Reliability : A step towards Business...
Transcript of Reliability : A step towards Business...
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Reliability : A step towards
Business Excellence
Using Minitab 16
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Reliability : A step towards
Business Excellence
By Rajeev Chadha, P.Eng.
Lean Six Sigma Master Black Belt
Mosaic Potash ULC Canada
In association with Minitab 16
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•Definition of Reliability
•Impact to the business
•Data distribution characteristics
•Exercises
•Break
•Compressor Case Study
Module Overview
A♦ - Minitab is a powerful tool for
reliability/survival analysis!
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How Do You Define Reliability?
The probability that an item (or system) will
perform its intended function for a given
period of time under a given set of conditions
Or
Achieving expected performance
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For consideration
–Pumps and Process Equipments
–Entire Manufacturing processes
–Customer invoicing & Services
–Month end Accounts closing
– Laptop computers
–Deep well blow out preventer
Where can you use Reliability
Analysis
A♦ - Reliability is not just for
maintenance
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Reliability – Why Do We Care ?
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How Does Reliability Works?
Most of the North American Blue chip Companies
non capital spending for turnaround, R&M, CL, and
internal labor are:-
• FY11 - $349 MM for Energy Sector
• FY11 – $189MM for Mining Sector
Would it be beneficial to save these $$ for your
company and for your career?
Bottom line dollars
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Reliability – Why Do we Care?
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Reliability
If You can Predict it You Can Prevent
The Estimated MRO Inventory cost of an Average US
Co. is 15-20% of the Worth just because our systems
are not Reliable and Predictable.
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Creating a
Community of
Problem
Solvers
Reliability Management :-
An Organizational Approach
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Probabilistic
•Measure reliability of sub systems through failure
Analysis
• Evaluate interactions between sub systems
• Predict reliability of the entire system without full
understanding of the details of what is causing the
variation – it’s too complex
Deterministic
•Religious vigilance and attention to detail – constant
and meticulous search for errors and defects through
inspections and testing – strict and thorough
implementation of corrective actions
Reliability – Two approaches
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Reliability –Bath Tub Curve
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Reliability – Time Scale
For Reliability, Time does not have to be
measured in only time! It can also be
measured in:-
• Mileage
• Man Hours
• Cycles
Start-ups
Thermal Stress
Mechanical Stress
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Reliability Hazard Rate
The one formula to describe it all
λ > 0 (scale or characteristic life)
K > 0 (shape)
H (x,k,λ) = (k/ λ) (x/ λ)k-1
A♦ -Minitab calculates it for you!
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Hazard Function graph Defines how failure rater vary over life
failure rate vs days
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Exercise To Calculate Reliability for Better Asset Utilization
• Let us take the example of Replacement of
Hi-tension (Voltage) swing wires in Mines and
Dredges:-
Objective- “To increase the Swing Wires life to
improve the Asset utilization”
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Reliability Parameters
•Reduce Employee Exposure to Hazards
arising from changing Hi-tension wires, Asset
failures and unsafe conditions.
•Increase Productivity of Assets by decreasing
downtime in Repair of Wires.
•Reduce Operating and Maintenance Expense
arising from frequent wire failures.
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Asset Utilization (Cable Life) Exercise
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Asset Utilization (Cable Life) Exercise
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Asset Utilization (Cable Life) Exercise
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Asset Utilization (Cable Life) Exercise
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Asset Utilization (Cable Life) Exercise
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Asset Utilization (Cable Life) Exercise
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Reliability If You can Predict it You Can Prevent it !
Other Uses :-
Predict Future Injury Rate
Predict Future Warranty Costs and Customer
Returns (Cost of Returned goods)
Measure, Predict & Optimize Utilization of
Your Assets
Man Hours worked Between Recordable
Injuries
Demonstrate Improvements & Draw
conclusions about your past performance.
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Additional Uses of Reliability analysis
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A Case Study On
Reliability
Analysis
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Compressor warranty claims:
Case Study (2009-10)
Suppose You work as a
Service/Reliability Manager for an
appliance manufacturer and want to
know the number of refrigerator
compressor warranty claims you
expect to see over the next five
months.
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Why Predictive Modeling?
With Weibull Modeling you can Predict
Future Compressor failures so that:-
• You can plan & Schedule after sales
services ahead of time.
• Arrange stock of Replacement Parts
(Compressors).
• Inform Manufacturing to improve process
to reduce compressor failures and control
warranty costs.
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Predict Future Compressor
failures
Use Weibull distribution to model time-
to-failure
The Past warranty claim data shows
that Out of 12,000 units in the field, 69
compressors failed in year 2009-10
A♦ -Remember Minitab is there
to Help you!
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Steps in Minitab to Predict
Future Compressor failures
STEP 1.
Arrange Data in a required format on
Minitab worksheet e.g. COMPRESSOR.MTW
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Compressor Warranty Claims Data
from past 12 months (2009-10)
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Steps in Minitab to Predict
Future Compressor failures
STEP 2.
Open worksheet and Choose Stat >
Reliability/Survival > Warranty Analysis
> Pre-Process Warranty Data.
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Input Pre-Process Warranty Data
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Steps in Minitab to Predict
Future Compressor failures
STEPS 3 AND 4:-
In Shipment (sale) column, enter Ship.
In Return (failure) columns, enter
Month1-Month12. Click OK.
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Minitab Calculates
Start Time, End Time &
Frequencies of Warranty claims
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Steps in Minitab to Predict
Future Compressor failures
Step 5
In Start time, enter 'Start time'. In
End time, enter 'End time'. In Frequency
(optional), enter Frequencies.
Step 6
Click Prediction. In Production
quantity for each time period, enter
1000. Click OK in each dialog box.
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Open Warranty Predictions in
Minitab
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Steps in Minitab to Predict
Future Compressor failures
Step 7-
Click Prediction. In Production
quantity for each time period, enter 1000.
Click OK in each dialog box.
OR
Stat > Reliability/Survival > Warranty
Analysis > Warranty Prediction > Graphs
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Minitab Output and Results
Distribution: Weibull with shape = 1.31962, scale = 328.914
Estimation method:Least squares (failure time (X) on rank (Y))
Summary of Current Warranty Claims:-
Total number of Compressor units shipped - 12000
Observed number of failures - 69
Expected number of failures - 71.2094
95% Poisson CI - (55.6367, 89.7905)
Number of units at risk for future time periods 11931
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Minitab Output and Results
Production Schedule of Compressors :-
Future time period (MONTHS) 1 2 3 4 5
Production quantity (UNITS) 1000 1000 1000 1000 1000
Table of Predicted Number of Failures:-
Future Potential Predicted
Time Number of Number of 95% Poisson CI
Period Failures Failures Lower Upper
1 12931 13.9815 7.6403 23.466
2 13931 29.3874 19.7387 42.106
3 14931 46.2486 33.8905 61.642
4 15931 64.5942 49.8093 82.393
5 16931 84.4519 67.4053 104.498
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Predicted No. of Compressor
Failures
Max Failure =104
Min Failure = 67
Max Failure in 1st month= 23
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Interpreting results about the
warranty claims
Out of 12,000 compressor units Sold in
2009-10, approximately 71 units are
expected to fail in next five months in 2011.
OR
From the failures plot, you can conclude with
95% confidence that between approximately
67 and 104 units are expected to fail in the
next five months.
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So Now Your Life is Easy !
You can…
• Plan and Schedule Max. 13 replacement
Compressors in 1st Month, Max. 30 in 2nd .
• CALCULATE the projected warranty costs.
• Carry (min. 20 –max. 30) Replacement
Compressors in stock.
• Advice Manufacturing to improve their process
where 11,931 Out of 12,000 units are at risk.
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Thank You For your Interest in
Reliability
Questions on Reliability Analysis?
Questions on Minitab Software?
*Apply for 30-Days Free Minitab trial
online at www.minitab.com
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The World Trusts MINITAB
• Minitab is the leading provider of
software for statistics education, Lean
Six Sigma, and quality improvement
projects. For nearly 40 years we have
been helping world-class organizations
analyze problems, transform their
business, and train their students.
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Additional Resources For
Reliability Analysis
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ASQ-Saskatchewan
www.asqsask.org
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Acknowledgements
I greatly appreciate my MOSAIC Corporate Six Sigma Team and ASQ-Saskatchewan team for helping me prepare this workshop presentation for ASQ-Canadian Quality Summit and Mining Gala 2012.
Last but not the least I would like to thank Mr. Jeff Adams of Minitab for supporting this project for training and educating our global quality community.
With Regards
Rajeev
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