Industrial Maintenance Planning and Scheduling with AI, ML & Mathematical Optimization

Changing consumer and business behavior in the post-Covid world has led to huge shifts in industrial equipment usage patterns. Whether the assets comprise power plants, utility grids, escalators or aircraft – these changes have forced organizations to rethink the way they plan and schedule their asset maintenance and repair activities. As a result of these drivers, organizations are accelerating their adoption of technology, such as computerized maintenance management systems (CMMS), IoT sensors and advanced artificial intelligence (AI) technologies, including machine learning and mathematical optimization. In this talk, we draw from real-world experience helping organizations in multiple industries improve their maintenance planning and scheduling processes to leverage advanced decision support software for planning and scheduling that leads to: 1) Reducing reactive repair call volume 2) Increasing productivity, and 3) Lowering equipment downtime