Data-driven Production Planning Models for Wafer Fabs: An Exploratory Study

Cycle time, which is of order of ten weeks for most products in semiconductor wafer fabrication facilities (wafer fabs), must be explicitly considered in production planning models. Cycle times depend nonlinearly on the resource workload in a wafer fab. Different data-driven (DD) production planning...

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Bibliographic Details
Published in:IEEE transactions on semiconductor manufacturing 2023-08, Vol.36 (3), p.1-1
Main Authors: Volker, Tobias, Monch, Lars
Format: Article
Language:English
Subjects:
Computational modeling
Costs
Cycle time
Data-driven Production Planning Models
Indexes
Industrial plants
Integrated circuit modeling
Planning
Production planning
Sampling
Semiconductor device modeling
Simulation Experiments
Simulation models
Workflow
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Summary:Cycle time, which is of order of ten weeks for most products in semiconductor wafer fabrication facilities (wafer fabs), must be explicitly considered in production planning models. Cycle times depend nonlinearly on the resource workload in a wafer fab. Different data-driven (DD) production planning formulations are studied in this paper. Such formulations are based on a set of system states representing the congestion behavior of a wafer fab with work in process (WIP) and resulting output levels. Different WIP-output relations in the DD formulations are investigated. In addition, different methods are proposed to gather representative sets of system states. The DD formulations are compared with the Allocated Clearing Function (ACF) formulation with respect to profit and cost values using simulation models of a scaled-down and a large-sized multiproduct wafer fab, respectively. The simulation results show that some DD variants are able to outperform the ACF formulation under several experimental conditions.
ISSN:0894-6507
1558-2345
DOI:10.1109/TSM.2023.3277410