Qualitätsdatenaustauschformat der Automobilindustrie Page 10 Automotive Quality Data Exchange Format

4.4 Create Example Data Sets

The certification of the export interface is based mainly on the verification of sample files for conformity with the specifications of the Q-DAS
® ASCII transfer format. Because, depending on the individual application, different data fields and data field relations are relevant, several fiels must be created and made available depending on the scope of the certification. • one file per application scenario in sample analysis and process capability study, or alter-natively, one file with characteristics of all the supported characteristics types (K2004) • one file per supported group type (K2008), or alternatively, one file with characteristics of different group types • one file with several characteristics per evaluation type (K2202) in Gage Capability • application examples for different measurement value attributes (K0002) (behavior in case of incomplete measuring cycles (attribute 255/256)) • examples of measurements with several events (K0005) and process parameters (K0011) • examples of the supported file formats (DFQ, DFD/DFX) • examples of the supported write modes (count up mode, append mode, individual meas-urement)

4.5 Return of the Certification Documents

After realization of the export interface, the gage supplier makes available the sample data sets to Q-DAS
® and returns the certification documents to Q-DAS
® : • sample files per application • list of supported data fields • printouts of data input screen masks; documentation of the export interface • exact description of the interface with version number • counter-signed frame contract

4.6 Behavior Verification of the Writing Systems

Q-DAS
® will verify the following aspects, based on the screen shots made provided or on the installed system: • possibility to record additional data (i.e. varying from measurement to measurement) • integration and selection possibility of catalog records (Q-DAS
® catalog file) • identification of faulty data input records (i.e. incorrect field type or field length) • identification of plausibility problems (i.e. USL < LSL)
Version 1.0 E 2006-03-16