International Journal of Science, Engineering and TechnologyAuthors: Sandbhor Atharva Vikas, Prof. S. R. Borhade, Prof. M. C. Kolse, Prof. S. K. Said
Abstract: Artificial intelligence is changing how industries design, produce, maintain and deliver products. This paper reviews AI in industrial operations within the Industry 4.0 paradigm, where cyber-physical systems, the industrial Internet of Things and data analytics connect machines, processes and people. It examines four major application areas: predictive maintenance, which uses vibration, temperature and current signals to estimate machine health and remaining useful life; automated visual quality inspection, which uses deep learning and unsupervised anomaly detection to find defects; demand and inventory forecasting with probabilistic deep learning models; and digital twins that mirror physical assets for monitoring and optimization. Supporting topics such as robotics, workplace-safety monitoring and the cross-domain use of AI for information verification and security are discussed briefly. A five-layer industrial AI architecture comprising the shop-floor, industrial IoT, data platform, AI services and enterprise decision layers is proposed, together with research gaps, objectives, a comparison of application areas and challenges such as data quality, legacy equipment, cybersecurity, skill shortages, cost and over-reliance on automation. The review concludes that AI delivers the greatest value when it is integrated with domain knowledge and human oversight.
DOI: https://doi.org/10.5281/zenodo.24214956
