Profiling Methods for Customer Issues & Returns
Identifying and predicting outcomes in customer issues and returns is often inaccurate. Methods to identify and positively recall product in the field are imprecise. Often analysis of these problems results being identified at NTF. Using issue stronger methods of traceability, profiling, predictive quality measures, automated commonality, knowledge management techniques and machine learning Xilinx has been able to deepen product controls, shorten time to issue resolution, & reduce the need for product returns.