Abstract: Cycle time and throughput of a manufacturing facility is effectively manages by a control system that employs a combination of a long-term horizon model and at least one short-term horizon model to generate control signals for a set of machines in a manufacturing facility. The long-term horizon model determines long-term average time allocation percentage for each machine for a given set of throughput targets and cycle time targets for products to be manufactured. Each of the at least one short-term horizon model determines queues for immediate use at processing tools, while the queues are subjected to a secondary adjustment based on the time allocation constraints generated by the long-term horizon model. The combination of the long-term and the at least one short-term horizon models provides a stable long-term proactive WIP bubble-management as well as short-term WIP bubble management.

Abstract: Cycle time and throughput of a manufacturing facility is effectively manages by a control system that employs a combination of a long-term horizon model and at least one short-term horizon model to generate control signals for a set of machines in a manufacturing facility. The long-term horizon model determines long-term average time allocation percentage for each machine for a given set of throughput targets and cycle time targets for products to be manufactured. Each of the at least one short-term horizon model determines queues for immediate use at processing tools, while the queues are subjected to a secondary adjustment based on the time allocation constraints generated by the long-term horizon model. The combination of the long-term and the at least one short-term horizon models provides a stable long-term proactive WIP bubble-management as well as short-term WIP bubble management.