Predictive maintenance is one of the maintenance methods widely used by businesses today. It is the process of monitoring the operation of machinery and equipment to detect problems and fix them promptly, because a machine failure can halt the production line, and repairs are then extremely costly. Furthermore, predictive maintenance gives businesses an effective, economical maintenance solution.
What is predictive maintenance?
As the economy grows, demand for goods keeps rising. Factories have to step up production, putting machinery under great pressure to run continuously to keep up. That is why applying predictive solutions to machine maintenance is essential for businesses. So what is predictive maintenance and how does it work?
Definition
Predictive maintenance is a method that helps prevent equipment failures during operation. It monitors the actual condition of equipment to predict failures and carries out maintenance before problems occur.
What is predictive maintenance?
Specifically, by using tools together with data analysis techniques, predictive maintenance helps manufacturers detect anomalies in machine operation or defects in equipment and operating processes. Based on this, manufacturers can plan timely repairs before breakdowns happen.
How it works
To predict equipment faults, manufacturers need to find the right predictive technique. Furthermore, the technique must provide enough warning time to carry out maintenance. Here are some commonly used predictive maintenance methods:
Vibration analysis: for heavy-duty machinery, manufacturers can rely on vibration sensors and Internet of Things (IoT) sensors to detect signs of deterioration during operation. This is considered one of the most accurate techniques for identifying machine problems.
Vibration analysis
Thermal imaging: also called infrared technique, it detects hot spots caused by parts with excessive friction during operation. These findings usually warn manufacturers of potential risks in equipment that needs maintenance.
Thermal imaging
Acoustic and ultrasonic analysis: a technique that uses sound signals to detect small cracks or failed welds before they become visible and lead to gas or liquid leaks.
Oil analysis: the process of checking the amount of debris in oil-lubricated equipment. The more metal debris there is, the more the equipment is showing signs of wear. This technique can also check for leaks and oil cleanliness.
The basic differences between predictive and preventive maintenance
Predictive maintenance and preventive maintenance share the common goal of preventing losses for the business and keeping machinery in the best condition. However, they differ in approach and requirements. Specifically:
Preventive maintenance is carried out periodically, while predictive maintenance is based on the condition of the equipment, which is closely monitored at all times.
Preventive maintenance is carried out when machinery is stopped, whereas predictive maintenance is carried out while machinery is running.
>>> Learn more: PREVENTIVE MAINTENANCE solutions for production assets.
The role of predictive maintenance for a production facility's assets
The main purpose of predictive maintenance is to predict when equipment is most likely to fail and to provide detailed information that supports timely, fast maintenance planning. This solution has contributed greatly to businesses' bottom line, notably:
Minimizing maintenance time.
Greatly increasing maintenance effectiveness.
Creating new revenue streams for the business.
Improving customer satisfaction.
Increasing competitive advantage.
Predictive maintenance helps prevent machine failures during operation as far as possible
Typical applications of predictive maintenance
Today, predictive maintenance has become one of the leading Industry 4.0 “case studies” in asset management (machinery, equipment). Predictive maintenance solutions are deployed together with IoT technology to monitor asset condition, optimize maintenance timing and receive real-time alerts about risks that may arise when equipment is running.
IoT analytics supports predictive maintenance for an oil and gas company
A typical example is predictive maintenance in the oil and gas industry. Oil and gas benefits greatly from predictive maintenance solutions, because physically inspecting oil and gas production equipment requires staff to work in fairly toxic, dangerous environments, and in many cases it isn't even feasible. Predictive maintenance with IoT technology helps businesses identify hidden risks so they can plan appropriate solutions.
>>> See also: What you need to know about applying IoT in industrial manufacturing.
So, predictive maintenance combined with IoT technology brings many benefits to businesses. It is considered an effective solution for extending equipment life and limiting the risks and losses that occur during operation.