The Development of Tools for the Automatic Extraction of Desired Information from Large Amounts of Engineering Data

Product development processes generate large quantities of experimental and analytical data. The data evaluation process is usually quite lengthy since the data needs to be extracted from a large number of individual output files and arranged in suitable formats before they can be compared. When the data quantity grows extremely large, manual extraction cannot be done in a limited timeframe. This paper describes a set of tools developed by MTS engineers to automatically extract the desired information from a large number of files and perform data post-processing. The tools greatly improved both speed and accuracy of the evaluation process during the development of a sound quality-based end-of-line inspection system for seat tracks [1]. It allowed engineers to quickly gather a comprehensive understanding of the relative importance of individual design parameters and of their correlation to the subjective perception of the sound quality of the seat track.