Therefore, what a CNC programmer would define as high quality data would not be described as such by someone setting up a finite element analysis model. This conundrum of differing data requirements must frame all discussions of product data quality. There are a number of elements that determine product data quality. The need for correct representations- Product data that do not correctly represent the product will inevitably lead to incorrect results and other problems in downstream activities. A classic example of this is a dimensioned geometric representation in which the numerical value of a dimension has been changed without changing the geometry addressed by the dimension.
Correct representations require good model building techniques as well as good software tools.
A clear identification of product data version, effectivity, approvals, etc.- Product data inevitably changes over time and therefore any given set of product data needs clear identification of what version it is, who approved it, the time period for which it is effective, and so on. 2.2 Varying Elements Some product data quality elements have different manifestations depending on the downstream applications. Perhaps the lowest level of detail is in graphics for user manuals. They typically require only product data that describe visual appearance, regardless of the underlying part numbers, and often from only a single view. Contrast that with CNC machining, which requires detailed information that completely describes the geometry of the machined surfaces, including applicable dimensions and tolerances.