Over deze norm
||Informatie-integratie en interoperabiliteit
The global automotive industry is increasingly dependent on electronic product data to design and produce vehicles. Because of that dependency, problems with the quality of product data cause problems in developing and producing the products. When its member organisations all recognised the problem and were all working on some aspects of product data quality (PDQ), SASIG decided that the most effective approach would be to produce this common set of guidelines on the aspects of PDQ. Addressing product data quality is a complicated issue. One underlying problem is that each user of product data has different requirements for that data. The following are a few examples that focus on CAD data. - CNC programming . A CAD model of a part or tool that looks good on the screen or when printed on paper may not contain the right set of information necessary for automatically programming a CNC machine tool to make the part. There may be excess geometry or incomplete geometry, either of which confuse the CNC programming software or result in an incorrect part or tool. - Structural finite element analysis . A CAD model that represents a detailed design typically has far too much detail for structural analysis. The model needs to be simplified for a realistic chance of getting a useful simulation. Examples of details that can get in the way include fillets and radii added for such purposes as making the part more manufacturable. - Tooling design . The original CAD model for a part that is going to be moulded or cast may not have the parting line identified or the necessary draft built in. The allowance for the inevitable shrinkage of a solidifying part may not be built into the model either. Similar allowances have to be built into stamping dies for over-bending to compensate for spring back. When too much or too little information is provided or the information is incorrect, the result is increased cost and time. To be able to use poor quality data, someone must spend time, often extensive, putting the model in a usable form. Sometimes the required changes are so time-consuming and expensive that the recreation of a correct version of the model is more cost-effective. Recreating data leads to the potential for introducing further errors in the data.
||SASIG Product data quality guidelines for the global automotive industry