reliability maintenance engineering 1 - 4 estimating reliability

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Reliability Engineering Fred Schenkelberg [email protected]

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Reliability Maintenance Engineering Day 1 session 4 Estimating Reliability Three day live course focused on reliability engineering for maintenance programs. Introductory material and discussion ranging from basic tools and techniques for data analysis to considerations when building or improving a program.

TRANSCRIPT

Page 1: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Reliability Engineering

Fred [email protected]

Page 2: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

USING FIELD AND TEST DATA TO ESTIMATE RELIABILITY

Day 1 Session 4

Page 3: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Objectives

• Discussing reliability data types• Considering complete and censored data• Analyzing trend plotting, 80-20 plots and

statistical plots• Drawing a best-fit regression line with Weibull• Recording data related to reliability

performance• Providing continuity in data collection systems

Page 4: Reliability Maintenance Engineering 1 - 4 Estimating Reliability
Page 5: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Reliability Data Types

• CMMS data

• Process data

• Life data

• Time to Failure data

Page 6: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Reliability Data Types

• Pass/Fail data• Attribute data

• Time or cycles to failure• Variables data

• Start and stop definitions

Page 7: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Reliability Data Types

• Complete data– All units have failed

• Censored data– Right censored – not all

have failed yet– Left censored – not sure

when some started– Interval censored – not

sure when failure occurred between inspections.

Page 8: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Reliability Data Types

• Non-repairable data

All start at time zero

Page 9: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Reliability Data Types

• repairable data

All start at time zero

Page 10: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Discussion & Questions

Page 11: Reliability Maintenance Engineering 1 - 4 Estimating Reliability
Page 12: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Trend Plotting

Advantages• Easy

• Visual

• Actual data

Disadvantages• Difficult to see changes

• Lagging indicator

• May require adjustments for scheduled downtime

Page 13: Reliability Maintenance Engineering 1 - 4 Estimating Reliability
Page 14: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

80 – 20 or Pareto plotting

Advantages• Easy

• Visual

• Prioritization build in

Disadvantages• Difficult to see changes over

time

• Doesn’t include costs impact

Page 15: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Coun

t or F

requ

ency

Page 16: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Life Data CDF

Advantages• Accounts for all data

• Visual

• Easy to read

Disadvantages• Difficult to see changes

• Requires probability paper or software

• Requires time to failure data

CDF – Cumulative Distribution Function -

Page 17: Reliability Maintenance Engineering 1 - 4 Estimating Reliability
Page 18: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

MCF plotting

Advantages• Very Easy to create

• Easy to see patterns

Disadvantages• Difficult to summarize

• Requires more than two failures/repairs per equipment

• Doesn’t account for scheduled downtime or extended repairs

MCF – Mean Cumulative Function

Page 19: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Wayne Nelson, Graphical Analysis of Repair Data

Page 20: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Discussion & Questions

Page 21: Reliability Maintenance Engineering 1 - 4 Estimating Reliability
Page 22: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Weibull Plotting with Weibull++

• Data preparation• Basic algorithm• Censored data handing

• For more details• www.weibul.com

Page 23: Reliability Maintenance Engineering 1 - 4 Estimating Reliability
Page 24: Reliability Maintenance Engineering 1 - 4 Estimating Reliability
Page 25: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Reading a Weibull CDF Plot

Page 26: Reliability Maintenance Engineering 1 - 4 Estimating Reliability
Page 27: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

MCF plotting

• Data Preparation• Basic algorithm

• For more information• Trindade paper, book,

Nelsons paper, book

Page 28: Reliability Maintenance Engineering 1 - 4 Estimating Reliability
Page 29: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Reading an MCF plot

Page 30: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Discussion & Questions

Page 31: Reliability Maintenance Engineering 1 - 4 Estimating Reliability
Page 32: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Plot labeling

• Title• Data source• Data timeframe

• Axis labels and units

Page 33: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Report Data

• Regular reports

• Project reports

• Analysis reports

• Recommendation reports

Page 34: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Comparisons over time

• Break up data by time– Before/after change– Before/after experiment– Before/after overhaul

• Labels• Show magnitude of

impact clearly, if any.

Page 35: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Data collection over time

• Vendor data• Installation• Maintenance• Decommissioning

Page 36: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Discussion & Questions

Page 37: Reliability Maintenance Engineering 1 - 4 Estimating Reliability

Summary

• Discussing reliability data types

• Considering complete and censored data

• Analyzing trend plotting, 80-20 plots and statistical plots

• Drawing a best-fit regression line with Weibull

• Recording data related to reliability performance

• Providing continuity in data collection systems

Using field and test data to estimate reliability