Enterprise AI for Predicting HVAC Chiller Failures

• 分析与建模 - 预测分析

• 设备与机械

• 质量预测分析

• 数据科学服务

• 加载和聚类传感器数据以用于预测模型
• 训练机器学习模型以预测冷水机组故障
• 通过在 < 1 周内完成项目来展示开发和部署的速度

未披露

• 全球设备制造商和服务公司
• 100,000 名员工
• 300亿美元的收入

• 在 4 天内配置 C3 AI 可靠性
• 为 165 台 HVAC 冷水机加载了 3 年的传感器数据（每台冷水机 40-50 个传感器馈电）
• 开发了 163 个分析作为故障预测算法的输入
• 训练和调整机器学习模型，以 73% 的准确率和 71% 的召回率预测冷水机组故障

• [Data Management - Data Analysis]
  

  The manufacturer deployed C3 AI Reliability for 165 of its chillers to address the objectives. The customer selected C3 AI for its proven ability to rapidly integrate sensor data, normalize and cluster disparate readings, and run machine learning algorithms to identify deteriorating conditions before failures occur.

• $178M annual benefit identified. 73% model precision. 71% model recall

• In 4 days, C3 AI and the customer loaded, normalized, and mapped 3 years of sensor data for all 165 chillers, created custom analytics on these data, and configured a machine learning algorithm to predict chiller failure events