In the assembly workshop of the ply-pack factory, a high-speed pillow packaging machine with more than 38,000 hours of service is still operating accurately. Li Ming, the chief engineer responsible for the full life cycle management of the equipment, pointed to the nameplate on the fuselage and exclaimed: "The secret of this equipment is hidden in the 30-minute packaging machine maintenance every day."
Packaging machine maintenance has long broken through the primary dimension of traditional wiping and oiling. In recent customer visits, it was found that 83% of downtime accidents were caused by abnormal lubrication systems, and such problems can be completely avoided in advance through preventive maintenance. Our intelligent diagnostic system collects data in real time through vibration sensors, and can warn of bearing wear risks 72 hours in advance. It is this predictive packaging machine maintenance strategy that has increased the average trouble-free time of customer equipment by 67%.
In the spare parts supply chain, the factory has established a unique "three-level early warning mechanism". When the system detects that the national replacement rate of a certain model of gear exceeds the critical value, the cloud inventory will automatically generate a replenishment order. This supply chain management based on big data ensures that the reserve sufficiency rate of common spare parts in 34 spare parts central warehouses across the country remains above 99.8%, providing a solid guarantee for the preventive replacement of core components.
The technical team specifically reminds operators to pay attention to three maintenance blind spots: periodic flushing of vacuum pump filters, atomization cleaning of photoelectric sensor mirrors, and quarterly calibration of transmission belt tension. These seemingly simple packaging machine maintenance actions often directly affect the 0.1 mm packaging accuracy of the equipment. A food company strictly follows the maintenance manual, and the vertical packaging machine it purchased in 2018 still maintains a zero-fault operation record.
In the face of the industry's intelligent transformation trend, the new generation of packaging machine maintenance system has been integrated with the Internet of Things gene. Through the equipment health management platform, customers can view the maintenance calendar, spare parts life countdown and energy consumption curve in real time. This transparent packaging machine maintenance management model has enabled a daily chemical group to successfully reduce annual maintenance costs by 42% and reduce unexpected downtime by 91%.
Standing at the top of the wave of intelligent manufacturing, ply-pack is transforming equipment maintenance experience into industry standards. From preventive maintenance procedures to remote diagnosis protocols, we look forward to building a smarter packaging machine maintenance ecosystem through in-depth collaboration with upstream and downstream partners, so that each device can release its maximum value potential.
