A yield estimating method for a continuously produced coiled material

Abstract

A yield estimating method for a continuously produced coiled material is provided. The method includes 1) a step of AOI detection, namely a step of performing non-contact real-time detection on each coil of the film material with an AOI device; 2) a step of AOI detection data extraction; 3) a step of data pretreatment, namely a step of unpacking the AOI detection data, and extracting data list heads to obtain needed defect information; 4) a step of data filtering; 5) a step of data section splitting, namely a step of, through a program, subjecting the coiled material to section splitting according to a section dimension and direction of an actual sheet-shaped finished product, and making a split diagram in one-to-one correspondence with an actual situation; and 6) a step of calculating thesplit diagram obtained in the step 5) to obtain an estimated yield high in accuracy. The estimated yield is high in accuracy and high in reliability, and is adopted as feedback data to improve the production quality and increase the product yield. The method has no influence on the yield of the coiled material through the non-contact detection, and sampling is not needed so that consumption is avoided.

Description

technical field [0001] The invention relates to a yield rate estimation method, in particular to a yield rate estimation method of roll materials. Background technique [0002] The roll length of roll-shaped materials is usually greater than 1000 meters, and the production is continuous without interruption, which is closely related to the production status. The quality of the rolls at the beginning and the end of rolls varies greatly; with the development of time, the production speed of roll-shaped materials has been greatly improved. [0003] For the current continuous production of roll materials, there may be no yield rate estimation during the production process; or there is only a simple yield rate estimation method, which consists of sampling inspection at the end of each roll and online process inspection, and only grades A / B / C / D, without a specific value, the estimated yield grade is the lowest grade between the final product grade and the process grade. [0004]...

AI Technical Summary

Problems solved by technology

[0010] Low accuracy of estimated yield rate: The current yield rate estimation technology has the following problems that lead to inaccurate estimated yield rate: only relying on final part sampling and partial process inspection, without overall inspection and estimation of the entire roll; There is a big difference at the end of the middle roll, only the last part is sampled, the representativeness is not strong, and the sample size is small; the process yield estimation is based on manual inspection, and as the production speed increases, the difficulty of manual inspection increases and the accuracy decreases;

[0011] Cause product loss: each volume is sampled, and the sampled product cannot be used again, resulting in loss

[0012] There is a risk of reducing product quality: During process inspection, inspectors need to enter the clean room to inspect materials at close range (≤0.5m). Personnel are the largest source of pollution in the clean room, which will reduce the cleanliness and reduce product quality. risks of

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