"This packaging machine has been running for 11 consecutive months without any failures. What is the secret?" At the ply-pack technical seminar, the real-time data screen displayed by equipment supervisor Zhang Wei to more than 200 companies sparked heated discussions. The answer lies in the packaging machine maintenance system driven by the intelligent diagnostic system. This solution has helped 34 companies achieve an annual maintenance cost reduction of more than 40%.
The core lies in building a three-level early warning mechanism. The first level consists of vibration sensors distributed in key parts of the equipment, which can capture abnormal fluctuations of bearings 72 hours in advance; the second level monitors the temperature rise curve of the motor through a thermal imager to accurately determine the status of the lubrication system; the third level is connected to the spare parts response system, and when the gear wear reaches the critical value, it automatically triggers the spare parts allocation process. This three-dimensional packaging machine maintenance strategy has increased the overall equipment efficiency (OEE) of a dairy company in Hubei by 28 percentage points.
The implementation of preventive maintenance requires more technical empowerment. The maintenance calendar system developed by the engineering team upgrades traditional paper work orders to dynamic task flows. Operators will receive customized instructions before starting the machine every day: it may be mirror cleaning of the photoelectric sensor or deep flushing of the vacuum pump filter. The specially designed torque calibration tool allows the transmission belt tension adjustment error to be controlled within the range of ±0.3 Nm. This improvement has increased the packaging accuracy qualification rate of a pharmaceutical company in Shanghai from 92% to 99.6%.
At the equipment life cycle management level, the system will generate exclusive health records based on operating data. When the packaging machine has worked for 8,000 hours, the system automatically pushes a preventive replacement recommendation for the spindle bearing; when it runs for 20,000 hours, it triggers a deep maintenance plan for the whole machine. This predictive packaging machine maintenance mode allows a vertical packaging machine of a food company in Zhejiang to continue to serve for 7 years and still maintain 97% of the factory performance.
In the face of sudden failures, the value of the intelligent diagnosis system is more prominent. Last month, a customer's equipment in Guangdong had intermittent film jams. Engineers remotely retrieved the pressure curve map of the last 30 days and accurately located the abnormality of the servo motor encoder of the film material traction roller. It took only 4 hours from the alarm trigger to the replacement of the parts, avoiding the average 2-day production stoppage loss in the past.
Today, this packaging machine maintenance system is exporting standards to the industry. Through in-depth data sharing with 30 spare parts suppliers, the average delivery cycle of key spare parts has been shortened to 12 hours. When a cutter module failure occurred in a Yunnan company late at night, the spare parts center closest to its factory completed emergency delivery within 3 hours through drones, setting a new timeliness record in the field of packaging machine maintenance.
Under the wave of intelligent manufacturing, packaging machine maintenance has transformed from a cost center to a value creation engine. ply-pack will continue to iterate its equipment health management algorithm to ensure that each packaging machine can exceed the design life limit and always be rejuvenated during the ten-year run.
