Heat Exchanger IoT Predictive Maintenance



Hau, Han Ming (2019) Heat Exchanger IoT Predictive Maintenance. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Kian Joo Group is the largest Processed Food Can Manufacturer in Malaysia. They product manufacturing by Kian Joo include 2-piece and 3-piece cans with distorted printing. Recently, Kian Joo Group started a program on implementing Industry 4.0 into their factory. One part of this program will be implementing smart heat exchanger monitoring system into the heat exchanger used to cool down UV lamp in 8 color printing line in plant 3 in Batu Cave. This project aim to improve performance monitoring system of heat exchanger in Kian Joo Can Factory to increase productivity and reduce maintenance costs. This project involve important element if industry 4.0 which is Big Data Analysis and Internet of Thing (IoT). In the existing system, data like temperature and pressure is measured by sensor installed in heat exchanger and show the data detected on control panel. However, this system is not good enough to track the heat exchanger performance and accurately determine the type of failure causing the issue. To improve the existing system, smart sensors is installed at more location of cooling system and data channeling architecture using Open Protocol Communication (OPC) will be built to allow constant monitor essential production line equipment and the production status. The data detected will then be recorded and transmitted in real-time to the cloud. By using the cloud data, graph will be plotted and be used for analysis on the heat exchanger’s performance. This makes study on performance trend easier and makes predictive maintenance analysis possible. The ultimate goal of this project is to predictive maintenance required for the heat exchanger allows the maintenance frequency to be as low as possible to prevent unplanned reactive maintenance. Predictive maintenance evaluates the condition of equipment by performing periodic (offline) or continuous (online) equipment condition monitoring.

Item Type: Final Year Project
Subjects: Technology > Mechanical engineering and machinery
Faculties: Faculty of Engineering and Technology > Bachelor of Engineering (Honours) Mechanical
Depositing User: Library Editor
Date Deposited: 15 Jan 2020 07:44
Last Modified: 15 Jan 2020 07:44
URI: https://eprints.tarc.edu.my/id/eprint/12855