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contributor authorHisham Said
contributor authorTony Nicoletti
contributor authorPeter Perez-Hernandez
date accessioned2017-12-30T13:04:59Z
date available2017-12-30T13:04:59Z
date issued2016
identifier other%28ASCE%29CP.1943-5487.0000444.pdf
identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4245435
description abstractContractors and equipment rental companies have started to acknowledge and use the telematics technology as a reliable solution for timely collection of their equipment fleet data. Telematics is the integration of wireless communications, vehicle monitoring systems, and location devices to provide real-time spatial and performance data of the fleet machines. Despite the large amount of real-time equipment data made available by telematics, fleet managers still try to identify ways to use such data to make informed fleet-management decisions. This paper presents the development of novel telematics-based computational methodologies to support two major equipment fleet management tasks: fleet use assessment and equipment health monitoring. First, a description of the telematics system and data used are presented. Second, a computational algorithm is proposed to quantify the fleet-wide equipment used, based on basic telematics data. Third, a health-monitoring framework is developed to estimate equipment failure events using telematics-based hazard functions, which were developed using survival analysis techniques. Finally, the telematics data sets of large equipment fleets (dozers, excavators, backhoes, and dump trucks) from two companies are used to verify and validate the proposed research developments by providing insightful fleet-management information.
publisherAmerican Society of Civil Engineers
titleUtilizing Telematics Data to Support Effective Equipment Fleet-Management Decisions: Utilization Rate and Hazard Functions
typeJournal Paper
journal volume30
journal issue1
journal titleJournal of Computing in Civil Engineering
identifier doi10.1061/(ASCE)CP.1943-5487.0000444
page04014122
treeJournal of Computing in Civil Engineering:;2016:;Volume ( 030 ):;issue: 001
contenttypeFulltext


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