Smart Factory Part 2: Predictive Maintenance for Industrial Robotics

A predictive approach to maintenance operations guarantees advantages such as reducing machine downtime, eliminating unnecessary interventions, and adding revenue streams for equipment vendors with aftermarket services. These benefits are achievable, but there are challenges in implementing predictive maintenance in application fields such as industrial robotics. One obstacle is the limited availability of functioning data and the lack of failure data needed for accurate results. In addition, choosing the best models for monitoring and prediction can be time consuming, and integrating devised algorithms with existing tools and infrastructures can cause a bottleneck in the implementation process. In this talk, we will analyze the benefits and challenges of predictive maintenance, and describe, via the exploration of a real case-study, the solution proposed by MathWorks to overcome these obstacles and realize efficient predictive maintenance systems.