ABSTRACT
Chapter 11, “Sustaining Product Reliability,” explores issues that are often experienced in fielded product data. Two prevalent factors are noise in the collected data and the misalignment of the field data to that of the final reliability model. Depending on the causes of the noise and ambiguities, data behavior will be different. Fortunately, many misbehaviors are known and the root causes of the noise may be attributed to misalignment of field data with the reliability model, a mismatch between field data and fitted distributions, use profile discrepancies, manufacturing process variation, and mixed-failure modes. Once field reliability failures are identified, they need to be investigated in a systematic approach. DMAIC, a robust Six Sigma tool, which stands for define, measure, analyze, improve, and control, may be used to systematically investigate, identify, and remediate failure root causes.
