Development of a Method for Automatic Extraction of Know -How from Historical Information on Operation

我们已经开发了一种方法，自动提取的操作诀窍，从历史信息有关工厂的运作。在该方法中，使用数据挖掘工具之一的C4.5提取操作诀窍作为if-then规则。然后，特殊的预处理应该是必要的，以处理这样的时间序列数据作为历史信息有关工厂的运作，因为事件或记录处理C4.5自然是相互独立的，记录的顺序是没有意义的。在这项研究中，我们注意到，运营商不仅观察变量的现值，而且还观察变量的趋势，并通过判断趋势是否定性地增加或减少来决定他们的运营。因此，我们建议使用采样期间之间变量差异的定性值。因此，可以肯定的是，如果可以进行适当的变量选择和预处理，可以从有关工厂操作的历史信息中提取操作诀窍。然而，C4.5有时会提取错误的规则，这些规则可以用因果关系的反比来解释。在今后的工作中，我们将联合收割机C4.5与一个概念，可以解释因果关系，如相关系数。

We have developed a method for automatic extraction of operational know -how from historical information concerning plant operations. In this method, an operational know-how is extracted as an if-then rule by using C4.5, which is a one of tools for data mining. Then, special preprocessing should be necessary to deal with such a time series data as historical information concerning plant operations because events or records treated by C4.5 are naturally independent each other and the 'order of records is meaningless. In this study, we pay attention that operators watch not only present values of variables but also trends of variables and make a decision about their operations by judging whether trends are qualitatively increased or decreased. So, we have proposed to use qualitative values of differences of variables between sampling periods. As a result, it has been definitely that operational know-how can be extracted from historical information concerning plant operations if adequate selection and preprocessing of variables may be performed. However, C4.5 sometimes extracted wrong rules that were explained by inverse relations between cause and effect. In future work, we will combine C4.5 with a concept that can explain cause and effect relationship such as correlation coefficients.