Finite capacity planning algorithm for semiconductor industry considering lots priority

Abstract

International audienceA finite capacity planning heuristic is developed for semiconductor manufacturing with high-mix low-volume production, complex processes, variable cycle times and reentrant flows characteristics. The proposed algorithm projects production lots trajectories (start and end dates) for the remaining process steps, estimates the expected load for all machines and balances the workload against bottleneck tools capacities. It takes into account lots' priorities, cycle time variability and equipment saturation. This algorithm helps plant management to define feasible target production plans. It is programmed in java, and tested on real data instances from STMicroelectronics Crolles300 production plant which allowed its assessment on the effectiveness and efficiency. The evaluation demonstrates that the proposed heuristic outperforms current practices for capacity planning and opens new perspectives for the production line management

Methodology and model-based DSS to managing the reallocation of inventory to orders in LHP situations. Application to the ceramics sector

“…The DSS generates product configurations that can be attractive to customers and suggests which versions of the products must be offered to customers in each period, in order to saturate the available capacity taking into account the attractiveness of the package of components for customers. A similar study can be found in [29] in which a DSS is proposed with the objectives of minimizing the delay of customer orders and optimizing the rate of use of the equipment, applied to the production lines in the semiconductor sector.…”