Most experienced maintenance engineers already have a detailed mental picture of the machinery they care for. They know whether a rattling valve means a breakdown is imminent, for example, or if it is safe to ignore it until the next scheduled shutdown. If a predictive maintenance system can tap into this pool of knowledge, it can learn to provide the best possible support in the decision-making process.
Download our free white paper to learn:
- The importance of a user-centric approach to predictive maintenance
- What lessons we can learn from other industries
- How Senseye focuses on meaningful outcomes for users
