N-iX > 实例探究 > 通过大数据分析和预测性维护改善机上互联网

通过大数据分析和预测性维护改善机上互联网

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技术
  • 分析与建模 - 大数据分析
  • 分析与建模 - 预测分析
适用行业
  • 设备与机械
  • 电信
适用功能
  • 维护
  • 采购
用例
  • 边缘计算与边缘智能
  • 预测性维护
服务
  • 云规划/设计/实施服务
  • 数据科学服务
关于客户
Gogo 是一家全球机上宽带互联网提供商,与超过 16 家商业航空公司建立了合作伙伴关系。他们已在超过 2,900 架商用飞机和 6,600 架公务飞机上安装了机上连接技术。
挑战
Gogo 需要确保机上互联网的高速运行,并预测导致停机和成本浪费的设备故障。
解决方案
N-iX帮助Gogo迁移到AWS云,构建基于云的统一数据平台。他们还确保有效的天线健康监测并开发了预测卫星天线故障的模型。
运营影响
  • The migration to AWS cloud not only expanded the data processing capacity but also saved Gogo costs spent on licenses and the on-premise infrastructure. The cloud-based unified data platform collects and aggregates both structured and unstructured data, providing a comprehensive view of the system's performance. The application of data science models for predicting antenna equipment failure and reducing the NFF rate has significantly improved the reliability of the in-flight internet service. The comprehensive reports provided to Gogo's C-level decision-makers have enabled them to make informed decisions based on data. The reporting tool developed has been instrumental in identifying user pain-points during the first fifteen seconds of the Internet connection, thereby improving the user experience.

数量效益
  • Migration to the cloud reduced costs on licenses (Cloudera/Microsoft) and on-premises servers.

  • The no-fault-found rate was reduced by 75%, saving costs on unnecessary removal of equipment for servicing.

  • Predictive analytics allows predicting the failure of antennas (>90 %, 20-30 days in advance).

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