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Exploratory Data Analysis Approaches to Reliability: Some New Directions Chris McCollin Cornel Bunea Maria Ramalhoto.

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Presentation on theme: "Exploratory Data Analysis Approaches to Reliability: Some New Directions Chris McCollin Cornel Bunea Maria Ramalhoto."— Presentation transcript:

1 Exploratory Data Analysis Approaches to Reliability: Some New Directions Chris McCollin Cornel Bunea Maria Ramalhoto

2 Chris McCollin The 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

3 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

4 FMEA/FRACAS Comparison

5 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

6 Flowchart of Problem Solving Database

7 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.

8 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

9 6. Bias, Rejection criteria for null hypothesis 7. Hard Collection, analysis Analysis: Questionnaires, Engineering analysis: e.g. materials test, statistical analysis, etc

10 8.ConclusionsAccept/reject hypothesis based on model/assumption/bias or change hypothesis (go to step 2) 9. Recommendations for corrective actionChange to schedules, procedures, Poka- Yoke devices, etc. Standardisation. 10. Feedback/Feed forward To next problem, to database for dissemination and comment

11 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.

12 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.

13 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

14 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

15 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

16 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).

17 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.

18 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

19 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, H 1 : Renewal process.

20 OrgNUKE M VTTJRC - ISPR A INTER - ATOM ENE A – VEL EDAM graph TT Kapla n Meier plot TT Trend Test No trend found NTNo trend found GF Trend found CF TD Serial Correl ation NT Log rank WR LR NT Distrib ution EX WE GF See EDA above OS GF EX WE Assum ptions OU CE OU CE Trend SC OU CE OU Other Analy sis AV

21 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.


23 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

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