System reliability is usually predicted with the assumption that all component states are independent. This assumption may not accurate for systems with outsourced components since their states are strongly dependent and component details may be unknown. The purpose of this study is to develop an accurate system reliability method that can produce complete joint probability density function (PDF) of all the component states, thereby leading to accurate system reliability predictions. The proposed method works for systems whose failures are caused by excessive loading. In addition to the component reliability, system designers also ask for partial safety factors for shared loadings from component suppliers. The information is then sufficient for building a system-level joint PDF. Algorithms are designed for a component supplier to generate partial safety factors. The method enables accurate system reliability predictions without requiring proprietary information from component suppliers.

References

References
1.
Click
,
R. L.
, and
Duening
,
T. N.
,
2004
,
Business Process Outsourcing: The Competitive Advantage
,
Wiley
, Hoboken, NJ.
2.
Lacity
,
M. C.
, and
Willcocks
,
L.
,
2000
,
Global Information Technology Outsourcing: In Search of Business Advantage
,
Wiley
, Chichester, UK.
3.
Fiondella
,
L.
, and
Xing
,
L.
, 2014, “
Reliability of Two Failure Mode Systems Subject to Correlated Failures
,”
Annual Reliability and Maintainability Symposium
, Colorado Springs, CO, Jan. 27–30, pp.
1
6
.
4.
Littlefield
,
S.
,
Mazzuchi
,
T.
, and
Sarkani
,
S.
, 2012, “
Predicting Reliability in Design of Complex Systems With Common-Cause Failures and Time-Varying Failure Rates
,”
IEEE International Systems Conference
(
SysCon
2012), Vancouver, BC, Canada, Mar. 19–22, pp.
1
6
.
5.
Cruse
,
T. A.
,
1997
,
Reliability-Based Mechanical Design
,
CRC Press
, Boca Raton, FL.
6.
Hoyland
,
A.
, and
Rausand
,
M.
,
2004
,
System Reliability Theory: Models, Statistical Methods, and Applications
,
Wiley
,
Hoboken, NJ
.
7.
Ditlevsen
,
O.
,
1979
, “
Narrow Reliability Bounds for Structural Systems
,”
J. Struct. Mech.
,
7
(
4
), pp.
453
472
.
8.
Yong Cang
,
Z.
,
1993
, “
High-Order Reliability Bounds for Series Systems and Application to Structural Systems
,”
Comput. Struct.
,
46
(
2
), pp.
381
386
.
9.
Song
,
J.
, and
Der Kiureghian
,
A.
,
2003
, “
Bounds on System Reliability by Linear Programming
,”
J. Eng. Mech.
,
129
(
6
), pp.
627
636
.
10.
Song
,
J.
, and
Der Kiureghian
,
A.
, 2005, “
Component Importance Measures by Linear Programming Bounds on System Reliability
,”
Nineth International Conference on Structural Safety and Reliability (ICOSSAR9)
, Rome, Italy, June 19–23, pp.
19
23
.
11.
Kang
,
W.-H.
,
Song
,
J.
, and
Gardoni
,
P.
,
2008
, “
Matrix-Based System Reliability Method and Applications to Bridge Networks
,”
Reliab. Eng. Syst. Saf.
,
93
(
11
), pp.
1584
1593
.
12.
Hu
,
Z.
, and
Du
,
X.
,
2017
, “
System Reliability Prediction With Shared Load and Unknown Component Design Details
,”
AI Edam
,
31
(
3
), pp.
223
234
.
13.
Hu
,
Z.
, 2016, “
A Physics-Based Reliability Method for Components Adopted in New Series Systems
,”
Annual Reliability and Maintainability Symposium
(
RAMS
), Tucson, AZ, Jan. 25–28, pp.
1
7
.
14.
Hu
,
Z.
, and
Du
,
X.
,
2018
, “
An Exploratory Study for Predicting Component Reliability With New Load Conditions
,”
Front. Mech. Eng.
,
14
(
1
), pp.
1
9
.
15.
Yu
,
S.
,
Wang
,
Z.
, and
Meng
,
D.
,
2018
, “
Time-Variant Reliability Assessment for Multiple Failure Modes and Temporal Parameters
,”
Struct. Multidiscip. Optim.
,
58
(
4
), pp.
1705
1717
.
16.
Yu
,
S.
, and
Wang
,
Z.
,
2018
, “
A Novel Time-Variant Reliability Analysis Method Based on Failure Processes Decomposition for Dynamic Uncertain Structures
,”
ASME J. Mech. Des.
,
140
(
5
), p.
051401
.
17.
Yu
,
S.
,
Wang
,
Z.
, and
Zhang
,
K.
,
2018
, “
Sequential Time-Dependent Reliability Analysis for the Lower Extremity Exoskeleton Under Uncertainty
,”
Reliab. Eng. Syst. Saf.
,
170
, pp.
45
52
.
18.
Youn
,
B. D.
, and
Wang
,
P.
,
2009
, “
Complementary Intersection Method for System Reliability Analysis
,”
ASME J. Mech. Des.
,
131
(
4
), p.
041004
.
19.
Wang
,
P.
,
Hu
,
C.
, and
Youn
,
B. D.
,
2011
, “
A Generalized Complementary Intersection Method (GCIM) for System Reliability Analysis
,”
ASME J. Mech. Des.
,
133
(
7
), p.
071003
.
20.
Wang
,
Z.
, and
Wang
,
P.
,
2015
, “
An Integrated Performance Measure Approach for System Reliability Analysis
,”
ASME J. Mech. Des.
,
137
(
2
), p.
021406
.
21.
Hu
,
Z.
, and
Mahadevan
,
S.
,
2016
, “
A Single-Loop Kriging Surrogate Modeling for Time-Dependent Reliability Analysis
,”
ASME J. Mech. Des.
,
138
(
6
), p.
061406
.
22.
Hu
,
Z.
,
Nannapaneni
,
S.
, and
Mahadevan
,
S.
,
2017
, “
Efficient Kriging Surrogate Modeling Approach for System Reliability Analysis
,”
AI Edam
,
31
(
2
), pp.
143
160
.
23.
Kumar
,
D.
, and
Westberg
,
U.
,
1996
, “
Proportional Hazards Modeling of Time-Dependent Covariates Using Linear Regression: A Case Study [Mine Power Cable Reliability]
,”
IEEE Trans. Reliab.
,
45
(
3
), pp.
386
392
.
24.
Cardoso
,
J. B.
,
de Almeida
,
J. R.
,
Dias
,
J. M.
, and
Coelho
,
P. G.
,
2008
, “
Structural Reliability Analysis Using Monte Carlo Simulation and Neural Networks
,”
Adv. Eng. Software
,
39
(
6
), pp.
505
513
.
25.
Hu
,
Z.
, and
Du
,
X.
, 2018, “
System Reliability Analysis With in-House and Outsourced Components
,”
Second International Conference on System Reliability and Safety
(
ICSRS
), Milan, Italy, Dec. 20–22, pp.
146
150
.
26.
Hu
,
Z.
, and
Du
,
X.
,
2018
, “
Integration of Statistics-and Physics-Based Methods—A Feasibility Study on Accurate System Reliability Prediction
,”
ASME J. Mech. Des.
,
140
(
7
), p.
074501
.
27.
Gollwitzer
,
S.
, and
Rackwitz
,
R.
,
1983
, “
Equivalent Components in First-Order System Reliability
,”
Reliab. Eng.
,
5
(
2
), pp.
99
115
.
28.
Roscoe
,
K.
,
Diermanse
,
F.
, and
Vrouwenvelder
,
T.
,
2015
, “
System Reliability With Correlated Components: Accuracy of the Equivalent Planes Method
,”
Struct. Saf.
,
57
, pp.
53
64
.
29.
Hu
,
Z.
, 2018, “
A Partial Safety Factor Method for System Reliability Prediction With Outsourced Components
,”
ASME
Paper No. DETC2018-85195.
30.
Rosenblatt
,
M.
,
1952
, “
Remarks on a Multivariate Transformation
,”
Ann. Math. Stat.
,
23
(
3
), pp.
470
472
.
31.
Mansour
,
R.
, and
Olsson
,
M.
,
2014
, “
A Closed-Form Second-Order Reliability Method Using Noncentral Chi-Squared Distributions
,”
ASME J. Mech. Des.
,
136
(
10
), p.
101402
.
32.
Choi
,
S.-K.
,
Grandhi
,
R.
, and
Canfield
,
R. A.
,
2006
,
Reliability-Based Structural Design
,
Springer Science & Business Media
, London.
33.
Castro
,
P. M.
,
Delgado
,
R. M.
,
Cesar
,
D. S.
, and
Jose
,
M.
,
2005
, “
A Partial Factors Methodology for Structural Safety Assessment in Non-Linear Analysis
,”
Comput. Concr.
,
2
(
1
), pp.
31
53
.
34.
Ayyub
,
B. M.
, and
White
,
G. J.
,
1987
, “
Reliability-Conditioned Partial Safety Factors
,”
J. Struct. Eng.
,
113
(
2
), pp.
279
294
.
35.
Nikolaidis
,
E.
,
Nikolaidis Efstratios
,
S.
,
Ghiocel
,
D. M.
, and
Singhal
,
S.
,
2004
,
Engineering Design Reliability Handbook
, CRC Press, Boca Raton, FL.
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