Artificial intelligence based predictive maintenance application

When it comes to the efficiency of production systems, maintenance approaches play an extremely important role. Although traditional maintenance approaches have achieved limited success, today's industrial technologies, particularly the driving force of Industry 4.0, enable data to be read in real time from machines according to specific standards. Following the development of the Internet of Things (IoT), it has become widely used in the industrial sector. Thanks to IoT, when data such as temperature, humidity, and vibration is collected and processed from any equipment or system, it provides important information about the equipment's lifespan. This collected data can be used with machine learning (ML) methods to minimise maintenance times and predict failure periods, enabling intervention before failures occur. This strategy, known as predictive maintenance, offers advantages in terms of time and cost.