Maintenance And Characterisation Of Rock Well Hardness Testing Machine

Main Article Content

Ubasinachi Osmond Udeh
Emmanuel Sunday Agbo
Nwachukwu Peter Ugwu

Abstract

Rockwell hardness testing machines are crucial in determining material hardness. However, their accuracy and reliability can be compromised if not properly maintained. This project focuses on the rehabilitation and maintenance of the Rockwell hardness testing machine in the Mechanical Engineering Department Caritas University, Amorji Nike, Enugu. The machine’s accuracy and reliability were restored through diagnostic tests, replacement of worn-out parts, calibration, and development of a maintenance schedule.The reliability and functionality of the Rockwell Hardness Testing Machine are critical for material testing and mechanical engineering applications. However, frequent power fluctuations, component wear, and inadequate maintenance practices often compromise the performance of this essential equipment, particularly in educational institutions like Caritas University Amorji Nike Enugu. This study investigates the application of a Fuzzy Logic-Based Static Var Compensator (SVC) to improve the rehabilitation and maintenance of the Rockwell Hardness Testing Machine. The fuzzy-based SVC system is designed to enhance voltage stability, mitigate harmonic distortions, and ensure a consistent power supply to the machine. By integrating intelligent control algorithms, the system can predict and adapt to varying operational conditions, enabling proactive maintenance and reducing the likelihood of system failures. This approach not only safeguards sensitive components from power-related damages but also extends the machine’s operational lifespan and minimizes downtime. The study employs a combination of experimental analysis and simulation to evaluate the performance of the fuzzy-based SVC system. Results demonstrate significant improvements in power quality, reduced maintenance costs, and enhanced operational reliability of the Rockwell Hardness Testing Machine. The findings underscore the potential of intelligent power systems in modernizing equipment maintenance practices and ensuring sustainable engineering education.

Article Details

Section
CJET Volume 4 Issue 1
Author Biographies

Ubasinachi Osmond Udeh

Department of Mechanical Engineering,

Caritas University Amorji-Nike, Emene, Enugu State Nigeria

Emmanuel Sunday Agbo

Department of Mechanical Engineering,

Caritas University Amorji-Nike, Emene, Enugu State Nigeria

Nwachukwu Peter Ugwu

Department of Mechanical Engineering,

Caritas University Amorji-Nike, Emene, Enugu State Nigeria

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