An Energy Efficient Architecture for Furnace Monitor and Control in Foundry Based on Industry 4.0 Using IoT

Subash Kumar, C S (2022) An Energy Efficient Architecture for Furnace Monitor and Control in Foundry Based on Industry 4.0 Using IoT. Scientific Programming, 2022: 1128717. pp. 1-8. ISSN 1058-9244

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Abstract

The global standards in the field of industrial automation are maintained in industries by completely digitizing their manufacturing process with industry 4.0 standard. Internet of Things (IoT) enables the conservation of cultural heritage with proper assistance on data management on the data collected from the sensors. However, energy efficient conservation is required to monitor the IoT sensors in order to deal with building a better infrastructure. In this paper, we develop a bio-inspired algorithm which can automate the entire furnace monitoring and controlling system in order to eliminate the human intervention involved in the physical process. The algorithm is blended as a web-based remote application for the better control of the tasks involved, energy utilized, and its subsequent log-report maintenance. The entire system employs Wi-Fi communication for data transfer from device to cloud where the stored data including temperature log, forth coming schedule, and process graphic are maintained by the proposed algorithm to predict the machine failure at an earlier stage. The real-time prototype system is supported by a heat treatment process that is completely automated using IoT to monitor and maintain the temperature during the production of metal casting process.

Item Type: Article
Uncontrolled Keywords: Data transfer; Energy efficiency; Historic preservation; Industry 4.0; Bio-inspired algorithms; Conservation of cultural heritages; Energy efficient; Energy-efficient architectures; Furnace monitoring systems; Global standards; Industrial automation; Manufacturing process; Monitor and control; Monitoring and controlling System
Subjects: A Artificial Intelligence and Data Science > Machine Learning
A Artificial Intelligence and Data Science > Artificial intelligence
C Computer Science and Engineering > Virtual Reality
F Mechanical Engineering > Manufacturing Engineering
Divisions: Electrical and Electronics Engineering
Depositing User: Users 5 not found.
Date Deposited: 28 Jun 2024 06:15
Last Modified: 28 Jun 2024 06:15
URI: https://ir.psgitech.ac.in/id/eprint/659

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