 Maintenance of production equipment plays a crucial role in ensuring business continuity and productivity. To ensure successful maintenance, it is important to determine the implementation time and select the appropriate scope of maintenance activities. Studies have been conducted in recent years to apply artificial intelligence, AI, techniques to model and manage maintenance. These studies aim to anticipate potential failures and respond to them in advance through timely maintenance activities. Computational analysis and simulation based on real industrial data sets were used to evaluate the effectiveness of these approaches. The results showed that effective use of preventive maintenance requires large amounts of reliable sensor data and well-trained machine learning algorithms. Companies of all sizes and with various production profiles could benefit from these solutions, which offer high efficiency at low implementation costs. This article was authored by Isabella Rojek, Malgorzata Jacejewicz Kezmarak, Mariusz Pichowski, and others. We are article.tv, links in the description below.