Smart manufacturing 4.0: Integration of artificial intelligence for real-time process control and productivity enhancement
Chandra Sekar T, Irshadullah Asim MOHAMMED, B. GANGADHAR, Syed Hassan Imam GARDEZI, Maddikera Kalyan CHAKRAVARTHI, Pramod KUMAR
Abstract. The proliferation of interlinked industrial devices at an exponential rate in the Industry 4.0 paradigm has produced volumes of real-time manufacturing information not seen before, creating a need and opportunity to establish intelligent process control. This article suggests a new hybrid artificial intelligence system of smart manufacturing, combining Long Short-Term Memory (LSTM) networks, Convolutional Neural Networks (CNN), ensemble tree-based classifiers, and a Proximal Policy Optimization (PPO)-based Reinforcement Learning (RL) agent in a four-layer system that includes data acquisition, AI processing, decision control, and feedback actuation. The framework is tested on the SECOM semiconductor manufacturing data with added synthetic CNC machining data, where a fault detection accuracy of 96.7, an Overall Equipment Effectiveness (OEE) of 91.8 and a defect rate is reduced by 6.8 to 1.1 compared to traditional Statistical Process Control (SPC) baselines. Latency of inference 44 ms meets hard real-time requirements in manufacturing. The superiority and generalizability of the proposed approach are supported by the results of comparative analysis against six state-of-the-art methods. The findings indicate that predictive modeling, computer vision and adaptive closed-loop control in a synergistic combination is a viable scalable route to intelligent manufacturing excellence.
Keywords
Smart Manufacturing, Industry 4.0, Artificial Intelligence, Real-Time Process Control, Predictive Maintenance, Reinforcement Learning, Convolutional Neural Network
Published online 8/15/2026, 7 pages
Copyright © 2026 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Chandra Sekar T, Irshadullah Asim MOHAMMED, B. GANGADHAR, Syed Hassan Imam GARDEZI, Maddikera Kalyan CHAKRAVARTHI, Pramod KUMAR, Smart manufacturing 4.0: Integration of artificial intelligence for real-time process control and productivity enhancement, Materials Research Proceedings, Vol. 71, pp 176-182, 2026
DOI: https://doi.org/10.21741/97816449042312-24
The article was published as article 24 of the book AI-Driven Innovations in Mechanical, Manufacturing, and Energy Engineering
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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