Hydrocarbon Processing - February 2021 - GP-29

TURBOMACHINERY

TABLE 4. Instantaneous availability results for the studied turbine
t, hr

D(t)

0.193

0.088

0.0427

0.0231

0.0147

0.0111

0.0095

0.0088

0.0085

0.0084

0.0083

TABLE 5. ABC Pareto analysis of the studied gas turbine
Item

Order of
intervention

Nature of intervention

Downtime, hr

Downtime, %

Cumulative
downtime, %

Category*

Problem related to the lubrication circuit

270

31.8

Problem related to the air circuit

216

25.4

57.2

Problem related to the communication module

10.6

67.8

Pump change

8.5

76.2

Cleaning

5.6

81.9

Sensor change (flame detector)

5.6

87.5

Clamping bolts

5.6

93.2

Battery change

2.8

Change of bottles (CO2)

2.8

98.8

Welding at chimney level

1.2

100

850

100

Total

*Category A: Approximately 20% of the causes in this category represent 57.2% of the hr of shadow, which constitutes zone A (problems related to the lubrication circuit
and the air circuit)
Category B: Approximately 30% of the causes represent an additional 24.7% (problems related to the communication module, pump and cleaning)
Category C: Approximately 50% of the remaining causes represent only 18.1% of the shutdown hr (change of sensor, tightening of bolts, change of batteries, change of bottles,
welding at chimney)

* Check the reliability of other
systems with links to turbine
equipment. GP
ACKNOWLEDGMENTS
This work was supported by the Applied
Automation and Industrial Diagnostics Laboratory
with the Gas Turbine Joint Research Team at the
University of Djelfa in Algeria. The authors express
their sincere thanks to the staff of the Menia-Ghardaia
power station for their kind hospitality during the realization of this work.
LITERATURE CITED
1
Zohair, A., A. Hafaifa and S. Abudura, " Operational
reliability analysis applied to a gas turbine based
on three-parameter Weibull distribution, " Mechanics,
Vol. 21, Iss. 3, 2015.
2
Saranyasoontorn, K. and L. Manuel, " Efficient models for wind turbine extreme loads using inverse
reliability, " Journal of Wind Engineering and Industrial
Aerodynamics, Vol. 92, April 2004.
3
Meslameni, W., " Optimization of maintenance times
of a gas turbine, " International Journal of Applied
Research and Technology, Vol. 1, 2018.
4
Shen, M. H. H., " Reliability assessment of high cycle
fatigue design of gas turbine blades using the probabilistic Goodman diagram, " International Journal of
Fatigue, Vol. 21, Iss. 7, August 1999.
5
Naikan, V. N. A. and S. Kapur, " Reliability modelling
and analysis of automobile engine oil, " Journal of
Automobile Engineering, Vol. 220, December 2004.
6
Rausand, M., " Reliability centered maintenance, "
Journal of Reliability Engineering and System Safety,
Vol. 60, 1998.
7
Zhang, J., Y. Zhao and M. Xiaobing, " Reliability
modeling methods for load-sharing k-out-of-n sys-

tem subject to discrete external load, " Journal of
Reliability Engineering and System Safety, Vol. 193,
August 2019.
8
Glovatskii, O.-Y., " Operating experience and reliability assessment of elements of pumping stations, "
Journal of Hydrotechnical Construction, Vol. 23, Iss. 9,
September 1989.
9
Zhejun, G., " Estimation of mixed Weibull distribution parameters using the SCEM-UA algorithm:
Application and comparison with MLE in automotive reliability analysis, " Journal of Reliability
Engineering & System Safety, Vol. 91, Iss. 8, August
2006.
NADJI HADROUG is an Associate
Professor with the faculty of science
and technology at Djelfa University
in Algeria, as well as a member of
Djelfa University's Applied
Automation and Industrial
Diagnostics Laboratory. He received
his PhD from the University of Ziane Achour in
Djelfa, Algeria. His work focuses on the development
of new methods and tools in fault-tolerant control for
industrial systems, and his research interests include
the monitoring and control of industrial gas turbine
systems. Dr. Hadroug is the author and co-author of
several publications and conference papers.
AHMED HAFAIFA is a Full
Professor in industrial automation
and diagnosis and reliability
engineering at the University
of Djelfa in Algeria, where he
conducts research work in applied
automation and industrial
diagnostics. He also serves as the Dean of the
Science and Technology Department and the
Director of the Applied Automation and Industrial

Diagnostic Laboratory at the University of Djelfa.
Dr. Hafaifa additionally leads the Gas Turbine Joint
Research Team in support of several international
research projects in the industrial sector. His research
interests include control in industrial systems,
reliability engineering, fault detection and isolation
in industrial processes and intelligent systems based
on fuzzy logic and neural networks. He has also
published a number of papers in industry journals.
MOSTEFA TELHA is a Professor in
the mechanical department of the
science and technology faculty at
Djelfa University in Algeria. He is
preparing his PhD in fluid
mechanics at the University of
Laghouat in Algeria. He is an
engineer in industrial maintenance, and his work
focuses on energy systems and the maintenance
and diagnostics of mechanical systems.
ABDELHAMID IRATNI is an
Associate Professor in control
engineering and automation
systems in the electrical
engineering department of the
faculty of science and technology
at the University of Bordj Bou
Arréridj in Algeria. He has served as the Chair of
the scientific committee of the electrical engineering
department since 2019, after serving as the head
of the bachelor's and master's programs since 2015.
Dr. Iratni received his BSc and MSc degrees in
electrical engineering from the University of
Boumerdes in Algeria in 1999 and 2003, respectively.
He received his PhD from the University of Sétif in
Algeria in 2013. His research areas include nonlinear
filtering, estimation and control, biomedical and
bioprocess engineering, and automation and
reliability of industrial systems.

Gas Processing & LNG | JANUARY/FEBRUARY 2021 29

Hydrocarbon Processing - February 2021

Table of Contents for the Digital Edition of Hydrocarbon Processing - February 2021