Predictive maintenance: From anomaly to action
Identifying anomalies in industrial IoT systems is just the beginning. Effective predictive maintenance requires integrating signals with diagnostics, work order management, and measurable feedback.

Co-owner, Member of the Supervisory Board, Intecracy Group
IT investment professional educated in law and finance; advisor on investment and M&A.
In the AZIOT knowledge base, the expert provides strategic commentary on published articles: investment, governance, security, and architecture angles for infrastructure decisions.
Identifying anomalies in industrial IoT systems is just the beginning. Effective predictive maintenance requires integrating signals with diagnostics, work order management, and measurable feedback.
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