Open AccessOverall Equipment Utilisation (OEU) Monitoring and Remote Quality Check in Legacy Machine with Raspberry Pi
Author(s) -
Siti Nurul Huda Abd Rahim,
Abd Halim Embong
Publication year - 2021
Publication title -
journal of integrated and advanced engineering
Language(s) - English
Resource type - Journals
eISSN - 2774-6038
pISSN - 2774-602X
DOI - 10.51662/jiae.v1i2.26
Subject(s) - optical character recognition , computer science , benchmark (surveying) , raspberry pi , classifier (uml) , word error rate , artificial intelligence , graphical user interface , artificial neural network , real time computing , embedded system , operating system , internet of things , geodesy , image (mathematics) , geography
Overall Equipment Utilisation (OEU) plays an important role as a benchmark for manufacturing companies to determine each machine's efficiency. Currently, there is no proper OEU measurement system in legacy machines and only relies on human observation. This project aims to develop a measurement of OEU system by using Optical Character Recognition (OCR). An efficient Optical Character Recognition (OCR) algorithm is needed to have a high percentage of recognition rate. The outcome of this project will be a Graphical User Interface (GUI) that display real-time OEU monitoring and remote quality check for legacy machines. Pytesseract-OCR Version 4 classifier using the Recurrent Neural Network (RNN) method has been proposed in this paper. Furthermore, an error detection feature is designed from OCR output.