語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Modeling preventive maintenance in c...
~
Rivas, Jessica.
FindBook
Google Book
Amazon
博客來
Modeling preventive maintenance in complex systems.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Modeling preventive maintenance in complex systems./
作者:
Rivas, Jessica.
面頁冊數:
148 p.
附註:
Source: Masters Abstracts International, Volume: 53-06.
Contained By:
Masters Abstracts International53-06(E).
標題:
Industrial engineering. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1565118
ISBN:
9781321191424
Modeling preventive maintenance in complex systems.
Rivas, Jessica.
Modeling preventive maintenance in complex systems.
- 148 p.
Source: Masters Abstracts International, Volume: 53-06.
Thesis (M.S.A.A.)--Purdue University, 2014.
This item must not be sold to any third party vendors.
This thesis presents an explicit consideration of the impacts of modeling decisions on the resulting maintenance planning. Incomplete data is common in maintenance planning, but is rarely considered explicitly. Robust optimization aims to minimize the impact of uncertainty---here, in contrast, I show how its impact can be explicitly quantified. Doing so allows decision makers to determine whether it is worthwhile to invest in reducing uncertainty about the system or the effect of maintenance. The thesis consists of two parts. Part I uses a case study to show how incomplete data arises and how the data can be used to derive models of a system. A case study based on the US Navy's DDG-51 class of ships illustrates the approach. Analysis of maintenance effort and cost against time suggests that significant effort is expended on numerous small unscheduled maintenance tasks. Some of these corrective tasks are likely the result of deferring maintenance, and, ultimately decreasing the ship reliability. I use a series of graphical tests to identify the underlying failure characteristics of the ship class. The tests suggest that the class follows a renewal process, and can be modeled as a single unit, at least in terms of predicting system lifetime.
ISBN: 9781321191424Subjects--Topical Terms:
526216
Industrial engineering.
Modeling preventive maintenance in complex systems.
LDR
:03410nmm a2200301 4500
001
2061483
005
20151006081808.5
008
170521s2014 ||||||||||||||||| ||eng d
020
$a
9781321191424
035
$a
(MiAaPQ)AAI1565118
035
$a
AAI1565118
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Rivas, Jessica.
$3
3175749
245
1 0
$a
Modeling preventive maintenance in complex systems.
300
$a
148 p.
500
$a
Source: Masters Abstracts International, Volume: 53-06.
500
$a
Adviser: Karen Marais.
502
$a
Thesis (M.S.A.A.)--Purdue University, 2014.
506
$a
This item must not be sold to any third party vendors.
520
$a
This thesis presents an explicit consideration of the impacts of modeling decisions on the resulting maintenance planning. Incomplete data is common in maintenance planning, but is rarely considered explicitly. Robust optimization aims to minimize the impact of uncertainty---here, in contrast, I show how its impact can be explicitly quantified. Doing so allows decision makers to determine whether it is worthwhile to invest in reducing uncertainty about the system or the effect of maintenance. The thesis consists of two parts. Part I uses a case study to show how incomplete data arises and how the data can be used to derive models of a system. A case study based on the US Navy's DDG-51 class of ships illustrates the approach. Analysis of maintenance effort and cost against time suggests that significant effort is expended on numerous small unscheduled maintenance tasks. Some of these corrective tasks are likely the result of deferring maintenance, and, ultimately decreasing the ship reliability. I use a series of graphical tests to identify the underlying failure characteristics of the ship class. The tests suggest that the class follows a renewal process, and can be modeled as a single unit, at least in terms of predicting system lifetime.
520
$a
Part II considers the impact of uncertainty and modeling decisions on preventive maintenance planning. I review the literature on multi-unit maintenance and provide a conceptual discussion of the impact of deferred maintenance on single and multi-unit systems. The single-unit assumption can be used without significant loss of accuracy when modeling preventive maintenance decisions, but leads to underestimating reliability and hence ultimately performance impacts in multi-unit systems. Next, I consider the two main approaches to modeling maintenance impact, Type I and Type II Kijima models and investigate the impact of maintenance level, maintenance interval, and system quality on system lifetime. I quantify the net present value obtained of the system under different maintenance strategies and show how modeling decisions and uncertainty affect how closely the actual system and maintenance policy approach the maximum net present value. Incorrect assumptions about the impact of maintenance on system aging have the most cost, while assumptions about design quality and maintenance level have significant but smaller impact. In these cases, it is generally better to underestimate quality, and to overestimate maintenance level.
590
$a
School code: 0183.
650
4
$a
Industrial engineering.
$3
526216
650
4
$a
Naval engineering.
$3
3173824
690
$a
0546
690
$a
0468
710
2
$a
Purdue University.
$b
Aeronautics and Astronautics.
$3
1035670
773
0
$t
Masters Abstracts International
$g
53-06(E).
790
$a
0183
791
$a
M.S.A.A.
792
$a
2014
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1565118
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9294141
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入