物联网数据分析案例研究 - 包装薄膜制造商
技术
- 分析与建模 - 预测分析
- 分析与建模 - 过程分析
- 传感器 - 压力传感器
适用行业
- 包装
适用功能
- 质量保证
用例
- 机器状态监测
- 质量预测分析
- 根因分析与诊断
客户
未公开
关于客户
一家专门从事包装薄膜生产的领先制造公司实施了 Altizon 的 Datonis Mint，这是一种减少质量下降的智能物联网解决方案。了解 Altizon 的 Datonis MInt – 制造智能解决方案如何提供帮助
挑战
该公司按订单生产或按订单配置生产包装薄膜。从产品特性的角度来看，每个订单都有不同的要求，因此需要相应地调整机器的设置。如果薄膜质量不符合要求的标准，质量下降会影响客户交付，导致客户不满意并导致利润率下降。最大的挑战是找出真正的根本原因并为此制定补救措施。
解决方案
在“包装薄膜”制造过程中，薄膜最终在“卷绕机”机器上向下游卷绕，并在“分切”机器上按订单进行切割。该解决方案需要能够处理历史机器数据并在机器设置和生产输出之间建立所需的相关性。部署的解决方案有助于收集历史性能数据。它使质量团队能够监控关键的机器设置参数，确定它们处于统计控制状态，并最终将过程和机器数据与不同类型的质量故障相关联。该解决方案 (Datonis MInt) 还使用相关分析帮助识别从 30 个参数到 2 个（压力和张力）的关键质量参数。基于收集到的数据建立了一个规范的质量模型，为每个新订单推荐产品配置的机器设置。这有助于减少质量下降并实现可预测的质量。
收集的数据
Process Parameters, Machine Performance, Machine Settings
运营影响
数量效益
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