For industrial businesses, machinery downtime can lead to significant losses, disrupting operations and increasing expenses. Finding cost-effective maintenance solutions is crucial for improving efficiency and maximizing equipment longevity.
With the global maintenance, repair, and operations market expected to reach $701.3 billion by 2026, industries must address major contributors to unplanned downtime—aging assets, equipment malfunctions, operator errors, and insufficient maintenance strategies.
One key solution is investing in maintenance-free components, such as ultrasonic clamp-on meters. These devices lack moving parts, reducing wear and eliminating frequent maintenance requirements—saving both time and money.
Another crucial strategy is preventive maintenance (PM). By scheduling regular servicing to detect issues early, companies can avoid unexpected breakdowns. As more and more manufacturing companies use PM to improve reliability and extend equipment lifespans, there are some downsides. For example, operational costs inevitably increase and the effectiveness varies depending on the machinery type.
A more advanced alternative is predictive maintenance (PdM), which leverages AI-driven analytics and sensor data to forecast when equipment requires servicing. 41% of manufacturers have already adopted PdM, and according to the U.S. Department of Energy, it reduces maintenance costs by 8% to 12% compared to preventive maintenance.
Predictive maintenance optimizes servicing schedules by performing maintenance only when needed, reducing unnecessary costs while preventing disruptive failures.
By implementing preventive and predictive maintenance strategies, businesses can cut costs, minimize downtime, and increase overall efficiency. Investing in advanced monitoring tools, maintenance-free components, and AI-driven analytics ensures maximum equipment performance and ROI.
For more expert insights on improving industrial maintenance strategies, check out the accompanying resource courtesy of Emerson.
