AI-Powered Predictive Analytics for Vehicle Maintenance Scheduling

Abstract

Vehicle maintenance scheduling is an important aspect of the automotive industry. With advancements in technology, one needs to relook at the existing practices on why there is a necessity to transform from traditional schedules to advanced technological solutions. Regular and periodic overhauls, as per the manufacturers' recommendations, can sometimes be costly with respect to both the impact of increased downtime of the vehicle, reduced span between service cycles due to harsh environmental conditions, and the cost of maintenance. This becomes more challenging when one needs to manage a fleet of vehicles with different configurations and road conditions. Predictive maintenance can be a critical strategy for rolling stock acceptance as it enhances not only the operational reliability based on actual conditions but also ensures that services are not missed during operations, helping to reduce delays. Maintenance of vehicles is now equipped with AI tools to predict and extend the life of the components without facing operational disruptions. The importance of predictive technologies in vehicle maintenance scheduling and their advantages are depicted in a figure. It focuses on addressing the existing concepts and developments in integrating artificial intelligence in vehicles, predictive maintenance, and other techniques. The text explains maintenance in the automotive field, including preventive, predictive, and prescriptive maintenance, as well as the necessity for predictive maintenance. It explains predictive transformations in the automotive system, especially in passenger cars and trucks. The section exhibits existing repair methods from the above technologies. Other concepts explain fault detection techniques for major components of the vehicle and reliability analysis. The case study focuses the attention of the readers on how big data redefines the maintenance scenario with the help of AI methods in the automotive field. Conclusions about choosing AI can be confusing with respect to the industries and organizations due to the benefits of cost. Forming the perfect data sets and working on AI algorithms will yield significant results. In the future, AI automotive tools would be a game changer in all fields, not only in the automotive industry.