Author : Asst. Prof. Dr. Nazhaat S. Abdul Razaaq and Mustafa T. Salih

There are many people who do not have any experience in locating the car malfunction, and it is known that the
malfunction can occur anywhere and at any time and the car may be in a place where it is difficult for the mechanic
to arrive for the purpose of maintenance on the car. In this thesis, a system was developed for the purpose of
diagnosing mechanical and electrical vehicle failures, which in turn helps inexperienced people diagnose car
malfunctions in the event of a sudden malfunction in their cars. The proposed system in diagnosis consists of two
parts, the first part in the collection of the largest number of faults and causes and create a table for these reasons
where collected from sources in mechanical engineering, which numbered 320 malfunctions and then process this
table using the algorithm Particle Swarm Optimization (PSO), where this algorithm extracted the most common
faults, which numbered 231 types of faults i.e. 1386 rule or cause. The second part of the research is the applying of
the Expert System to the data generated by the PSO process. The expert system works as follows, which is to display a set of questions to the user which through the user’s answers the system can determine the location of the fault and also how to fix it.

Keywords: E-Service, Expert System, Car’s Faults Diagnosis, PSO

Article published in International Journal of Current Engineering and Technology, Vol.10, No.6 (Nov/Dec 2020)