relation: https://khub.utp.edu.my/scholars/11628/
title: Fault Tree Analysis for Control Valves in Process Plants by using R
creator: Mathur, N.
creator: Asirvadam, V.S.
creator: Abd Aziz, A.
creator: Ibrahim, R.
description: An industrial plants assembled with many components, standby systems, sensors, controlling components to make a smooth operation of plants. Losses produced by unplanned downtime may lead to major problems. Although, control valves which are used to control the rate of flow for pressure or liquid is an essential part of the plant operation. Since to reduce the losses or downtime damage, high reliability and standby availability are required to monitor. Hence, it requires some prediction which can express the likelihood of the events in the terms of quantitative methods. This research performs the prediction for reliability on the control instruments and its availability that is visualized for a quantitative perspective and estimation of the consequences of these failure depends on the control valve assembled in a process plant. This research will give practical assessments of the reliability of a control valve for better actions and higher reliable redundancy. By using R statistical software and packages this research will be more vibrant and will be visualized to a very extent level. Package »FaultTree »will be used in this paper to demonstrate and to explore the use of R software and it packages usages in many manners. This paper will demonstrate how Fault Tree Analysis can be done in process plants and how R statistical software holds importance in representing it. © 2019 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2019
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Mathur, N. and Asirvadam, V.S. and Abd Aziz, A. and Ibrahim, R.  (2019) Fault Tree Analysis for Control Valves in Process Plants by using R.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065483840&doi=10.1109%2fCSPA.2019.8696008&partnerID=40&md5=494ddba87cb221ef7f5aacfd6fdefe8b
relation: 10.1109/CSPA.2019.8696008
identifier: 10.1109/CSPA.2019.8696008