eprintid: 7742
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/77/42
datestamp: 2023-11-09 16:19:34
lastmod: 2023-11-09 16:19:34
status_changed: 2023-11-09 16:10:18
type: article
metadata_visibility: show
creators_name: Ahmed, U.
creators_name: Hussin, H.
creators_name: Muhammad, M.
title: Comprehensive data collection for root cause failure analysis in oil and gas industries
ispublished: pub
note: cited By 0
abstract: Equipment failure that affects plant operations is a major issue in industries. When equipment fails it causes immense loss to industries in terms of resources and time, increased maintenance cost and equipment stoppage. The priority of reliability/maintenance team is to overcome these failures as soon as possible to avoid further losses. Root cause failure analysis (RCFA) process is used to identify and stop recurrence of these failures and data collection is most significant part of this process. Comprehensive and relevant failure data is crucial to identify and understand the root causes of a failure accurately. Unavailability of correct, adequate and sufficient data can lead to undesired results of RCFA. The purpose of this study is to propose a comprehensive approach of data collection for equipment failure in oil & gas/process industries for successful identification and elimination of root causes. Furthermore, this study has also proposed a template for comprehensive data collection that can be used to gather sufficient data for equipment failure investigation. ©2006-2016 Asian Research Publishing Network (ARPN).
date: 2016
publisher: Asian Research Publishing Network
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994378271&partnerID=40&md5=382ea278bfb42b6376fc3ad5eba13322
full_text_status: none
publication: ARPN Journal of Engineering and Applied Sciences
volume: 11
number: 20
pagerange: 12153-12158
refereed: TRUE
issn: 18196608
citation:   Ahmed, U. and Hussin, H. and Muhammad, M.  (2016) Comprehensive data collection for root cause failure analysis in oil and gas industries.  ARPN Journal of Engineering and Applied Sciences, 11 (20).  pp. 12153-12158.  ISSN 18196608