This Infosys white paper outlines a systematic, data-driven approach to predictive maintenance, aiming to reduce costs and downtime by servicing equipment only when failure is likely. It details required data sources, analytics techniques (Pareto, temporal, univariate, multivariate), and model-building best practices with precision/recall evaluation. Deployment considerations include scalable architecture, cloud/on-prem options, and integration with monitoring dashboards. Emphasis is placed on accurate data mapping, validated precursors, domain expertise, and rigorous validation on recent field data to ensure reliable, industry-ready solutions.

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