What is Predictive Maintenance? Benefits and Tips
Industries have to re-evaluate and re-interpret their maintenance and production processes in line with the digitalization experienced in the last 10 years. This rapid change and transformation are forcing production facilities to be smarter and more competitive. Industrial maintenance now has to be as digital and smart as possible for production facilities. Predictive maintenance offers great opportunities to businesses for a smarter and more digital facility. What is predictive maintenance, and why is it important? Let’s look at the answers to these questions in our article.
What is Predictive Maintenance?
Predictive maintenance is a technique that uses data analysis tools and techniques to detect anomalies in your operation and potential defects in equipment and processes. Thanks to predictive maintenance, possible failures are detected in advance and possible errors are prevented. This way, production facilities have a chance to reduce unplanned downtime as much as possible. While techniques such as oil analysis, vibration analysis, and infrared were frequently used in predictive maintenance in the past, predictive maintenance technologies have also changed and developed with the cheapening of sensors and the spread of IoT technology.
What Does Predictive Maintenance Offer to Factories?
Decrease in maintenance costs
Predictive maintenance is essential when creating a comprehensive maintenance management program for an industrial facility. While traditional maintenance programs are based on service routines for all equipment and offer rapid response to unexpected failures, predictive maintenance plans specific maintenance tasks only when they are actually needed. Therefore, one of the leading benefits of predictive maintenance is the reduction of overall maintenance costs in the business. Predictive maintenance reduces the cost of spare parts, tools and other equipment required for equipment maintenance.
Decrease in machine breakdowns
Regular monitoring of the actual conditions of equipment and process systems significantly reduces the number of unexpected and catastrophic equipment failures. When comparing the unexpected equipment failure prior to the implementation of the predictive maintenance program and the two-year period following the inclusion of condition monitoring into the program, the failure rate drops significantly.
Decrease in Stock Costs
The ability to predict defective parts and tools that require repair and the relevant workmanship skills reduces both repair time and costs. Industrial facilities have sufficient time to order a replacement or spare parts as needed, rather than purchasing all spare parts for stock.
Better Production Efficiency
The availability of process systems increases after implementing a state-based predictive maintenance program. The improvement here is based on machine availability and does not include improved process returns. However, a complete predictive maintenance program that includes process parameter monitoring contributes significantly to production efficiency.
Increased Employee Safety
Early warning of machine and system problems reduces the risk of catastrophic failure that could result in personal injury or death.
Longer Service Life
Prevention of catastrophic failures and the early detection of machine and system problems increase the service life of industrial machines by an average of 30%. Another benefit of predictive maintenance is that it can automatically estimate the mean time between failures (MTBF). This statistic provides a way to determine the most cost-effective time to replace the machine rather than constantly incurring high maintenance costs.
Verification of Maintenance Activities
Predictive maintenance can be used to determine whether repairs made on existing machines fix the identified problems or cause additional abnormal behavior before the system restarts. In addition, the data obtained in the predictive maintenance program can be used to schedule plant shutdowns. Many industries try to fix major issues or schedule preventive maintenance schedules during annual maintenance shutdowns. Predictive data can provide the information necessary to schedule specific repairs as well as other activities during shutdown.
What is the Difference Between Preventive and Predictive Maintenance?
Preventive maintenance involves the inspection and maintenance of an asset at predetermined intervals, whether necessary or not. Maintenance intervals are typically based on usage or time determined from the average life cycle of an asset. Predictive maintenance ensures consistent tracking of an asset, which helps to define a tailored maintenance plan for each asset. This approach maximizes an asset’s lifetime while at the same time contributing to lowering maintenance costs.
How Artesis Helps You?
Thanks to its comprehensive fault detection feature, Artesis Predictive Maintenance solutions significantly reduce your maintenance costs and contribute to your energy efficiency throughout the facility. The error detection accuracy is higher than 90%, ensuring the most accurate maintenance.
The sensors used can be easily installed and recognized by all electrical personnel. Moreover, Motor Condition Monitoring does not have to be with the monitored system because the sensors and the main unit can be placed in the motor cabin.
Predictive maintenance enables automatic database establishment and monitoring of parameters. The degree of failure is displayed on a variable scale, eliminating the need for expert personnel.
Motor Condition Monitoring data is repeatable. Motor Condition Monitoring has no effect on the devices it monitors.
Predictive maintenance is effective in detecting both electrical and mechanical faults. In addition, it can be used in both production and energy efficiency measurement. This point is important, since studies show that motor failures can affect energy efficiency up to 18%.
In Motor Condition Monitoring technology, threshold values are not affected by system conditions. Therefore, predictive maintenance can give early and accurate warnings.