Customer feedback in the form of warranty/field performance is an important and direct indicator of quality and robustness of a product. Linking warranty information to manufacturing measurements can identify key <i>design parameters</i> and <i>process variables</i> (DPs and PVs) that are related to warranty failures. Warranty data has been traditionally used in reliability studies to determine failure distributions and warranty cost. This paper proposes a novel Fault Region Localization (FRL) methodology to map warranty failures to manufacturing measurements (hence to DPs/PVs) to diagnose warranty failures and perform tolerance revaluation. The FRL methodology consists of two parts: 1. Identifying relations between warranty failures and DPs and PVs using the Generalized Rough Set (GRS) method. GRS is a supervised learning technique to identify specific DPs and PVs related to the given warranty failures and then determining the corresponding Warranty Fault Regions (WFR), Normal Region (NR) and Boundary region (BND). GRS expands traditional Rough Set method by allowing inclusion of noise and uncertainty of warranty data classes. 2. Revaluating the original tolerances of DPs/PVs based on the WFR and BND region identified. The FRL methodology is illustrated using case studies based on two warranty failures from the electronics industry.