© 2006 Hewlett-Packard Development Company, L.P.The information contained herein is subject to change without notice

Methods for reliability prediction, testing and

measurement in Engineering teams

December 21, 2015 2

Statistical team areas of expertise • Reliability tests plan and analysis• Design and analysis of experiments• Sampling optimizations• Calculation and verification of tolerances• Evaluation of measurement error (Gauge R&R study)• Analysis of existing data (IServe, suppliers, MFG, ...)• Forecasting models• Utilization and operational models• Support of Lab/System/Alpha/Beta tests• Numeric Simulations• Wide range of trainings on different statistical topics

and software

December 21, 2015 3

Engineering team activities can benefit

from following Reliability methods:

• Estimation of current product reliability

• Setting targets for reliability of improved product

• Reliability allocation between sub-systems

• Reliability testing (for conformance with targets)

− Accelerated lab tests

− Field tests

December 21, 2015 4

The goal of our activity

Provide tools to all engineers for reliability prediction, testing and measurement

− Introduce the team with terminology and methodology

− Explain how to ensure that the tests performed are able to provide required answers

− Train the team to use statistically valid reliability calculations

December 21, 2015 5

Beta plan and analysis

• Goal definition − Chiller example: Same or better → MTBF → 95% Reliability

• Measuring methods (Filter/BID vs. PIP/Blkt vs. Imp. Paper)

• Test plan and recording of results

• Integration of reference in the test

• Sample size calculations (# of presses, # of Imp, time period)Same – better criteria

• Choice of customers (AMPV, stable LS, problems)

• Analysis of results

December 21, 2015 6

The Reliability forum vision :

• The whole organization will work according to pre-defined reliability plan

• All data will be recorded in appropriate way, which will allowed to use it for reliability estimations and predictions

• Managers will recognize the benefits of reliability-based methods (reduced development time, elimination of inconclusive tests, better understanding of problems) and make sure that all team members are using these methods *

* Statistical team will provide training to all CPE team members on application of above methods

December 21, 2015 7

The main message

• Managers should recognize the benefits of reliability-based methods and demand from all engineers to use them

• All engineers should receive training on reliability methods

• All engineers should use these methods for relevant projects

• We need engineering representative to join a reliability forum as a member

December 21, 2015 8

Sample size calculationsSample size calculations

Required sample size for consumables field LS testing

0

100

200

300

400

500

600

700

800

900

1000

10% 15% 20% 25% 30% 35% 40% 45% 50%

Minimal detectable difference between test and reference

Requ

ired

sam

ple

size

Beta=0.1

Beta=0.15

Beta=0.2

Alpha = 0.05

Alpha - probability for false declaration of differenceBeta - probability not to detect desired difference

How many test blankets should be used till their failure in order to detect 10% decrease in LS

December 21, 2015 9

Possible shapes of LS distribution

December 21, 2015 10

Donaldson chiller reliability

Survival Plot: time till the first failure hp-5000 presses that were installed since 27/10/2005. Field data from all service calls on hp-5000 presses between 22/11/2005 and 20/11/2006

0.80

0.82

0.84

0.86

0.88

0.90

0.92

0.94

0.96

0.98

1.00

Surv

ivin

g

0 1 2 3 4 5 6 7 8 9 10 11 12 13

LS (months)

12% of units w ill fail during the f irst 6 months

3% of units w ill fail during the first 1 month

Warranty period

December 21, 2015 11

Impression paper reliability

Survival Plot: time till Imp. Paper tear – beta results

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Sur

vivi

ng

0 10 20 30 40 50 60 70 80

LS

0.05

0.10

0.15

0.20

Pro

babi

lity

0 30000 70000 110000 160000 210000 260000

Reference

Mean = 42.8

Std. = 42.2

Test

0.05

0.10

0.15

Pro

babi

lity

0 30000 70000 110000 160000 210000 260000

Mean = 64.3

Std. = 22.8

December 21, 2015 12

Blanket LS behavior

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

55000

60000

Pri

nt Im

p.

09/

02/

2005

23/

02/

2005

11/

03/

2005

24/

03/

2005

18/

04/

2005

29/

04/

2005

13/

05/

2005

23/

05/

2005

31/

05/

2005

09/

06/

2005

16/

06/

2005

22/

06/

2005

05/

07/

2005

12/

07/

2005

Rep. Date

December 21, 2015 13

Possible shapes of hazard

0

0.00001

0.00002

0.00003

0.00004

0.00005

0.00006

0.00007

Haz

ard

Rat

e

0 10000 20000 30000 40000 50000 60000 70000 80000 90000 100000 110000 120000

Imp.

beta=0.5

beta=1

beta=1.4

beta=2

beta=3

December 21, 2015 14

Possible shapes of LS distribution

0.10

0.20

0.30

0.40

0.50

Probability

0 20000 60000 100000 140000 180000 220000 260000 300000

Beta=0.5

0.05

0.10

0.15

Probability

0 20000 60000 100000 140000 180000 220000 260000 300000

Beta=1

0.05

0.10

0.15

Probability

0 20000 60000 100000 140000 180000 220000 260000 300000

Beta=2

0.05

0.10

0.15

0.20

0.25

Probability

0 20000 60000 100000 140000 180000 220000 260000 300000

Beta=3

December 21, 2015 15

HP32x0 Consumables Life Span Trend Analysis

• Decrease of 8K in average PIP LS in the period after 01/06.

• No impact of HP3250 presses on LS decrease.

• All customers (big and small) showed drop in average PIP LS in March06.

• Substantial decrease in PIP LS after 01/06 was observed mainly in 2 customers: Jeppesen (Denver and Frankfort, 6.5K and 21K accordingly) and Boschdruck (13.5K).

• The impact of Jeppesen Frankfort on PIP LS average gradually increased while their average LS decreased.

• Autobias Incomplete was the main RPM that increased after 01/06.