MATLAB® and Simulink® product managers talked to more than 100 engineers and engineering managers working on predictive maintenance systems to find what these teams had in common.
Four areas came up as common obstacles to predictive maintenance across companies and industries:
- Do we have enough data?
- Do we have enough failure data?
- How do we predict failure?
- How do we build a predictive maintenance algorithm?
Download this paper to learn how to overcome these obstacles through best practices, examples from real businesses, and an explanation of the predictive maintenance workflow.