Muammer Koç

Prof. Dr. Muammer Koç

Founding Professor and Head of Sustainability Division, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar
orcid

Research Focus & Metrics

Academic Career Length

31Years (1996-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2018 in Journal of Magnesium and Alloys
Verified
Journal Article
Open access
NSNurettin Sezer
Nurettin Sezer
ZEZafer Evis
Zafer Evis
SKSaid Murat Kayhan
Said Murat Kayhan
ATAydin Tahmasebifar
Aydin Tahmasebifar
MKMuammer Koç
Muammer Koç



1 October 2020 in Automation in Construction
Verified
Journal Article
Open access
ARAns Al Rashid
Ans Al Rashid
SKShoukat alim Khan
Shoukat alim Khan
Sami G. Al-GhamdiSami G. Al-Ghamdi
Sami G. Al-Ghamdi
MKMuammer Koç
Muammer Koç

1 January 2001 in Journal of Materials Processing Technology
Verified
Journal Article
Closed access
MKMuammer Koç
Muammer Koç
TATaylan Altan
Taylan Altan

1 December 2004 in Production Planning & Control
Verified
Journal Article
Closed access
JYJihong Yan
Jihong Yan
MKMuammer Koç
Muammer Koç
JLJay Lee
Jay Lee
This paper explores a method to assess assets performance and predict the remaining useful life, which would lead to proactive maintenance processes to minimize downtime of machinery and production in various industries, thus increasing efficiency of operations and manufacturing. At first, a performance model is established by taking advantage of logistic regression analysis with maximum-likelihood technique. Two kinds of application situations, with or without enough historical data, are discussed in detail. Then, real-time performance is evaluated by inputting features of online data to the logistic model. Finally, the remaining life is estimated using an ARMA model based on machine performance history; degradation predictions are also upgraded dynamically. The results such as current machine running condition and the remaining useful life, are output to the maintenance decision module to determine a window of appropriate maintenance before the machine fails. An application of the method on an elevator door motion system is demonstrated.