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3M Manufacturing Plant Leverages Azure SQL Edge for Efficiency and Cost Savings
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
- 电子产品
- 运输
适用功能
- 物流运输
- 维护
用例
- 自动化制造系统
- 预测性维护
服务
- 云规划/设计/实施服务
- 数据科学服务
挑战
3M 是一家跨国集团公司，在各个业务部门生产 60,000 多种产品。在其美国制造工厂之一，3M 企业研究实验室和当地 3M 制造团队发现了一个预测异常并利用这些见解来减少制造停机时间的机会。面临的挑战是集成来自两条生产线的数据流，将它们关联起来，然后在本地运行分析和机器学习。然而，两个系统的数据到达时间不同，工厂的网络连接受到限制。该团队需要一个能够提供必要的性能、管理和安全性的解决方案。
关于客户
3M 是一家跨国集团公司，以其广泛的产品而闻名，从透明胶带和便利贴等办公用品到 N95 呼吸器等医疗设备。该公司将其 60,000 多种产品分为四个不同的业务组：安全和工业、运输和电子、医疗保健以及消费者。 3M 成立于 1902 年，是一家总部位于明尼苏达州的矿业公司，现已发展成为财富 500 强公司，在 87 个国家/地区拥有 96,000 名员工。该公司以其对制造流程的创新和效率的承诺而闻名。
解决方案
该团队建议使用通过 Microsoft Azure IoT Edge 部署的 Microsoft Azure SQL Edge 构建自定义模块。该解决方案使他们能够在本地边缘处理和分析大数据。他们开发了一种算法，可以在生产线上出现问题前几个小时进行预测。该模块位于 Azure IoT Edge 设备上，经过云训练并部署到生产线数据所在的 Azure SQL Edge。它无缝运行以创建预测。通过关联和分析两个数据流，他们能够将分析和机器学习应用于数据。使用 Azure SQL Edge，该团队创建了一个将数据从那里同步到云的解决方案，该解决方案在几乎任何网络条件下都具有容错能力。该解决方案还解决了工厂网络容量有限的问题。
运营影响
数量效益
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