According to the International Society of Automation, factories worldwide lose 5-20% of their productive capacity to unplanned downtime. With supply chain disruptions increasing, Predictive maintenance solutions help manufacturers identify equipment failures before they occur, maintaining operational continuity.
Higher transport costs and worker shortages have amplified the impact of each stoppage. In this environment, predicting maintenance needs gives companies a significant advantage. Mainly due to the early indication of a fault, allowing it to be fixed during the next maintenance period, which means longer machine uptime.
AI-Maintenance In Figures
As Rafi Ezra, Managing Partner US Industrial Market at IBM Services states: “AI-powered maintenance solutions can cut downtime by up to 50%, reduce breakdowns by 70%, and lower overall costs by 25%.”
Industry Response to The Needs
“Today, implementing predictive maintenance tools is no longer just an advantage but a necessity for companies that want to stay competitive,” emphasises Daniel Sperlich, Strategic Product Manager Controllers from Mitsubishi Electric. “Our solutions help manufacturers address problems before they affect their production lines. We ‘put intelligence’ where it is required most, directly into our equipment, close to the mechanics.”
Real-World Impact
“Supply chain reliability starts on the factory floor,” says Daniel Sperlich. “When a machine can self-diagnose before breaking down, it prevents the chain reaction of missed deliveries that can disrupt downstream operations.”
The Predictive Future
The dynamic growth of the predictive maintenance market reflects the increasing need of manufacturing companies to shift from reactive to proactive strategies, enhancing performance whilst stabilising supply chains in uncertain times. A key driver is the ability to implement these solutions in a scalable manner—from individual devices to entire production facilities—without requiring significant initial capital investment and with clear and easy ROI calculation.
Sources:
Deloitte “Predictive maintenance and smart factory”: us-cons-predictive-maintenance.pdf
Forbes “Unplanned Downtime Costs More Than You Think”: Unplanned Downtime Costs More Than You Think
Sage Clarity “Manufacturing Performance OEE Benchmark Data for Fast Moving Consumer Goods”: OEE Benchmark Study | Sage Clarity
Resilinc “Top 5 Manufacturing Supply Chain Disruptions in 2024”: Top 5 Manufacturing Supply Chain Disruptions in 2024 – Resilinc
Grand View Research “ Predictive Maintenance Market Size, Share & Trends Analysis Report By Component, By Solution, By Service, By Deployment, By Enterprise Size, By Monitoring Technique, By End-use, And Segment Forecasts”: Predictive Maintenance Market Size | Industry Report, 2030
