Parameters Monitoring Automation Kiln Manufacture Based Optical Character Recognition (OCR) with The Template Matching Method

Authors

  • Agustia Hananto Information and Communication Technology, Asia E University, Malaysia
  • Titik Khawa Abdul Rahman Information and Communication Technology, Asia E University, Malaysia
  • Goenawan Brotosaputro Faculty of Information Technology, Universitas Budi Luhur, Indonesia
  • Ahmad Fauzi Faculty of Computer Science, Universitas Buana Perjuangan Karawang, Indonesia
  • April Lia Hananto Faculty of Computer Science, Universitas Buana Perjuangan Karawang, Indonesia
  • Bayu Priyatna Faculty of Computer Science, Universitas Buana Perjuangan Karawang, Indonesia

Keywords:

Digital Image, Optical Character Recognition, Kiln Manufacturing, Early warning

Abstract

One of the pieces of equipment used in the combustion-based process of creating ceramic tiles is a kiln production machine or oven. To make sure the combustion process runs smoothly, 39 parameters on the kiln engine are closely monitored, and it is manually determined if the value of these parameters exceeds the minimum or maximum limits based on the data produced by the image on the kiln engine. Losses for the company are caused by human error, carelessness, and other characteristics while these metrics are being monitored. In order to minimize losses, a monitoring system that can automate the settings of ceramic tile combustion engines is required. The initial analysis's findings are obtained using a LAN (Local Area Network) sensor recorder, which displays parameter data that can be accessed as an image rather than as digital alphanumeric data that cannot be processed directly and must instead be converted into alphanumeric data as a data source. The image is turned into alphanumeric data using the template matching technique introduced with optical character recognition (OCR), and the generated data is then compared with the given minimum or maximum parameter values. This gadget will issue an early warning message if the conversion result is more than the minimum or maximum limit. The system prototype used in this study for converting image data into alphanumeric data achieved an accuracy of 100.00% and was able to send early warning notifications in accordance with parameters that were above the established minimum or maximum limits.

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Published

17.05.2023

How to Cite

Hananto, A. ., Abdul Rahman, T. K. ., Brotosaputro, G. ., Fauzi, A. ., Hananto, A. L. ., & Priyatna, B. . (2023). Parameters Monitoring Automation Kiln Manufacture Based Optical Character Recognition (OCR) with The Template Matching Method. International Journal of Intelligent Systems and Applications in Engineering, 11(6s), 621–635. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2896

Issue

Vol. 11 No. 6s (2023)

Section

Research Article

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