Synergizing Smart Sensors and Artificial Intelligence for Maintenance 4.0: A Critical Review and Future Paradigms

Abstract

Various industrial equipment relies on complex mechanisms to maintain high production efficiency and consistent product quality. However, frequent equipment failures and maintenance issues caused by mechanical wear can lead to costly downtime, also quality fluctuations. Traditional maintenance methods such as preventive or reactive maintenance, often fail to predict failures accurately, resulting in ineffective strategies. The integration of smart sensor technologies is revolutionizing maintenance and repair of various equipment. These sensors continuously analyse equipment parameters such as temperature, vibration, pressure, and humidity. The aim of using sensors is to provide real-time monitoring, predictive maintenance, and fault detection. Using the Internet of Things (IoT) and Artificial Intelligence (AI), sensors increase operational efficiency, reduce maintenance costs, and extend lifespan. This study explores the key components, sensor types, predictive maintenance approaches, advantages, drawbacks, and future trends.