﻿ 强化统计分析算法应用：提升晶圆加工铸锭品质管控水平 Strengthen Statistical Analysis Algorithm Application: Elevating Wafer Manufacturing Ingot Quality Management Level

Material Sciences
Vol.08 No.04(2018), Article ID:24410,5 pages
10.12677/MS.2018.84027

Strengthen Statistical Analysis Algorithm Application: Elevating Wafer Manufacturing Ingot Quality Management Level

Shunkui Ke

Shanghai Huali Microelectronics Corporation, Shanghai

Received: Mar. 22nd, 2018; accepted: Apr. 11th, 2018; published: Apr. 18th, 2018

ABSTRACT

In order to efficiently elevate the semiconductor manufacturing Ingot quality management level, a suggested method which based on the data statistical analysis method coupled with information technology was introduced. The suggested method including the automatic and periodic semiconductor ingot data acquisition, standard semiconductor ingot management method and quality alarm feedback control method. By the application of this suggested method, it can be looking forward to transform the traditional statistic and sampling semiconductor manufacturing ingot quality management and control method into dynamic real-time feedback control method. Finally, it can be used for elevating the semiconductor manufacturing ingot quality management level.

Keywords:Wafer, Standard, Ingot, Quality Management and Control, Alarm Feedback

1. 概述

2. 解决方案

2.1. 铸锭数据采集

Figure 1. Ingot quality management solution for wafer manufacturing

Figure 2. Ingot quality management handling process

2.2. 铸锭品质管控方法

2.2.1. 铸锭自身参数对whitepixel影响的相关性分析

2.2.2. 异常铸锭发现

1) 选择产品种类。根据所选择的产品类型，得到铸锭列表信息；

2) 计算并保存该类产品的白像素点平均数值。将该数值进行保存并作为铸锭品质评估的标准；

3) 根据正态分布理论及数据统计，建立异常铸锭发现的阈值标准为：平均值±3*标准偏离；

4) 对异常铸锭进行标记并生成结果输出。

2.2.3 异常铸锭发现

3. 结束语

Figure 3. Abnormal Ingot identification flow

Strengthen Statistical Analysis Algorithm Application: Elevating Wafer Manufacturing Ingot Quality Management Level[J]. 材料科学, 2018, 08(04): 253-257. https://doi.org/10.12677/MS.2018.84027

1. 1. 梁德丰, 梁静, 钱省三. SPC在半导体晶圆制造厂的应用[J]. 半导体技术, 2004, 29(3): 35-37.

2. 2. 简祯富, 林鼎浩, 徐绍钟, 等. 建构半导体晶圆允收测试资料挖矿架构及其实证研究[J]. 工业工程学刊, 2001, 18(4): 37-48.

3. 3. 段桂江, 严懿, 王洋. 基于数据挖掘的质量成本分析与控制[J]. 计算机集成制造系统, 2013, 7(19): 1692-1696.

4. 4. 钮轶君, 钱省三, 任建华. 基于数据挖掘的半导体制造质量异常研究[J]. 观察与思考, 2006(2): 892-899.

5. 5. 胡玉. 半导体晶圆测试间的洁净度控制[J]. 科学技术, 2016(10): 407.