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Detect faults before they occur
Greater safety, better comfort and innovative functions: The increasing complexity of technical systems in vehicles presents an even greater challenge for manufacturers and suppliers. Part Average Analysis, developed in 2001, permits the early detection of stochastic and systematic failures, called “dormant failures.” The product quality of new parts and the value creation process of technical systems can be improved substantially with this new method. PAA aims to minimize in particular the faults that frequently arise during the first operating hours of a vehicle and are caused by a technical malfunction of a unit or component. Ideally, the target is zero-fault production. The PAA is thus an analysis process and a preventive measure at the same time. In the iTAC.MES.Suite implements the analysis methods of the Part Average Analysis as a standard. A decisive factor here is the online detection of anomalous components, which is ensured by bi-directional coupling of the testing systems. This allows immediate preventive action during the manufacturing process, i.e. the parts that have come to attention are eliminated from further processing, which is an elementary contribution to zero-fault production and failure avoidance. Cross-supplier PAA monitoring becomes possible. The PAA 2.0 is based on the comparison of measurement data. The PAA examines the data of “good” parts whose parameter values are within a permitted value range but which behave in a peculiar way compared to other parts. Anomaly analysis and process capability analysis run in two functions in the web-based standard software iTAC.MES.Suite:
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