Computing algorithms and technology are providing organizations and companies new methods in order to achieve their goals. Understanding complex physical phenomena, in which multiple variables are interacting, over time leads to advancement in many engineering fields. This understanding is based on processing huge amounts of readings and data. In this paper, we show the power of data visualization, when using many machining process’ sensors data in order to understand and to analyze the machining outcomes. Information is extracted from experimental results. Logical Analysis of Data (LAD) is used as knowledge extraction approach, which is presented in the form of characteristic patterns. The input data, the outcomes and the patterns are presented visually by using some visualization tools. We conclude with a discussion of the potential use of the data visualization.
Visual data mining of faults in machining process based on machine learning
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