**Abstract**

The fourth industrial revelation has brought exponential technologies in the area of digitization, internet of things (IOT), artificial intelligence (AI), and optimization which has helped mining companies to increase the availability and utilization of equipment's. As mining companies implement predictive maintenance technologies, to improve overall equipment availability, there is more value to be unearthed if predictive maintenance is optimized with the production schedules. Ant colony optimization (ACO) is a metaheuristic that is inspired from the behavior of real ants to solve combinatorial optimization problems. This chapter describes an innovative maintenance scheduling framework in the context of optimizing schedules for preventive maintenance and predictive maintenance, with multiple constraints for optimized dynamic schedule to reduce the maintenance time, and production losses.

**Keywords:** ant colony optimization, predictive maintenance, preventive maintenance, mining, schedule, optimizing mining equipment schedule
