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. In our new article, let’s take a look at what predictive maintenance is, why it is used, what advantages it provides to businesses.

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.

 

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. For more information condition monitoring.

How does Predictive Maintenance work?

Predictive maintenance utilizes sensors and devices that connect wirelessly to a system. These sensors monitor factors, like temperature, vibrations and oil levels to provide real time information on equipment performance.

Data Analysis

The data gathered from sensors is sent to a hub where machine learning algorithms analyze it within the context of machine operation and wear. This analysis helps detect patterns, anomalies and deviations from operating conditions.

Predictive Models

Predictive maintenance models utilize the gathered data to predict equipment failures. Suggest maintenance actions. These models compare equipment behavior with expected behavior enabling technicians to take action before breakdowns occur. Early detection aids in preventing failures and reducing downtime.

Establishing a Predictive Maintenance Plan

For a predictive maintenance plan implementation businesses should consider the steps;

Start small; Initiate predictive maintenance on select assets before expanding. This approach allows testing of the strategys effectiveness and refining the process.

Identify assets; Determine which assets are most suitable, for maintenance.
Certain equipment may have importance. Be more susceptible, to breakdowns, which makes them suitable candidates for this method.

Resource allocation; Identify the resources needed for implementing maintenance, such as manpower, materials, infrastructure and technology. Providing training to staff involved in the procedure is also crucial.

Initiate asset monitoring; Begin monitoring the selected assets and gather data. This data serves as the basis for establishing a maintenance system.

Create machine learning algorithms; Utilize the gathered data to create personalized machine learning algorithms of forecasting equipment failures based on data trends.

Implement algorithms on trial assets; Apply the algorithms to trial assets. Produce reports and insights derived from the collected data. This stage enables companies to assess the efficiency of their maintenance regimen.

Continuous enhancement; Utilize outcomes and input from trial assets to enhance and optimize the maintenance process. Continuous improvement guarantees that the strategy remains effective, over time.

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.