Predictive monitoring technologies are used to monitor the condition of your facility’s equipment. These include vibration analysis, infrared thermography, and condition-based maintenance.
Predictive monitoring technologies based on vibration analysis are becoming increasingly popular. These technologies allow companies to make informed maintenance decisions to maximize uptime and minimize maintenance costs.
One of the most critical components of any predictive maintenance program is determining the root cause of a malfunction. Using vibration analysis, engineers can detect the most likely root cause of a fault before a machine breaks down.
For example, a VA technician can determine if a bearing is failing by identifying a failure mode indicator. They can then report the findings in a CMMS.
In addition to detecting potential damage, vibration analysis can also predict the onset of a machine failure. This is important because it helps to avoid unplanned downtime.
Vibration analysis uses several tools and processes to analyze and record the frequency and intensity of vibration pulses on a rotating machine. These pulses can be compared with past equipment history to pinpoint failures or potential problems.
A vibration sensor is one of the most effective vibration analysis tools, which physically attaches to a machine’s core equipment. It provides information on the running condition of a device, including its performance and state, and can inform a company’s predictive maintenance program.
Infrared thermography and predictive monitoring technologies are used for a variety of applications, including quality assurance, preventive maintenance, and surveillance. These non-destructive techniques are safe and reliable. They can also help you prevent downtime and save money.
Infrared thermography uses a thermal imager to capture infrared radiation and convert it to temperature values. The camera’s thermal sequences are then processed with various methods to extract valuable conclusions about the condition of the equipment.
This technology can be used for many different types of equipment, including refractory, electrical, and industrial equipment. Thermal imaging can reveal problems before they cause catastrophic failures. For example, a thermal image can reveal a bad bearing or poor insulation. It can also detect current overload, corroded terminals, and other issues that can impact the life of a machine.
Predictive maintenance increases output by 20-25%. It can also decrease downtime and production loss. A good monitoring system is a valuable tool for any manufacturing or industrial operation.
There are several challenges when using infrared thermography. One challenge is the difficulty in interpreting infrared data. Because of this, operators need to have a high level of training and knowledge about infrared cameras and radiometry.
Predictive monitoring technologies provide insight into the health of an asset. They can increase equipment availability and reduce downtime. They can also streamline maintenance processes. They can be so effective they can save money and improve productivity. Using them correctly can lead to better performance, more productive operations, and increased reliability.
There are several technologies used to do this. One of the more advanced is predictive maintenance. It uses machine learning algorithms to detect breakdowns before they occur. This allows you to schedule maintenance ahead of time and avoid unscheduled downtime.
Another is condition-based maintenance. The technology uses sensors to monitor the health of an asset. These sensors can help maintenance teams make better decisions. Specifically, they can predict the condition of an asset before it breaks down. When this happens, the maintenance team can take action to prevent the problem from becoming a bigger problem.
A CMMS (computerized maintenance management system) can analyze the data collected from these sensors. Often, third-party experts are called in to make sense of the numbers.
Oil and gas
Predictive monitoring technologies are an essential tool for oil and gas operations. They are designed to detect failure signatures and proactively recommend maintenance tasks to minimize equipment downtime. This reduces costs and improves equipment reliability.
Oil and gas operations involve a large number of complex assets. They also require a diverse set of critical assets that are frequently located in remote locations. In such environments, regular manual inspections can be challenging.
Nevertheless, a few technologies can help companies make their operations more energy-efficient and environmentally friendly. These include the Internet of Things (IoT) and artificial intelligence.
In addition, predictive monitoring technology can be used to analyze the root cause of production bottlenecks. These systems can also simulate weather risks and environmental conditions.
Real-time pipeline monitoring helps oil and gas companies address performance fluctuations and unplanned shutdowns. These can minimize revenue losses and reduce risks of hazardous operations.
A wide range of sensors can be installed on assets to gather and analyze data. These include acoustic emission monitoring, which can identify leaks and gas emissions. Flow rate monitoring can be done using an IoT-powered system. Moreover, these systems can be equipped with wearable devices to alert maintenance technicians when dangerous gases or liquids are present.