process Grade Factors, and/or Bayesian Analysis, and/or Predecessor Data

PRISM Methodology Operational Profile, Environmental and Electrical Stresses Process Assessments RAC Component Models Test Data RAC Failure Rate Databases System Reliability Assessment Model Bayesian Data Combination Historical Data on Similar Systems System Reliability Estimate Software Model

Primary Causes of Failure (Nominal Values)

PRISM Process Grade Factor Types Design Manufacturing Parts Quality System Management CND (Can Not Duplicate) Induced Wearout Growth Infant Mortality

Other PRISM Adjustments Bayesian Uses test and field data to enhance predicted failure rate Predecessor Uses previous history data to further refine predicted failure rate

PRISM Note Although PRISM contains RAC Rate models for many part types, it does not include the following: Rotating devices Relays Switching devices Tubes Connections Lasers Miscellaneous parts Relex can solve this problem by allowing the user to apply PRISM concepts (Process Grade, Bayesian, Predecessor) to a failure rate calculated by all other models.