【Omron industry case】Predictive maintenance of smoke machine in automobile welding workshop

Process introduction

Automobile welding is the second of the four major processes in vehicle production, which mainly assembles stamped body components into a complete body. In the welding process, spot welding and arc welding of robots are the mainstay, and there will be a station for visual inspection of the welding status in the middle.

【Omron industry case】Predictive maintenance of smoke machine in automobile welding workshop

　　As one of the country's largest automobile manufacturers, it has a very high market share in the Chinese market, so it expects to improve the stability, utilization rate, safety of equipment at the business level, and reduce the total investment cost.

　　problem

01. It is difficult to obtain the operating parameters of the motor

The welding site needs a high-power smoke exhaust machine to ensure the production environment on site, and the existing smoke machine does not have a frequency converter, and the maintenance personnel cannot obtain the operating parameters of the motor

02. It is impossible to grasp the status of the motor in real time

Since the motor is located on the second floor of the workshop, it is not convenient for maintenance personnel to measure, so it is difficult to control the status of the motor in real time.

Once the motor fails, the security personnel can not understand the situation at the first time, which will cause harm to the on-site environment and the external environment, and may face warnings and fines from environmental protection agencies, which will have a great impact on the production and environmental protection of the enterprise.

solution

1. Monitor bearing abnormalities through vibration and temperature

By continuously monitoring vibrations, signs of bearing abnormalities can be quickly detected. In addition to this, the surface temperature of the motor, which is checked daily, can be measured at the same time.

　　Vibration frequencies up to 10 kHz can be measured, so motor abnormalities can be detected at an early stage.

　　2. Comprehensively monitor the abnormality of the motor and load according to the degree of aging

Two algorithms are used to calculate the degree of aging 1 and the degree of aging 2 to monitor anomalies in a composite manner.

Degree of Aging 1:

It is suitable for monitoring anomalies that have irregular effects on the motor shaft, as it converts the entire current waveform data acquired during sampling to the deviation from the ideal sine wave.

　　Degree of Aging 2:

It is useful for monitoring anomalies that occur on a regular basis by clearly capturing specific frequency components that affect the axis of rotation of a motor and converting them into numerical values. Especially in environments where there is inverter interference, anomalies can also be detected with high sensitivity.

　　3. Through the special monitoring software, the motor status is clear at a glance

With the K6CM series, which is connected to the Internet, the status of up to 10 motors can be displayed at a glance. You can view the data of up to 30 K6CM units. (Three types of K6CM can be mounted on one motor.) )

　　The alarm status of multiple motors is displayed, and changes in the motor status can be checked in chronological order. And grasp the trend of the measured value with a graph. (Measured and accumulated data can be exported to CSV format, which is useful for creating reports and statistics)

　　Control system

● Motor status monitor K6CM series

● Temperature status monitoring equipment K6PM-TH series

　　Deliver value

1. Comply with production environmental protection standards

2. Avoid unplanned downtime and achieve "uninterrupted" production

Traditional predictive maintenance has a long system construction cycle, requires huge raw data support, and has high barriers to introduction.

　　Omron's predictive maintenance solution based on the equipment layer uses edge computing to achieve line-level maintenance and remote monitoring at the equipment level without the need for development and programming for specific equipment, with a short installation cycle and simpler on-site operation.

【Management】

■ As a large-scale automobile manufacturer, it is at the forefront of the industry, taking the lead in adopting predictive maintenance solutions to monitor and protect the production environment and external environment in real time, and has contributed to environmental protection and sustainable development.

【Management】

■ Through predictive maintenance, the stable operation of the smoke machine is guaranteed, the production loss caused by unexpected shutdown is avoided, and the equipment utilization rate is greatly improved.

■ There is no need to rely on the experience of skilled maintenance personnel, and it reduces the high maintenance cost caused by manual regular inspection and a large number of inspection items.

【Engineer Layer】

■ Real-time monitoring of a variety of motor data, early prevention or the first time to deal with motor failures, no need to spend a lot of time on site spot inspection and maintenance.

■ Through the special monitoring software, the motor status is clear at a glance. It is easy to use and easy to use, and the measured and accumulated data can be exported to CSV format, which is very useful for creating reports and statistics.

Article source: Omron Industrial Automation Information Account

【Omron industry case】Predictive maintenance of smoke machine in automobile welding workshop

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