Pain points of cutting ends of seamless pipes
Manual measurement is inefficient
It is impossible to manually complete precise wall thickness measurement in a short time, such as measuring 9 points every 1 cm, and usually 4 points every 10 cm.
Humans cannot complete calculations quickly
When cutting the ends of seamless pipes, it is necessary to consider the wall thickness, contract requirements, and pipe saw efficiency. It is impossible for humans to complete all calculations within the time required by the process.
Sacrificing yield rate
Due to manual measurements, yield is often sacrificed through extra cutting in order to avoid not meeting contract requirements.
Unable to dynamically adapt to the process
Due to the maximum cutting capacity of the pipe gang saw, it is impossible to complete the head and tail cutting of a single pipe, and gang cutting must be used. The time allowed by the on-site process is different, and the number of head and tail cutting parameter groups needs to be dynamically adjusted, which cannot be completed manually in real time.
Pipe cutting AI engine
Through a large-scale spatial search algorithm, the combination of cutting head and tail coordinates that maximizes the yield rate can be quickly found within the time allowed by the process, thereby quickly improving the yield rate of seamless pipes.
Pipe Cutting AI Engine Advantages
Leverage wall thickness measurement data
The pipe cutting AI engine can make full use of the measurement data of measuring equipment such as X-ray wall thickness measuring instruments.
Maximize yield rate
The large-scale spatial search algorithm automatically finds the optimal combination of cutting head and tail coordinates to maximize the yield rate.
Pipe gang saw linkage
After the optimal cutting coordinates are determined, the pipe gang saw can be linked to achieve automatic cutting to avoid manual input errors.
Dynamically adjust cutting combinations
Thanks to multi-objective dynamic optimization, the pipe cutting AI engine can adjust the sawing rhythm in time to adapt to the process requirements.
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