This Siemens guide explains that successful predictive maintenance starts with strong industrial connectivity. By connecting machines, sensors, legacy equipment, and enterprise systems, manufacturers can collect and contextualize operational data needed to improve uptime, productivity, and Overall Equipment Effectiveness (OEE). The paper emphasizes that connectivity is the foundation for digital transformation and predictive maintenance, enabling organizations to integrate IT and OT systems, overcome data silos, and support AI-driven maintenance strategies. Siemens highlights solutions such as the Brownfield Connectivity Gateway, Industrial Edge, and Senseye Predictive Maintenance, which use machine learning to detect anomalies, predict failures, prioritize maintenance actions, and reduce unplanned downtime. The recommended approach is to begin with a pilot project, integrate insights into maintenance workflows, standardize processes, and then scale across the enterprise to create continuous improvement and enterprise-wide asset intelligence.

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