摘要(英) |
With the technology improved and widely used of TFT-LCD and it have become key electronic components. Taiwan is the top three of panel makers and market share of 32% in the world. In recent years, production capacity increase of the China and panel prices continue to fall. Panel maker maintain the company reputation at the limited cost by continuously improving product yields and maintaining customer quality. Although panel maker is already highly automated production in panel industry, it is still pursue to make full use of existing resource allocation with intelligent factories, intelligent manufacturing, big data, and AI functions. It can effectively intercept abnormalities in the factory to reduce the extra sorting costs by abnormal product leakage to customer and lose of company reputation. Due to the trend of the abnormal panel percent ratio is not obviously with the OQC (Outgoing Quality Control) sampling reject and customer VLRR (Vendor Line Reject Ratio). Customer VLRR still has not been effectively reduced. In this research introduces the precision sampling model to improve OQC inspection capability before shipment, which can effectively maximize the sampling failure rate. The cluster sampling concept this action of reject the abnormal product to re-work or re-test can effectively reduce the cost of the customer′s VLRR and the customer′s failure to stop the product line, and invisibly increases the company′s reputation. |
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