C3 IoT > 实例探究 > 优化半导体制造良率

优化半导体制造良率

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 Optimizing Semiconductor Manufacturing Yield with IoT - IoT ONE Case Study
技术
  • 分析与建模 - 机器学习
  • 功能应用 - 制造执行系统 (MES)
适用行业
  • 设备与机械
  • 半导体
适用功能
  • 产品研发
  • 质量保证
用例
  • 添加剂制造
  • 制造过程模拟
服务
  • 数据科学服务
  • 测试与认证
客户
关于客户

大型高性能半导体制造商

挑战

这家总部位于美国的制造商设计并提供一系列尖端产品,包括射频滤波器、放大器、调制器、衰减器等。然而,该制造商的一些最复杂产品的总产量低于预期。

解决方案

一家大型高性能半导体制造商实施了 C3 AI 工艺优化,以优化其无线产品的制造工艺,展示了在工艺早期预测低良率晶圆并确定工艺改进以提高整体良率的能力。

通过实施 C3 AI 工艺优化,制造商现在可以识别不良晶圆,量化节省的时间和成本,并调整设计和制造工艺以优化产量。制造优化和设计每年对经济的总影响超过 3000 万美元。

运营影响
  • The implementation of the C3 AI Process Optimization solution has had a significant impact on the manufacturer's operations. The ability to predict low-yield wafers early in the process and identify process improvements has led to an increase in overall yield. The solution has also enabled the company to identify bad wafers, quantify time and costs saved, and tune design and manufacturing processes to optimize yields. The insights delivered through the C3 AI Process Optimization user interface have been instrumental in driving manufacturing optimization. The solution has also demonstrated the potential of AI in manufacturing, with the company now able to build machine learning algorithms to predict die quality and low-yield wafers.
数量效益
  • $39 million estimated annual economic impact
  • Created 3 terabyte unified data image of 830,000 files
  • Created more than 1,500 relevant features

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