Thursday 28th of March 2024
 

Implementing an Expert Diagnostic Assistance System for Car Failure and Malfunction


Salama A. Mostafa, Mohd Sharifuddin Ahmad, Mazin Abed Mohammed and Omar Ibrahim Obaid

Applications in fault diagnosis are continuously being implemented to serve different sectors. Car failure detection is a sequence of diagnostic processes that necessitates the deployment of expertise. The Expert System (ES) is one of the leading Artificial Intelligence (AI) techniques that have been adopted to handle such task. This paper presents the imperatives for an ES in developing car failure detection model and the requirements of constructing successful Knowledge-Based Systems (KBS) for such model. In addition, it exhibits the adaptation of the ES in the development of Car Failure and Malfunction Diagnosis Assistance System (CFMDAS). However, CFMDAS development faces many challenges such as collecting the required data for building the knowledge base and performing the inferencing. Furthermore, diagnosis of car faults requires high technical skills and experienced mechanics who are typically scarce and expensive to get. Thus, systems such as CFMDAS can be highly useful in assisting mechanics for failure detection and training purposes. Moreover, capturing and retaining valuable knowledge on such domain yield more accurate and less time consuming models.

Keywords: Expert system (ES), Artificial Intelligence (AI), car fault, Knowledge-Based System (KBS), Inference engine.

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ABOUT THE AUTHORS

Salama A. Mostafa
Ph.D student, College of Graduate Studies, Universiti Tenaga Nasional.

Mohd Sharifuddin Ahmad
Assoc. Prof. Dr., College of Graduate Studies, Universiti Tenaga Nasional.

Mazin Abed Mohammed
M.Sc. student, College of Graduate Studies, Universiti Tenaga Nasional.

Omar Ibrahim Obaid
M.Sc. student, College of Graduate Studies, Universiti Tenaga Nasional.


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