Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (6): 12601271.doi: 10.21629/JSEE.2019.06.20
• Reliability • Previous Articles
Received:
20181226
Online:
20191220
Published:
20191225
Contact:
Zhenya WU
Email:wzy9012@163.com;hao001@sina.com
About author:
WU Zhenya was born in 1990. He received his B.S. degree in missile engineering from Air Force Engineering University, Xi'an, Shaanxi, China, in 2013, and M.S. degree in equipment management from Air Force Engineering University, in 2016. He is currently pursuing his Ph.D. degree in armament science and technology at Shijiazhuang Campus of Army Engineering University. His current research interests include maintainability demonstration and statistics. Email: Supported by:
Zhenya WU, Jianping HAO. Clusteringbased maintainability demonstration for complex systems with a mixed maintenance time distribution[J]. Journal of Systems Engineering and Electronics, 2019, 30(6): 12601271.
Table 1
Maintainability attributes for mechanical systems"
Feature  Number  Maintainability attribute 
1  Accessibility  
2  Disassembly/assembly  
3  Standardization  
4  Simplicity  
Design  5  Identification 
6  Diagnosability  
7  Modularization  
8  Triboconcepts  
Personnel  9  Personnel including ergonomics 
10  System environment  
Logistic  11  Tools and test equipment 
Support  12  Documentation 
Table 2
Equipment maintenance time records"
Number  A  B  C  D  E  F  G  H  I 
1  17(2.83)  35(3.56)  13(2.56)  16(2.77)  31(3.43)  20(3.00)  31(3.43)  19(2.94)  45(3.81) 
2  9(2.19)  39(3.66)  21(3.04)  14(2.64)  28(3.33)  11(2.40)  16(2.77)  28(3.33)  47(3.85) 
3  29(3.37)  21(3.04)  28(3.33)  15(2.71)  23(3.14)  18(2.89)  30(3.40)  23(3.14)  42(3.74) 
4  11(2.40)  13(2.56)  19(2.94)  16(2.77)  33(3.50)  20(3.00)  16(2.77)  25(3.22)  41(3.71) 
5  20(3.00)  11(2.40)  18(2.89)  15(2.71)  37(3.61)  8(2.08)  16(2.77)  28(3.33)  36(3.58) 
6  10(2.30)  17(2.83)  33(3.50)  12(2.48)  29(3.37)  9(2.20)  37(3.61)  23(3.14)  41(3.71) 
7  11(2.40)  19(2.94)  12(2.48)  16(2.77)  38(3.64)  13(2.56)  9(2.20)  25(3.22)  31(3.43) 
8  25(3.22)  10(2.30)  19(2.94)  36(3.58)  29(3.37)  10(2.30)  20(3.00)  28(3.33)  32(3.47) 
9  10(2.30)  15(2.71)  23(3.14)  19(2.94)  38(3.64)  32(3.47)  19(2.94)  33(3.50)  34(3.53) 
10  15(2.71)    23(3.14)    39(3.66)  33(3.50)  22(3.09)  27(3.30)  34(3.53) 
11      18(2.89)    39(3.66)  11(2.40)    36(3.58)  34(3.53) 
12      17(2.83)    32(3.47)  18(2.89)    28(3.33)   
13      20(3.00)    23(3.14)         
Mean= 23.62 min(3.07); Variance ≈ 97.61 min^{2}(0.20) 
Table 3
Initial parameters for each component's distribution using the Kmeans algorithm"
Model  Centroid  Boundary  
1  2  3  4  1  2  3  4  
k = 2  2.68  3.44  –  –  [2.07 3.05]  [3.09 3.86]  –  –  
k = 3  2.38  2.95  3.52  –  [2.07 2.64]  [2.70 3.22]  [3.29 3.86]  –  
k = 4  2.36  2.79  3.06  3.52  [2.07 2.57]  [2.63 2.90]  [2.94 3.22]  [3.29 3.86] 
Table 4
Improved parameters for each component's distribution using the EM algorithm"
Model  Component distribution  
1  2  3  4  
k = 2   –  –  
k = 3    –  
k = 4    
Table 5
Improved parameters for each component's distribution using the EM algorithm"
Model  Component distribution  
1  2  3  4  
k = 2   –  –  
k = 3    –  
k = 4    
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