Target Correlation and Allocation Using Reliability Metrics to Validate Design Effectiveness of Improved Sample 2018-01-0790
All automotive components, systems and vehicles undergo stringent validation protocol standards. Nevertheless, there are certain factors which cannot be captured during validation phase and result in field failures. With multiple players prying for market share in the automotive industry, timely resolution of field failures can go a long way in retaining customer base. In such a scenario, when customer’s tolerance on field failures is very limited, failures need severe attention and must be captured as early as possible to cut down warranty expenses. This project aims at creating a methodology to simulate field failures and validate improved design. The reliability parameters such as β (Shape Factor), η (Scale factor), Reliability and life are estimated and the values are compared between field and lab conditions. Life estimated in field conditions (Failure data base) and lab are correlated using Reliability techniques and target is established for validating improved sample. Cross functional team works on design improvement and analyzes the proposed improvement using Finite Element Analysis for design effectiveness. Upon establishing design effectiveness, Reliability demonstration tests (RDT) are designed to assess the reliability of the component at the established target hours. During the tests, if a component fails, target is revised using reliability demonstration table to meet reliability requirements. The improved sample will be monitored in field for validation effectiveness and correlation.