TY  - CONF
SN  - 9781538672693
PB  - Institute of Electrical and Electronics Engineers Inc.
ID  - scholars9657
TI  - Development of Predictive Maintenance Interface Using Multiple Linear Regression
N2  - The common practice in most of the oil and gas organizations is to use periodic and preventive (time-based) maintenance techniques. These time-based maintenance techniques apply checking on equipment at regular intervals to avoid failures. However, they can lead to high maintenance cost with either over maintenance or unscheduled downtime. This issue can be encountered by using predictive maintenance which predicts future equipment failures ahead of time. This method performs maintenance based on actual operating condition of equipment which reduces maintenance cost and eliminates the need for periodic maintenance. The purpose of this work is to develop a user-friendly Graphical User Interface (GUI) application based predictive maintenance data analytic interface with the implementation of Multiple Linear Regression predictive maintenance technique. Multiple data sets of parameters of Booster Compressor (BC) are used on the proposed GUI to determine the accuracy of future prediction through implementation of Multiple Linear Regression technique. © 2018 IEEE.
KW  - Graphical user interfaces; Internet of things; Linear regression; Preventive maintenance
KW  -  Booster compressor; Data Analytic; Graphical user interfaces (GUI); Multiple linear regressions; Operating condition; Periodic maintenance; Predictive maintenance; Time based maintenance
KW  -  Costs
A1  - Abbasi, T.
A1  - Lim, K.H.
A1  - Rosli, N.S.
A1  - Ismail, I.
A1  - Ibrahim, R.
AV  - none
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059759662&doi=10.1109%2fICIAS.2018.8540602&partnerID=40&md5=a69d2c1280a40459277ca4abf4a3030f
N1  - cited By 9; Conference of 7th International Conference on Intelligent and Advanced System, ICIAS 2018 ; Conference Date: 13 August 2018 Through 14 August 2018; Conference Code:143005
Y1  - 2018///
ER  -