Predictive Maintenance is about more than algorithms
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.
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- 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