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Exploratory Data Analysis Approaches to Reliability: Some New Directions. Chris McCollin Cornel Bunea Maria Ramalhoto. Chris McCollin The Nottingham Trent University. Involved in Reliability since 1976 Worked as a reliability engineer for 3 major aerospace companies

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exploratory data analysis approaches to reliability some new directions

Exploratory Data Analysis Approaches to Reliability: Some New Directions

Chris McCollin

Cornel Bunea

Maria Ramalhoto

slide2

Chris McCollinThe Nottingham Trent University

  • Involved in Reliability since 1976
  • Worked as a reliability engineer for 3 major aerospace companies
  • Consultancies/Training: Nuclear, Rail, Commercial
  • Involved with Q&RE paper for Engineering Council for last 8 years
  • RSS representative for BSI
  • ENBIS Reliability Website coordinator
areas of common sme problems
Areas of Common SME Problems
  • Effect of short-term management outlook on reliability
  • Lack of time, manpower for analysis and improvement
  • Lack of expertise, resources
  • OEM dependency, meeting requirements only
  • Lack of knowledge retention
problem solving requirements
Problem Solving Requirements
  • Structured approach, easy to use, computer/web based
  • Developing hypotheses to answer (inter-related) problems over life cycle of a product(s)
  • Using past/present information across diverse databases
  • Central storage access on-line
problem solving procedure
Problem Solving Procedure
  • 1. Layout of Scenario

Problem: environment, conditions, flowcharts, etc

2. State Null Hypothesis

Consider Problem effect across all interfacing levels leading to possible (multiple) causes (flowchart). Address complexity of problem, whether there is more than one. Alternative hypotheses listed. Costing issues addressed.

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3. Analysis Flowchart

Failure records, statistical flowcharts – alternative research methodologies identified

  • 4. Risks

Previous works, arguments, risk assessments available?

  • 5. Problem solving tools, Working model

Physical assumptions, background theory – design equations, physics, use of C and E (appropriate method), 5 Whys, brainstorming, Fault tree, FMEA, MORT, Design of Experiments, etc

slide9
6. Bias, Rejection criteria for null hypothesis
  • 7. Hard Collection, analysis

Analysis: Questionnaires, Engineering analysis: e.g. materials test, statistical analysis, etc

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8.Conclusions Accept/reject hypothesis based on model/assumption/bias or change hypothesis (go to step 2)
  • 9. Recommendations for corrective action Change to schedules, procedures, Poka-Yoke devices, etc. Standardisation.
  • 10. Feedback/Feed forward

To next problem, to database for dissemination and comment

job description of facilitator
Job Description of Facilitator
  • Aids the problem solving activity
  • knowledge and experience of the problem solving approach, team dynamics
  • knowledge of what expertise is required for a particular problem and who can provide it (available from personnel files)
  • has the ability to aid incorporation of diverse knowledge
  • can mediate in issues arising from differing viewpoints
  • suggest methods of solution (qualitative and/or quantitative)
  • provide guidance of the holistic view of the company strategic plan.
no fault found nff
No Fault Found (NFF)

Reason: not been installed on the aircraft and since the classification ‘Missing’ did not exist in the failure definitions inventory (because ‘Missing’ was not a failure category) the nearest most appropriate category was NFF. In this case, NFF is a misleading classification because it may indicate that a failure did not exist in the first place.

We should stratify the problem by disseminating our data into more appropriate categories and discuss them individually.

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No Fault Found

Plenty of Reasons:

No classification for what has been found

Replace everything (saves time)

Interdependencies between systems, e.g. common power supplies

Loading

Working at limits of operation

Intermittent Wiring faults

Ground test conditions cannot reproduce latent defect

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Example Hypothesis

  • Aircraft operating, external temperatures and vibration affecting systems
  • Time lag of thermal shocks 10º a minute in chamber but system takes longer
  • Rise in temperature causes expansions – effects on interconnections (transistors –pnp,npn; solder: DC wetting; may create micro-cracks
  • (DC wetting is passing of DC current over dry joint creates an increase in heat, resulting in the joint melting back together) – cannot locate fault
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Continued

  • Possibly surfaces become more elastic, cracks open quicker over time allowing contamination
  • Cracks will close again, only long term exposure to adverse conditions may produce identifiable failure
  • Road Surface testing, DOE (long term effects), FEA/Thermal effects, compatible materials, HALT, Simulation within CAD of thermal/vibration effects
step 1
Step 1.

The environment, the operating conditions and the problem and associated inter-relationships should be outlined in sketch form (e.g. an Affinity diagram) to highlight areas where a possible solution may lie. Flowcharts, diagrams, previous analyses should be made available (preferably on-line).

step 3 structure
Step 3. Structure
  • Approaches to identifying structure can be split into two separate areas; where extra explanatory information is available and where it is not.
multivariate data analysis flowchart
Multivariate Data Analysis Flowchart

Description of physical and functional system

Check for missing or corrupt data

Discriminant analysis

Multivariate analyses for determining structure - PCA, correspondence, cluster, correlation, distance measures, etc

EDA

Modelling time metric data - time series, PHM, PIM, GLIM, regression

data analysis
Data Analysis
  • Hypothesis 1: The stratum of a number of sockets is homogeneous. The alternatives are that times are clustered (non-independence) and/or inhomogeneous
  • Hypothesis 2: The processes are independent against clustering (process identified as “colored”)
  • Hypothesis 3: The colored process is stationary
  • Hypothesis 4: The process is “color blind competing risk”
  • Hypothesis 5: The process is stationary competing risk
  • Hypothesis 6: The process is renewal competing risk
  • Hypothesis 7: The process is Poisson competing risk and under the alternative hypothesis, H1: Renewal process.
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Org

NUKEM

VTT

JRC - ISPRA

INTER-ATOM

ENEA –VEL

EDA

M graph

TT Kaplan Meier plot

TT

Trend Test

No trend found

NT

No trend found GF

Trend found CF

TD

Serial Correlation

NT

NT

Log rank WR LR

NT

NT

Distribution

EX WE GF

EX WE GF

See EDA above OS GF

EX WE

EX WE

Assumptions

OU CE

OU CE Trend SC

OU CE

OU CE

OU

Other Analysis

AV

step 5
Step 5

A repository of tools should be kept with examples of how they may be used in conjunction with each other. The repository may contain examples of the 7 quality tools, the 7 new quality tools, brainstorming, Management Oversight and Risk Tree (MORT), Failure Modes and Effects Analysis (FMEA), radar charts, etc.

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The Pro-Enbis project is supported by funding under the European Commission's Fifth Framework 'Growth' Programme via the Thematic Network "Pro-ENBIS" contract reference: G6RT-CT-2001-05059.
  • The authors (i.e., Pro-ENBIS) are solely responsible for the content and it does not represent the opinion of the Community, the Community is not responsible for any use that might be made of data therein