IOT Based Palm Oil Mill Automation In Monitoring Oil Extraction Rate

Hon, Jessica Siau Chieh (2020) IOT Based Palm Oil Mill Automation In Monitoring Oil Extraction Rate. Final Year Project, UTAR.

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Abstract

Oil extraction rate (OER) can be used to assess the efficiency or profitability of a palm oil mill, in which it measures the crude palm oil (CPO) extraction output against the fresh fruit bunches (FFB) of oil palm input into the mill. Nowadays, the oil level monitoring system is based on manual way by using a sounding meter to measure the oil in the storage tank. This manual method can cause a less accurate data acquisition in addition to the waste of time and manpower in executing the task. This method also causes loss of oil in factory due to smuggling or stealing of oil by the workers, which cause losses to the company. Hence, an IoT based palm oil extraction rate monitoring system was developed for heating palm oil in storage tank which considered the effect of temperature on the volume expansion of the tank under heating, density properties of the oil and the content of the oil varying with temperature. The oil storage tank would experience expansion during heating while the varying temperature could cause hydrolysis or solidification of oil. This project used ultrasonic level sensor connected to Arduino UNO for oil level measurement. The upload of raw data to ThingSpeak server via ESP8266 Wifi module, and further data analysis and real-time data display in Microsoft Power BI were successful. The experiment was carried out and the system prototype showed promising result which established the significant impact of the factor of tank expansion and palm oil density properties during heating on the weight of extracted oil and OER. The results further demonstrated the financial loss to the palm oil mill of 14.20% of the total production. Therefore, the system can be applied as a part of palm oil mill automation system to reduce the substantial production loss from a business perspective.

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