For quality control workers, nothing could be more frustrating than knowing the key to unlock a particular problem is available, but that it is lost somewhere in a mountain of data. This voluminous data has been collected by a touch from a coordinate measuring machine, the click of an optical camera, the beep of a bar code scanner or from some of the multitude of other test measurement and inspection routines that are daily occurrences in modern factories.
For many companies, the data generated from these quality control efforts and filtered through statistical analysis soft-ware represents too much information stored in too many places for any one person to grasp. For them, data mining could be the answer. Data mining is the process of finding patterns and correlations in large amounts of data. Software from a handful of companies combine pattern recognition with statistical and mathematical techniques to root through these millions of data values looking for patterns.