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Mondi Implements Statistics-Based Health Monitoring and Predictive Maintenance
技术
- 分析与建模 - 机器学习
- 分析与建模 - 预测分析
- 自动化与控制 - 可编程逻辑控制器 (PLC)
- 功能应用 - 远程监控系统
- 传感器 - 加速度计
- 传感器 - 压力传感器
- 传感器 - 温度传感器
适用行业
- 包装
适用功能
- 维护
用例
- 预测性维护
挑战
Mondi 工厂的挤压机和其他机器庞大而复杂，长达 50 米，高 15 米。每台机器最多由五个可编程逻辑控制器 (PLC) 控制，这些控制器记录机器传感器的温度、压力、速度和其他性能参数。每台机器每分钟记录 300–400 个参数值，每天生成 7 GB 的数据。
Mondi 在使用这些数据进行预测性维护方面面临着若干挑战。首先，工厂人员在统计分析和机器学习方面的经验有限。他们需要评估各种机器学习方法，以确定哪些方法为他们的数据产生了最准确的结果。他们还需要开发一个应用程序，将结果清晰而直接地呈现给机器操作员。最后，他们需要打包这个应用程序以便在生产环境中持续使用。
客户
蒙迪格罗纳
关于客户
Mondi Grona 是国际领先的包装和纸制品制造商。该公司的塑料生产厂每年提供约 1800 万吨塑料和薄膜产品。该工厂的 900 名工人大约在
解决方案
使用 MATLAB 开发和部署使用机器学习算法预测机器故障的监控和预测性维护软件
收集的数据
Machine Performance
数量效益
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