AI- and IoT-Based CNC Optimization for Sustainable Production

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Authors: Kali Charan Rath, Kamalakanta Muduli, Manas Ranjan Panda, Gopal Krushna Mohanta, Sasank Sekhar Panda
Cited by: 1

Abstract

Manufacturing is being transformed by Industry 4.0, which uses advanced technologies like Internet of Things (IoT) and artificial intelligence (AI) to make it more efficient and environmentally benign. Computer numerical control (CNC) systems are essential to contemporary production, and this chapter explains various investigations about how these technologies can revolutionize them. The study presented created an AI-powered optimization system that gathers and analyzes real-time data from CNC machines using IoT sensors. This innovative approach aims to increase operational efficiency, decrease waste, and promote sustainable manufacturing practices. The ability of CNC machines to adapt and operate more efficiently is enabling smarter, cleaner production processes. This chapter presents research that could benefit several industries and is a significant step toward more ecologically friendly production. The main goal is to create a reliable system that supports sustainable production objectives by enhancing machining accuracy, lowering energy usage, and minimizing material waste. Because it integrates AI and IoT technologies for CNC optimization holistically, this research is unique. It goes beyond traditional methods to incorporate energy-efficient machining techniques, adaptive control, and predictive maintenance. The outcomes show how AI and IoT have the potential to completely transform CNC machining by demonstrating notable gains in sustainability metrics and production efficiency. Consequently, this work highlights the significance of advanced technologies in achieving sustainable production and provides a model for future research and industry applications in smart manufacturing environments.

Fields of Study & Subjects

Advanced machining processes and optimization Digital Transformation in Industry Energy Efficiency and Management

Publication details

Journal / source
AIoT-Driven Sustainable Manufacturing and Operational Initiatives
Publisher
CRC Press
Pages
118–138
Publication date
27 January 2026
Language
EN
Document type
Book chapter