The evolution of maintenance
May 16th, 2024
As long as there have been machines, there have also been maintenance and repairs. Now, predictive maintenance is about to revolutionize the way we safeguard equipment.
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Equipment lifetime
There is no way around servicing and maintenance if you want to ensure the longevity, reliability, and efficiency of your equipment. In today’s fast-paced industry, though, the key is to intervene as efficiently as possible to achieve maximum cost savings. To accomplish that, maintenance practices have evolved significantly over the years, with preventive and predictive maintenance emerging as two prominent strategies. While both strategies share the common goal of avoiding equipment failures, they differ in their approaches and outcomes.
Preventive maintenance
A time-based approach
The primary objective of preventive maintenance is to replace or refurbish components before they reach their failure points. Typical strategies involve performing routine inspections, servicing equipment, and carrying out repairs at predetermined intervals – based on recommendations or historical data – to prevent equipment failures. Minor issues are addressed before they escalate into major problems. That reduces the likelihood of unexpected costly breakdowns and repairs, as well as the associated production losses.
Following this proactive approach allows for planning resources, labor, and spare parts in advance.
However, preventive maintenance has its limitations: Preset maintenance intervals may not consider the actual condition of the equipment. That may lead to over-maintenance with unnecessary expenses and resource allocation, while unscheduled failures can still occur due to unforeseen circumstances.
Predictive maintenance
Intervening only if necessary
The clever use of predictive maintenance eliminates these weaknesses. It relies on real-time condition monitoring, sensor data, and analytics to identify potential issues and trigger maintenance actions.
By analyzing patterns and trends, predictive maintenance aims to optimize maintenance activities and prioritize resources based on actual equipment health. Parts are replaced or repaired only when necessary, for example when process parameters indicate irregularities. This reduces downtime and results in cost savings by foregoing unnecessary replacements and repairs.
Of course, the accuracy and effectiveness of predictive maintenance rely heavily on the quality and reliability of the data collected. Only if the data is on track, can the algorithms extract meaningful insights or detect subtle changes and abnormalities that may indicate impending problems accurately. Over the last years, technology has made great leaps in this area. IoT-enabled sensors and interconnected devices gather and analyze data in real-time and with high precision providing the base infrastructure for successful predictive maintenance strategies.
Whats next?
The future of maintenance lies in a hybrid approach that integrates the strengths of both the preventive and predictive strategies. Historical and real-time data will complement each other and work together towards their shared goal. Ultimately, decision-making will become more proactive, and maintenance will be carried out with greater precision, leading to higher operational efficiency.
Have you started this journey yet?
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