For the last couple of years, queries regarding predictive maintenance have been on the rise. This goes to show that manufacturers are looking at AI-driven innovations to improve revenue and profitability. Predictive maintenance emerged as a critical use case for manufacturing industries that had unlimited data storage available and access to advanced analytics technologies. Predictive maintenance technologies make use of the latest applications of artificial intelligence, machine learning and IoT sensors, to predict the failure of equipment and allow maintenance managers to rectify the situation ahead of time. The possibilities of increased efficiency and reduced costs are endless if predictive maintenance solutions are well-executed.
What is predictive maintenance?
Predictive maintenance is a data-driven, proactive maintenance approach that relies on predictive analytics to forecast equipment failures before they can occur. The data from machines are consistently collected and then fed into the data analytics applications to detect any anomalies in any localized parts. This technology allows maintenance managers to gain insights into the health of the machine parts and mitigate breakdowns by taking the necessary actions.
Predictive maintenance keeps track of the performance and condition of the equipment in a normal working state to determine when a failure might occur and thus, tries to reduce the likelihood of uncalled-for downtime. It monitors the equipment with sensors and software and analyzes all the data fed into the predictive maintenance applications to make sure which machine needs attention and when.
Why predictive maintenance is better than other maintenance approaches?
Reactive maintenance methodology is similar in its workflow to that of predictive maintenance, the operators and managers are alerted when a failure occurs and then instinctively react to repair or replace the equipment. Reactive maintenance programs respond to unexpected failures, causing downtime and loss of production. However, predictive maintenance seeks to avoid such unexpected failures by anticipating issues or damage before they can happen.
Both preventive and predictive maintenance are proactive in nature. Preventive maintenance programs are set in place to avoid unnecessary downtime through regular checks and scheduled replacement and repair of equipment. Yet, the problem of additional costs arises since any part or equipment that is still in good working condition can end up being replaced. With predictive maintenance, only the required maintenance efforts are put in place.
Predictive maintenance is not a replacement for traditional maintenance techniques but a valuable addition to the regulated maintenance program. It contributes to significant benefits for the manufacturer by simultaneously increasing the life of the machinery and reducing the cost of maintenance. Intellicus can provide a platform with highly advanced BI and manufacturing analytics and empower manufacturers with predictive maintenance capabilities.
Benefits of Predictive Maintenance
Minimized Downtime and Improved Availability - One of the primary benefits of predictive maintenance is its ability to minimize unplanned downtime. Businesses can continuously monitor the condition of their equipment, detect early signs of potential failures and take preventive action before problems get worse by leveraging sensors, IoT devices and advanced analytics. This proactive approach makes sure that maintenance tasks are carried out during scheduled downtime, reducing the risk of unexpected equipment breakdowns and maximizing operational availability.
Cost Optimization - Organizations can lower maintenance costs substantially with the help of predictive maintenance. Manufacturers can prevent needless replacements and streamline their maintenance procedures by identifying specific components or parts that require attention. Improved inventory management also becomes possible since spare parts and materials can be ordered in advance, which eliminates the need for excessive stockpiling or rushed orders.
Improved Safety and Reliability – Manufacturers across industries are extremely concerned with safety. Accidents, injuries and even catastrophic events can result from equipment failures. In order to maintain the equipment's reliability and safety, predictive maintenance is essential. By monitoring key parameters and detecting deviations or abnormalities, maintenance teams can intervene before safety hazards arise.
Increased Lifespan of Equipment – By constantly monitoring the condition of the equipment and analyzing the data, maintenance teams can easily identify the underlying issues that can lead to failure. Early detection allows for timely repairs, adjustments, or replacements to help keep the machine in top form, thus increasing its lifespan.
Conclusion
Predictive maintenance takes preventative maintenance to another level, ensuring repairs happen before equipment fails. Predictive maintenance is an approach to maintenance that is most beneficial for industries that rely on heavy machinery like oil and gas plants, infrastructure and other large manufacturing operations. The cost incurred on the replacement of damaged parts or labor is much less than that of the loss of production during the time when the maintenance work is performed. Therefore, it is essential for manufacturers to reduce downtime as much as possible. Thus, businesses that embrace predictive maintenance can cut costs and increase productivity with the least possible disruptions to the manufacturing process.
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