Introduction
Unplanned downtime continues to be one of the most pressing challenges in manufacturing, costing companies up to USD 260,000 per hour. Traditional maintenance approaches—reactive or time-based—often fail to detect failures before they disrupt operations. In today’s high-stakes production environments, manufacturers must shift from outdated methods to AI-powered predictive maintenance (AI-PdM) to stay competitive.
About the Whitepaper
This whitepaper explores how AI-driven Predictive Maintenance empowers manufacturers to transition from reactive maintenance to a proactive, data-informed approach. It outlines the role of AI, Machine Learning, and Digital Twins in predicting failures, optimizing asset performance, and minimizing downtime. The paper also shares real-world implementation insights, industry benchmarks, and a case study on a global waste management firm that achieved substantial efficiency gains using Straive’s AI-PdM solution.