Late last Wednesday night, the test workshop of our factory was still brightly lit. Xiao Liu from the technical department suddenly slapped the table and jumped up: "It's done! 200 bags in a row with zero misjudgment!" On the monitoring screen, the newly developed AI quality inspection system is scanning coffee packaging bags at a speed of 3 frames per second. The seal wrinkles and weight deviations that used to rely on the old master to squint their eyes are now all marked with red warning boxes.
As one of the first domestic manufacturers to integrate AI quality inspection systems in coffee packaging machines, we know too well what this breakthrough means. At the industry exhibition last year, at least 20 customers surrounded our prototype and asked: "Can we solve the problem of missed inspection of small bags of coffee?" At that time, the quality control director of a Brazilian brand held up a sample of a broken bag as big as a needle tip and said: "This defect will occur 5 times per million bags, but it is 100% a customer complaint for us." Now, our engineering team has finally tackled this tough problem. The newly installed AI quality inspection system has built-in double insurance-high-frame industrial cameras combined with deep learning algorithms can simultaneously capture 12 key inspection points of packaging bags. I still remember the day when we did on-site testing for customers in Hangzhou. When the coffee packaging machine on the conveyor belt continuously found 3 bags of defective products with bubbles in the seal, the workshop director Lao Li directly took out his mobile phone to record a video: "This is more accurate than our quality inspectors wearing magnifying glasses!" The killer feature of this system is its adaptive learning ability. Traditional visual inspection requires manual setting of parameters, and it has to be re-debugged when encountering coffee packaging machines of different specifications. Our AI model has been trained with 100,000 images. It can not only identify common packaging defects, but also automatically establish a feature library when encountering new models. Last month, when we were renovating an old production line for a Yunnan customer, we were worried that the vibration of the old coffee packaging machine would affect the detection accuracy. As a result, the system generated a dedicated anti-shake compensation solution two days after it was put into operation.
The masters who have been working in the packaging workshop for ten years have the most say. When installing equipment for a company in Zhangzhou, the operator Lao Zhang initially muttered, "How can machines be as reliable as human eyes?" When he saw the quality control heat map generated by the system in real time, he immediately changed his words: "This thing can even eliminate the visual error caused by the reflection of aluminum foil bags. It is really good." What surprised the customer even more was that the linkage control function of the AI quality inspection system and the coffee packaging machine automatically stopped the machine and alarmed when continuous defects were found, avoiding the loss of the traditional production line "hundreds of bags of defective products have been produced when the problem was found".
Industry partners may have noticed that the recent Starbucks Supplier Conference specifically mentioned that "intelligent quality control has become a core competitiveness". Our AI quality inspection system was born in line with the trend. It can not only connect to various coffee packaging machines, but also the detection data generated by it can reversely optimize production parameters. Three months after a high-end coffee brand in Qingdao connected to the system, their production director reported that the raw material loss rate dropped by 18%, and the number of customer complaints hit a new low since the establishment of the factory.
Standing at the forefront of intelligent manufacturing, we know better than anyone: the evolution of coffee packaging machines should not stop at speed improvement. When the AI quality inspection system is still tirelessly scanning each packaging bag in the workshop at three o'clock in the morning, and when the decimal point after the "qualified rate" in the acceptance report sent by the customer keeps moving to the right, these real changes are what a smart factory should look like.
Watching another batch of coffee packaging machines equipped with AI systems being loaded and shipped, I suddenly remembered the snowy night in the early stage of research and development. At that time, in order to collect enough defective samples, our team stayed in the customer workshop for 72 hours and collected more than 8,000 bags of defective products. Now, these hard-earned data have become the "fire eyes" of the AI model, and continue to guard the quality promise of every cup of coffee on more production lines.
