SHIFTING PRODUCTION BOTTLENECKS: CAUSES,CURES, AND CONUNDRUMS

We examine the phenomenon of shifting production bottlenecks from an analytic perspective. We quantify the propensity of a work center to be a bottleneck, defined as maximal queue length, using a simple Jackson production network model. Comparison of the analytic model against an empirical simulation-based model shows that the two are in good agreement. A scalar measure of bottleneck shiftiness is proposed and used to investigate several policies for mitigating shiftiness. Simulation experiments show that several commonly observed managerial policies for coping with shifting bottlenecks actually increase shiftiness, but that shiftiness declines when the capacity of nonbottleneck resources is increased.     

A SYSTEMATIC STRATEGY FOR OPTIMIZING MANUFACTURING OPERATIONS

A manufacturing optimization strategy is developed and demonstrated, which combines an asset utilization model and a process optimization framework with multivariate statistical analysis in a systematic manner to focus and drive process improvement activities. Although this manufacturing strategy is broadly applicable, the approach is discussed with respect to a polymer sheet manufacturing operation. The asset utilization (AU) model demonstrates that efficient equipment utilization can be monitored quantitatively and improvement opportunities identified so that the greatest benefit to the operation can be obtained. The process optimization framework, comprised of three parallel activities and a designed experiment, establishes the process-product relationship. The overall strategy of predictive model development provided from the parallel activities comprising the optimization framework is to synthesize a model based on existing data, both qualitative and quantitative, using canonical discriminant analysis, to identify main effect variables affecting the principal efficiency constraints identified using AU, operator knowledge and order-of-magni-tude calculations are then employed to refine this model using designed experiments, where appropriate, to facilitate the development of a quantitative, proactive optimization strategy for eliminating the constraints. Most importantly, this overall strategy plays a significant role in demonstrating, and facilitating employee acceptance, that the manufacturing operation has evolved from an experienced-based process to one based on quantifiable science.