Allocation of variance reduction targets under the influence of supplier interaction

A common quality improvement strategy used by manufacturers is to periodica lly allocate quality improvement targets among their suppliers. We propose a formal modelling and optimization approach for assessing quality improvem ent targets for suppliers. In this approach it is understood that a manufac turer's quality improvement results from reductions in supplier process var iances, which occurs only through investments in learning. A constrained no nlinear optimization model is developed for determining an optimal allocati on of variance reduction target that minimizes expected total cost, where t he relationship between performance measures and the set of design paramete rs is generally represented by second-order polynomial functions. An exampl e in the fabrication of a tyre tread compound is used both to demonstrate t he implementation of our proposed models as well as to provide an empirical comparison of optimal learning rates for different functional relationship s between the performance measures and the set of design parameters.