Research has shown that strict RE methodologies may be devised for any classification of parts as opposed to a customized approach for each part (analogous to group technology manufacturing).

Also, example methodologies for laser scanning illustrate that for every part family there exists an ideal manner in which parts may be scanned while avoiding potential trouble areas that may lead to poor scan quality or speed.
For any product classification, several factors are expected to influence the scan quality and duration. Of these factors, three have been shown to be the vitally important parameters in obtaining high-quality laser scan data:

 1. Coating - the type of material used to coat the part for maximum reflectivity.

 2. Horizontal point spacing - the horizontal distance between measured points.

 3. Part orientation and mounting - the position of the piece during the scanning procedure and the manner in which it is held in this position.

 Research results demonstrate credible evidence that the variability witnessed in scan quality is largely the result of the change in coating type, horizontal point spacing and part orientation/mounting. Further, changes in values of other variable parameters do not significantly affect the quality of the resultant scan data. In each experimental replication, substantial evidence suggested that the three aforementioned factors contribute most to the change in quality.

  Within these three factors deemed most important to the success of the scan, it is clear that a more dense point cloud - or smaller horizontal point spacing - produces a more accurate scan with fewer imperfections. However, the increase in density of the point cloud often leads to additional minor data editing tasks, which are easily solved using repair algorithms. Never does the increase in point cloud density lead to unsolvable data problems that would not have existed with a less dense data set. The converse is often true, however.

  Occasionally a low-density data set will exhibit data imperfections, such as a hole of missing points, that a high-density set will eliminate through its more defined search for data.
The single variable that most affects the quality of a scan is the part mounting and orientation.Any gains in quality seen as a result of optimizing the other variable settings can quickly be lost when improperly orienting the part. Furthermore, a subtle alteration of a part's orientation can lead to a substantial increase or decrease in scan quality. Often, in cases of oddly-shaped parts, a small number of orientation iterations can lead to a considerable improvement in quality.                   

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