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contributor authorSaumil Ambani
contributor authorLin Li
contributor authorJun Ni
date accessioned2017-05-09T00:34:07Z
date available2017-05-09T00:34:07Z
date copyrightJune, 2009
date issued2009
identifier issn1087-1357
identifier otherJMSEFK-28137#031009_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/141234
description abstractMaintenance decision-making has emerged as an important area of industrial research. Over the past two decades, maintenance policies have evolved from simple reactive maintenance to complex versions of condition-based maintenance (CBM). A quantitative description of a machine’s health, as found in CBM, is essential to plan maintenance effectively as it helps avoid excessive or insufficient maintenance. In spite of several advancements in the degradation monitoring techniques, most CBM decision-making methods still focus on a single machine system. Maintenance analysis of a single machine provides good insights, but lacks practical applications. In this paper, we develop a continuous time Markov chain degradation model and a cost model to quantify the effects of maintenance on a multiple machine system. An optimal maintenance policy for a multiple machine system in the absence of resource constraints is obtained. In the presence of resource constraints, two prioritization methods are proposed to obtain effective maintenance policies for a multiple machine system. A case study focusing on a section of an automotive assembly line is used to illustrate the effectiveness of the proposed method.
publisherThe American Society of Mechanical Engineers (ASME)
titleCondition-Based Maintenance Decision-Making for Multiple Machine Systems
typeJournal Paper
journal volume131
journal issue3
journal titleJournal of Manufacturing Science and Engineering
identifier doi10.1115/1.3123339
journal fristpage31009
identifier eissn1528-8935
keywordsMachinery
keywordsMaintenance AND Decision making
treeJournal of Manufacturing Science and Engineering:;2009:;volume( 131 ):;issue: 003
contenttypeFulltext


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