Post on 22-Jan-2018
© 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.