Process condition monitoring

Proceedings of IEEE Technical Conference on Rubber and Plastics Industry Pub Date : 1994-04-26 DOI:10.1109/RAPCON.1994.337328

L.E. Stockline

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Abstract

The call in the 1990's is for a higher level of quality at a faster rate. This task can be insurmountable if process control is not taken to a new level of implementation. Today we attempt to understand the results of a product produced, and correct any variations in this process, after the product is produced. In the future a self teaching "ideal" signature of the process will be stored after the process has been optimized. A trending tolerance will be established so that, in-process, any changes can be observed, and corrective actions can be taken. Force and color monitoring are but two of the many in-process methods which are being employed by a self teaching method. Slave microprocessors can then be provided that monitor the application whenever product is involved. The next step would then have the slaves report to a PC host that collects trending data. This then would allow a "cause and effect" analysis which can be seen in real time, whenever a change in the process is being manually manipulated. The end result will be online inspection that will eliminate many of the offline manual inspections.<>

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工艺状态监测

20世纪90年代的呼声是以更快的速度追求更高水平的质量。如果不把过程控制提升到一个新的实现水平，这个任务就无法完成。今天，我们试图了解产品生产的结果，并在产品生产后纠正这个过程中的任何变化。在未来，过程的自我教学“理想”签名将在过程优化后存储。将建立趋势公差，以便在过程中可以观察到任何变化，并采取纠正措施。力和颜色监测只是许多过程中方法中的两种，这些方法正在被自学方法所采用。然后可以提供从微处理器，在涉及产品时监视应用程序。下一步是让从机向收集趋势数据的PC主机报告。这将允许“因果”分析，可以实时看到，无论何时手工操作过程中的更改。最终的结果将是在线检查，这将消除许多离线人工检查

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of IEEE Technical Conference on Rubber and Plastics Industry

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