reliability : a step towards business...

Reliability : A step towards

Business Excellence

Using Minitab 16

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

•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!

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

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

Reliability – Why Do We Care ?

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

Reliability – Why Do we Care?

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.

Creating a

Community of

Problem

Solvers

Reliability Management :-

An Organizational Approach

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

Reliability –Bath Tub Curve

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

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!

Hazard Function graph Defines how failure rater vary over life

failure rate vs days

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”

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.

Asset Utilization (Cable Life) Exercise

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.

Additional Uses of Reliability analysis

A Case Study On

Reliability

Analysis

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.

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.

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!

Steps in Minitab to Predict

Future Compressor failures

STEP 1.

Arrange Data in a required format on

Minitab worksheet e.g. COMPRESSOR.MTW

Compressor Warranty Claims Data

from past 12 months (2009-10)



STEP 2.

Open worksheet and Choose Stat >

Reliability/Survival > Warranty Analysis

> Pre-Process Warranty Data.

Input Pre-Process Warranty Data



STEPS 3 AND 4:-

In Shipment (sale) column, enter Ship.

In Return (failure) columns, enter

Month1-Month12. Click OK.

Minitab Calculates

Start Time, End Time &

Frequencies of Warranty claims



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.

Open Warranty Predictions in

Minitab



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

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

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

Predicted No. of Compressor

Failures

Max Failure =104

Min Failure = 67

Max Failure in 1st month= 23

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.

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.

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

http://www.minitab.com/

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.

Additional Resources For

Reliability Analysis

ASQ-Saskatchewan

www.asqsask.org

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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