Smart maintenance of remote machinery

Challenge

Many companies install and maintain machinery that is dispersed over a large geographical area. Service contracts for those machines stipulate maintenance according to fixed time schedules which is usually suboptimal and involves a quite high financial cost to these companies.
Furthermore, in case of problems, remote troubleshooting can be challenging because of the lack of data or visibility of what is going on.

Evolving from reactive to predictive maintenance

Predictive maintenance can resolve issues related to fixed maintenance schedules or pure reactive maintenance. Predictive maintenance allows to detect problems upfront or as soon as they occur and resolve problems proactively. Predictive maintenance relies on data analysis to optimize maintenance schedules, avoid downtimes and optimize services costs.

Predictive maintenance requirements

  • Continuous analysis of data from various sources.
  • Analysis of data, trends and correlations.
  • Predict problems, degradations and diagnose root causes.
  • Take proactive action to remedy problems.

Solution

Waylay’s orchestration middleware allows for the periodic collection of data from a varierty of systems, evaluating that data and acting on the outcome of that evaluation. Waylay’s platform can detect out-of-range values, trends, correlate phenomena and diagnose root causes. Moreover, Waylay provides the link between your IoT solution and your ticketing systems and helpdesk.

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