Transforming Small Businesses 2025

A detailed look – AI-enabled predictive maintenance FIGURE 7 Current scenario AI-enabled scenario Predictive maintenance Reactive maintenance and manual practices lead to frequent breakdowns and production delaysAI and IoT sensors optimize maintenance schedules, minimizing downtime through centralized monitoring Streamlined planning aligns parts procurement with predicted needs Real-time sensor data enables proactive maintenance and enhanced reliabilityLimited monitoring capabilities delay issue resolution, affecting productivityHigh spare parts inventory tied to unpredictable failures consumes working capital Source: World Economic Forum CASE STUDY 1 Predictive maintenance for industrial gearbox manufacturer A mid-sized Indian manufacturer of industrial gearboxes faced recurring problems because of the corrosion of bearings, the degradation of gear surfaces and the failure of lubrication systems in its manufacturing equipment. These issues caused production disruptions and increased its maintenance costs. Partnering with a technology service provider, the company implemented an AI-based predictive maintenance solution that integrated temperature and vibration sensors with advanced machine-learning algorithms. The system continuously monitored critical equipment parameters, analysing data in real time to identify early-warning signs of failures, which enabled maintenance teams to address issues before they escalated. The implementation delivered a 40% reduction in unplanned breakdowns and a 30% decrease in maintenance costs. Beyond cost savings, the solution enhanced the industrial gearbox-maker’s reliability and operational efficiency, transforming the company’s manufacturing operations. Transforming Small Businesses: An AI Playbook for India’s SMEs 28