A mes system-based LED wafer test disassembly machine splitting and collecting method

Abstract

The invention discloses a MES system-based method for LED wafer test dismantling, grouping, and collection. The information recorded on the barcode is uploaded through a code scanning gun and compared with the information on the MES system, without manual comparison by naked eyes, reducing The operator checks the workload of the report, and at the same time, the information check can be 100% correct, avoiding the problem of wrong pairing between the sub-batch and the production equipment, and reducing the production error rate; using the MES system to monitor the production status of the sub-batch in real time, Operators can accurately judge the time of sub-batch merging, improve production efficiency, thereby greatly reducing the time of splitting batches, and achieve precise control management.

Description

technical field [0001] The invention relates to the technical field of LED chip testing and production, in particular to a method for separating, assembling, and collecting an LED wafer testing machine based on an MES system. Background technique [0002] The LED wafer is the core part of the LED. In fact, the main optoelectronic parameters such as the wavelength, brightness, and forward voltage of the LED basically depend on the wafer material. The processing and fabrication of related circuit components of LEDs are all done on wafers, so wafer technology and equipment are the key to wafer fabrication technology. [0003] At present, the LED front-end chip manufacturing equipment determines that each batch of wafers is about 40 or more. The test time of each LED chip testing equipment is controlled at about 3-7 hours according to the size of the product and the change of test conditions. In order to shorten the time In the testing time, each batch of wafers needs to be div...

AI Technical Summary

Problems solved by technology

[0004] At present, most enterprises still use manual report records to track the production operations of each sub-batch, and rely on the physical location to distinguish which batch of products each equipment should produce. When the operator pulls the product to the front of the corresponding equipment, it needs to Correspond the data in the report one by one with the naked eye. The data that needs to be checked includes customer code, product model, station, date of move-in, date of start of work, etc. If there is a slight mistake, there will be a check error, and the workload of manual report tracking is heavy. And the timeliness is poor, which affects the production cycle of the product. In addition, after the split production, because the start time and completion time of each batch are different, it is difficult for humans to accurately judge the time when all batches are completed.

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