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Complex Discrete Manufacturing with ThingWorx Analytics

 Complex Discrete Manufacturing with ThingWorx Analytics - IoT ONE Case Study
技术
  • 分析与建模 - 机器学习
  • 分析与建模 - 预测分析
挑战

ABC 在利用收集到的数据时面临两个主要问题。一是所收集数据的规模、复杂性和差异性需要大量工时来处理和评估。二是由于数据科学分析的性质,实时数据无法投入使用。

客户
未公开
关于客户
ABC Manufacturing 运营着 27 个全球制造设施,战略性地分布在世界各地,为我们的国际客户提供直接支持和服务。
解决方案

ThingWorx Analytics 是一种自动执行高级预测分析的学习技术。该技术使用专有的人工智能和机器学习技术自动从数据中学习、发现模式、构建经过验证的预测模型,并将信息发送到几乎任何类型的应用程序或技术。

收集的数据
Facility Health Status, Humidity, Production Efficiency, Temperature
运营影响
  • [Efficiency Improvement - Maintenance]
    Cloud solutions enable aggregation of 'big data' to automatically detect patterns, anomalies, and flag machines for maintenance before downtime, manufacturing errors, or yield faults occurred.
  • [Efficiency Improvement - Maintenance]
    Real-time status reports enable maintenance personnel to remotely diagnose the status of a device.
  • [Data Management - Data Analysis]
    Data Mining, prognostics, diagnostics, and embedded intelligence are used to make ABB's production line smarter so that they can meet their customer's needs.
数量效益
  • ThingWorx Analytics was able to quickly analyze billions of points of information to determine that a particular failure pattern occurred when product line 2 was running operation 4467ANX when the ambient temperature was between 77 degree celsius and 79 degree celsius.

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