Expert PC Troubleshooter With Fuzzy-Logic And Self-Learning Support

TL;DR

This paper introduces an expert system for diagnosing PC problems that integrates fuzzy logic and self-learning features to automate troubleshooting and reduce human technician workload.

Contribution

It presents a novel expert system architecture combining fuzzy logic and intelligent agents for automated PC fault diagnosis.

Findings

Effective diagnosis of POST beep errors using fuzzy logic

Automates routine maintenance tasks to save technician time

System architecture supports future parallelization for improved performance

Abstract

Expert systems use human knowledge often stored as rules within the computer to solve problems that generally would entail human intelligence. Today, with information systems turning out to be more pervasive and with the myriad advances in information technologies, automating computer fault diagnosis is becoming so fundamental that soon every enterprise has to endorse it. This paper proposes an expert system called Expert PC Troubleshooter for diagnosing computer problems. The system is composed of a user interface, a rule-base, an inference engine, and an expert interface. Additionally, the system features a fuzzy-logic module to troubleshoot POST beep errors, and an intelligent agent that assists in the knowledge acquisition process. The proposed system is meant to automate the maintenance, repair, and operations (MRO) process, and free-up human technicians from manually performing routine, laborious, and timeconsuming maintenance tasks. As future work, the proposed system is to be parallelized so as to boost its performance and speed-up its various operations.