When you develop solutions for predictive maintenance, one of the challenges is being caught between the people who design/build the machines, and the people who service machines. Whatever you build has to provide business value without stepping on the feet of either of those parties. In this article I’m going to try and provide insight into what it means to walk this line.
Predictive Maintenance is fundamentally about two goals - keeping your machines running, and making them run in the best way possible. In other words, focus on reducing downtime and continuously optimizing how your machines run. The concept of downtime is easy to describe and understand, but calculating it can be much more complex than people realize. In this post I’ll walk through calculating downtime for a factory machine, and how the complexity of the calculation reveals why using predictive models for predictive maintenance is so challenging.
People often underestimate how false alarms from predictive models can erase all the business value you set out to create from those models. In this post we will explore how label noise can drive up your service costs instead of decreasing it, and how a small fraction of incorrect predictions of impending machine issues can erase all the benefit created by correct predictions.
When conceptualizing and implementing a predictive maintenance project, it can be hard to grasp the entire chain of people and technology needed for success. In this post I’ll try to break down all the people and teams needed for this type of project, and also provide insight into how these people work together.
One mistaken assumption I see people make with predictive maintenance programs is that the cost savings of many lower value projects will add up to a big number, so it’s worth putting in the effort. But sometimes saving a million dollars isn’t worth it if it costs you more than that to implement it. In this post we’ll look at four types of programs and understand why some of them aren’t worth doing because they have a negative return-on-investment (ROI)