推动更好的业务决策
技术
- 功能应用 - 计算机化维护管理系统 (CMMS)
- 功能应用 - 制造执行系统 (MES)
适用行业
- 电子产品
- 设备与机械
适用功能
- 维护
- 采购
用例
- 添加剂制造
- 数字线程
服务
- 硬件设计与工程服务
- 系统集成
挑战
问题是，为了确定他们工厂的实际利用率，Service Thread 不得不依靠对机器进行频繁和选择性的亲自检查。
但是，这种系统的缺点并没有在 Service Thread 上丢失。检查员每周将花费大约 10 小时或每年 500 小时进行这些分析。这种方法的另一个问题是人为错误的可能性及其对整体商店绩效的影响。最后，由于数据范围相当有限，他们的最终估计不一定准确。
客户
服务线程
关于客户
Service Thread是美国领先的商业线和纱线制造商。他们位于北卡罗来纳州劳林堡的工厂在 115,000 平方英尺的占地面积和 24 种不同的机器类型中拥有超过 3,000 个主轴（操作位置）。在他们努力优化的过程中，这些变量成为了 Service Thread 对工厂绩效进行有效监控和分析的障碍。
解决方案
该团队决定设计自己的硬件解决方案，使用粒子光子从机器现有传感器收集数据。
Logical Advantage 的最终硬件解决方案能够同时从 16 个主轴收集数据。然后，这些数据通过 Particle Cloud 传递到使用 Wi-Fi 的 Microsoft 的 Azure IoT 中心。然后，Logical Advantage 构建了一个简单的移动应用程序，用于配置主轴传感器。
数量效益
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