Robust Parameter Design for Quality and Reliability Issues Based on Accelerated Degradation Measurements

Manufacturing quality and lifetime testing conditions may affect product reliability measurements. The literature for the design of experiments (DOE) and robust product optimization considering both quality and reliability issues is scarce. This article develops a model to include both manufacturing variables and accelerated degradation test (ADT) conditions. A simple algorithm provides calculations of the maximum likelihood estimates (MLEs) of these model parameters and percentile lifetimes. Variances of these estimates are derived based on large sample theory. Our DOE plans focus on deciding replication sizes and proportions of the test-units allocated at three stress levels for various manufacturing and ADT conditions. This work also explores robust parameter design (RPD) optimizations for selected controllable manufacturing variables to achieve the longest product lifetime and smallest variation in lifetime distributions.