Online quality detecting parametric analysis method

Abstract

An online quality detection parametric analysis method comprises the steps of, analyzing the online quality detecting parameter value meets the predetermined specifications, searching the sample testing items or chip testing items relating to online quality detecting items from the data base, searching the testing parameter values items corresponding to each batch of inventory products from the data base, generating the relational expression between the online quality detecting items and the sample testing items, or the relational expression between the online quality detecting items and the chip testing items.

Description

technical field [0001] The invention relates to a process parameter analysis method, in particular to an online quality detection parameter analysis method. Background technique [0002] In semiconductor manufacturing technology, to complete semiconductor products, it usually needs to go through many processes, such as lithography process, etching process, ion implantation process, etc.; cumbersome procedures. Therefore, people familiar with this technology are committed to ensuring the normal operation of the machine, maintaining or improving product yield, detecting and confirming problems, and machine maintenance, so that the production speed and quality of semiconductor products can meet customer needs. [0003] Generally speaking, to discuss the problems of semiconductor manufacturing process, the following data can be analyzed, including process parameter data, in-line QC data, defect inspection data, sample test (sample test) ) data, wafer test (wafer test) data and...

AI Technical Summary

Problems solved by technology

[0011] However, since the existing technology uses human experience judgment to determine the analysis result (step 103), or predict the subsequent test result of the product (step 204), the accuracy and reliability of the final analysis result will be questionable; Coupled with the frequent change of personnel in the semiconductor manufacturing industry, it is difficult to pass on the experience of the engineers in the early and late stages, and each engineer has limited ability and cannot take into account the operating status of all the machines in the factory. Therefore, when the test results of semiconductor products are abnormal , engineers may not have enough experience to quickly and correctly judge which link is wrong, or correctly predict the yield rate of the product in the subsequent process, so it may take a lot of time to conduct relevant research, and it is even possible to do In this way, it will not only reduce the efficiency of the manufacturing process, increase the production cost, but also fail to improve the online production situation in time to increase the yield rate.

Images