Automation of industrial machinerie
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2023.14.2.41Keywords:
Programmable logic controller, Human-machine interface, Variable-frequency drive, Internet of things, Virtual machines, Arduino.Dimensions Badge
Issue
Section
License
Copyright (c) 2023 The Scientific Temper
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
In past two decades, the automation of industrial machines is proliferating. Fourth industrial revolution (Industry 4.0) also focuses on industrial automation and artificial intelligence. As every technology has its ebb and flow, industrial automation also has huge scope in future and its own limitations. One of the major issues is in troubleshooting the virtually controlled machine. The biscuit making and baking machines are controlled using PLC I/O and HMI. The errors are rectified by taking feedback from machine’s component connections and supply connections. This helps us in troubleshooting the faults occurring in the connections and components used.Abstract
How to Cite
Downloads
Similar Articles
- A. Sandanasamy, P. Joseph Charles, Distributed SDN control for IoT networks: A federated meta reinforcement learning solution for load balancing , The Scientific Temper: Vol. 16 No. 06 (2025): The Scientific Temper
- Sanjeev Kumar, Saurabh Charaya, Rachna Mehta, Multi-Metric Evaluation Framework for Machine Learning-Based Load Prediction in e-Governance Systems , The Scientific Temper: Vol. 17 No. 01 (2026): The Scientific Temper
- Priscilla I, Jayasimman Lawrence, Enhanced Symmetric Cryptography Technique (ESCTGPU) for Secure Communication between the IoT Gateway and the public Cloud Environment , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- V. Umadevi, S. Ranganathan, IoT based energy aware local approximated MapReduce fuzzy clustering for smart healthcare data transmission , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Kinjal K. Patel, Kiran Amin, Predictive modeling of dropout in MOOCs using machine learning techniques , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Gomathi Ramalingam, Logeswari S, M. D. Kumar, Manjula Prabakaran, Neerav Nishant, Syed A. Ahmed, Machine learning classifiers to predict the quality of semantic web queries , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- R. Kalaiselvi, P. Meenakshi Sundaram, Unified framework for sybil attack detection in mobile ad hoc networks using machine learning approach , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- M. Iniyan, A. Banumathi, The WBANs: Steps towards a comprehensive analysis of wireless body area networks , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Panda Aditi Ambarish, Kaushik Trivedi, Immersive learning: A virtual reality teaching model for enhancing english speaking skills , The Scientific Temper: Vol. 15 No. spl-2 (2024): The Scientific Temper
- G. Deena, K. Raja, M. Azhagiri, W.A. Breen, S. Prema, Application of support vector classifier for mango leaf disease classification , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
<< < 2 3 4 5 6 7 8 9 10 11 > >>
You may also start an advanced similarity search for this article.
