In the traditional hot forming stamping production process, someone must be responsible for monitoring whether the hot material above 700℃ is stacked up or not cast correctly after it is put into the mold before stamping, and whether the molded parts are picked up by the unloading manipulator after stamping, etc., so as to ensure the operation safety of the equipment and the yield rate of the workpieces. Due to the special characteristics of hot stamping, the production line is basically a 24-hour continuous production, and the working environment is very terrible: dust, high temperature, noise and so on. For this reason, the recruitment of personnel for this station has always been a headache for manufacturers.

　　In order to solve the customer's pain point, AWIZ team invested human and financial resources in independent research and development for three years, through the long-wave infrared cameras, short-wave infrared cameras based on AI deep learning target detection technology and combined with traditional image processing algorithms, to achieve real-time detection of the feeding situation, and automatically triggered the shutdown of abnormalities without the need for personnel on duty.

　　This system can be installed on new production lines or add new functions to old lines. It is easy to install and quick to deliver. It only takes one day for on-site installation, five days for debugging, and one day for training. It can be delivered for use in one week.

　　It can bring customers:

　　- Higher efficiency: Avoiding mold damage caused by human negligence and reducing unplanned downtime.

　　- Lower management and manufacturing costs: Reduce one person per shift and three people per day.

　　- Higher yield rate: Real-time detection of sheet temperature to avoid the production of defective products.