With the rise of the Internet of things, big data and AI technology, factory equipment has ushered in a new change. More and more machines are connected to the Internet, realizing remote data monitoring and analysis. This scenario brings easier and efficient work to the staff. However, many people are unfamiliar with this model, and blindly following the trend may not get the desired effect. So how can companies combine the Internet of Things and big data to enhance the value of factories?

At present, the biggest application of the Internet of Things in the industrial field is predictive maintenance. It was difficult to ensure the continuous operation of the production line 24 hours a day, but today, predictive maintenance can solve the hidden dangers of equipment in advance, so as to prevent equipment failure and downtime.

Electric motor is the main force of today's industry, the factory has many motors for various purposes, such as: lifting, stamping, handling, dust removal, drying and other equipment to use the motor. The maintenance of the motor has become an important issue in the factory, especially in some harsh environments, users are more inclined to remote maintenance.

The decrease in motor efficiency is the most common. If the efficiency of hundreds of motors in the factory has dropped, it will have a great impact on the production of the factory and may cause the risk of downtime. In some production lines, the failure of one motor may cause the entire production line to stop, which is very expensive.

To reduce unplanned downtime, plants hire maintenance personnel. But traditional maintenance methods are also expensive because they have no better way to predict the future of the equipment and still cannot avoid downtime. Usually the motor has the following maintenance methods:

　　Post-Fault Maintenance:It means that maintenance is carried out after the motor fails and stops. In this case, the motor is usually damaged and needs to be replaced, because it is not a simple matter to repair the motor on site. In this case, it can only be replaced first to ensure that production can continue.

　　Preventive maintenance:In order to avoid complete failure of the motor, the staff will regularly maintain the motor according to the average running time of the motor. Usually for safety reasons, maintenance happens too early, and the parts are still in good condition and may be replaced. This method does not guarantee that new problems will not occur after maintenance.

　　Condition monitoring maintenance:Usually, some phenomena occur before the motor stops, such as noise, vibration, and uneven speed. The method of condition monitoring and maintenance is to monitor each motor, similar to the way of a doctor's stethoscope, and the maintenance personnel determine whether maintenance is needed after on-site diagnosis. On-site inspection can be a dangerous task, with maintenance crews running all over the plant.

With the development of Internet of Things technology, these traditional maintenance methods will become a thing of the past. The factory will equip each motor with one or more sensors, which are connected to the control database to continuously collect data about the motor. The database uses artificial intelligence to learn the behavior of each motor, and immediately generates an alarm when the motor deviates from the normal situation.

This sensor-based data collection is more accurate and thorough than any human detection, because many signs of motors are difficult to identify with eyes and ears, but small changes in equipment can be detected through IoT sensors.

The combination of the Internet of Things and artificial intelligence can not only see problems, but also continuously scan and detect possible problems. This method is called predictive maintenance. This method is very good to avoid the occurrence of faults, and at the same time let the maintenance personnel know when is the best maintenance time, will not appear too slow or too early. At the same time, depending on the severity of the problem and alarm, the downtime of the motor can even be planned to minimize interference with the operation.

In the operation of the factory, the wrong decision or make a decision too slow, too early, will lead to a lot of waste of resources and money. The Internet of Things helps users collect data that has never been captured in the past, and through the analysis of artificial intelligence, they can learn from it and make better decisions faster.