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Application of Special Cause Control Charts to Green Sand Process

机译:特殊原因控制图在绿砂工艺中的应用

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Statistical Process Control (SPC) based on the well known Shewhart control charts, is widely used in contemporary manufacturing industry, including many foundries. However, the classic SPC methods require that the measured quantities, e.g. process or product parameters, are not auto-correlated, i.e. their current values do not depend on the preceding ones. For the processes which do not obey this assumption the Special Cause Control (SCC) charts were proposed, utilizing the residual data obtained from the time-series analysis. In the present paper the results of application of SCC charts to a green sand processing system are presented. The tests, made on real industrial data collected in a big iron foundry, were aimed at the comparison of occurrences of out-of-control signals detected in the original data with those appeared in the residual data. It was found that application of the SCC charts reduces numbers of the signals in almost all cases It is concluded that it can be helpful in avoiding false signals, i.e. resulting from predictable factors.
机译:基于众所周知的Shewhart控制图的统计过程控制(SPC)被广泛用于当代制造业,包括许多铸造厂。但是,经典的SPC方法要求测量的量例如过程或产品参数不是自动相关的,即它们的当前值不取决于前面的参数。对于不遵守该假设的过程,提出了特殊原因控制(SCC)图,利用了从时间序列分析中获得的剩余数据。本文介绍了将SCC图应用于绿砂处理系统的结果。这些测试是根据在大型铸铁厂中收集的真实工业数据进行的,旨在将原始数据中检测到的失控信号与残留数据中出现的失控信号进行比较。已经发现,在几乎所有情况下,SCC图的应用都会减少信号的数量。结论是,这有助于避免错误信号,即由可预测因素引起的错误信号。

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