Chapter an explanation of the approach which is used

Chapter Three

 Research Methodology

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3.1
Introduction

 

This
chapter presents an explanation of the approach which is used to achieve the aims
of the research. It includes the description of the place, data collection, and
the flowchart of research methodology and analysis procedures.

 

3.2
Description of the place

 

This
research is conducted in the west Doha PPWD. It is located in Kuwait. It is an oil
type power plant with a design capacity of 2400 Mega Watt (MW).
It has 8 units. The first unit was commissioned in 1982 and the last one in
1984. It is operated by the Ministry of Electricity
and Water (MEW) in Kuwait (www.globalenergy.org/geoid).

 

3.3
Data Collection

 

The
major source of the data collection was the maintenance department historical
data which were obtained from the job orders
between (2012- 2017). 6055 job orders were analyzed, each job order contains
information pertaining to the dates of failure occurrence and repair, details
of maintenance works, and the name of failed item. Another source of the data
collection was interviewing the maintenance staff and asking them about the
nature of major challenges faced in their work and their proposing (based on
the experience) recommendations for solving these challenges.

 

3.4 Flowchart of
research methodology

 

This research
represents a case study of investigating and
managing the maintenance processes of the (ACs) in the west Doha PPWD in
Kuwait. The following Figure 3-1

illustrates
the steps to be implemented in the research.

 

Figure 3-1: Research methodology

 

The above figure shows that the first step in conducting the
research is studying the numbers and frequencies of the failures in the ACs in the
west Doha PPWD in the period (2012-2017). There are some maintenance related
parameters to be investigated and analyzed in the research. The first parameter
to be investigated is the MTBF. It represents a reliability concept which is
applied in many applications of industries. It was defined as the prediction of
the random variable which keeps track of the succeeding happening of a system failure Ghazizadeh, Florin, Zadeh, & Olariu (2015).
Another maintenance parameter which will be analyzed is the MTTR. It was
defined as the anticipated time to recover a system from a failure. It includes
its failure diagnosis time, time needed for bringing the repair technician
onsite, and its repairing time Torell (2004). The following parameters which
will be studied will be the availability and the reliability of the maintenance
system in the west Doha PPWD. The definition of the availability is the operational
and accessibility degree of a system or component when being demanded for use.
While the reliability is defined as the capability of a system or component to do
the demanded tasks under certain circumstances for a certain time interval (Torell,
2004). All the mentioned analysis will be conducted through performing Pareto
chart analysis to determine the failures which are responsible of 80% of the
total failures.

After finishing the analysis of the failures, the following
analysis will handle the highest maintenance costs. This will be achieved
through performing Pareto chart analysis to determine the costs which are
responsible of 80% of the total maintenance costs. After that, Ishikawa diagram
will be deployed to illustrate the root causes of these 80% failures and costs
which were investigated in the last two previous steps. The final step in the
methodology will be the presenting of the recommendations to improve the
current maintenance system at west Doha PPWD by proposing a solutions for the
major failures and costs.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

References

 

Ghazizadeh, P., Florin, R., Zadeh,
A., & Olariu, S. (2015). Reasoning about Mean Time to Failure in Vehicular
Clouds, IEEE Transactions on Intelligent Transportation Systems.

Torell, W., and Avelar, V. (2004).
Mean Time Between Failure: Explanation and Standards. White Paper 78, Schneider
Electric – Data Center Science Center.

www.globalenergyobservatory.org/geoid/2952

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