A Systematic Review of Conventional and Industry 4.0-Based Approaches for Downtime Reduction and Yield Improvement in Continuous Casting Operations

Abstract

Continuous casting is a critical process in steel manufacturing that directly influences productivity, product quality, and operational profitability. Frequent downtime, equipment failures, process interruptions, and billet quality defects significantly reduce production efficiency and yield. This review systematically examines conventional approaches such as Preventive Maintenance, Reliability-Centered Maintenance (RCM), Total Productive Maintenance (TPM), Lean Manufacturing, Kaizen, Six Sigma, and Overall Equipment Effectiveness (OEE) for downtime reduction and yield improvement. Furthermore, recent Industry 4.0 technologies including Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Predictive Maintenance, Big Data Analytics, Cyber-Physical Systems, and Digital Twin technology are critically analyzed for their role in enhancing continuous casting operations. The review highlights the advantages, limitations, and industrial applications of both conventional and smart manufacturing approaches. Research trends, technological advancements, and existing research gaps are identified to support future developments in intelligent steel manufacturing. The study concludes that integrating conventional maintenance strategies with Industry 4.0 technologies offers significant potential for reducing downtime, improving billet yield, enhancing equipment reliability, and maximizing industrial profitability.

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