European Mask and Lithography Conference EMLC 2024 – Grenoble, France
This paper presents the challenges and results of implementing an optimization-based scheduling engine in a high-mix 300mm fully automated semiconductor manufacturing facility. Efficient scheduling of lots on photolithography machines is crucial due to their high cost and critical role in production. Optimally managing the transportation, storage and inspection of a large number of masks is essential to ensure this efficiency. Initially deployed in the cleaning and diffusion work center, the optimization engine was adapted for photolithography and is operational since May 2024. This generic engine solves large multi-objective scheduling problems in minutes, considering diverse constraints related to processing and transportation resources, product quality, and global production targets. The successful deployment demonstrates the engine’s potential for full factory scheduling, with ongoing efforts to enhance its genericity, efficiency, and effectiveness.
Winter Simulation Conference 2023 – San Antonio, TX
This paper surveys the industrialization of an advanced optimization engine that was developed by Planimize and put into production in the cleaning and diffusion work center of the most advanced factory of a semiconductor manufacturing company. Hundreds of lots requiring several thousands operations in the work center must be scheduled on about 150 machines, while taking complex constraints into account, in particular hundreds of time constraints, and optimizing a collection of criteria. The optimization engine provides significantly better results, runs significantly faster, and can handle much larger problem instances than the previous Constraint Programming optimization engine used in the factory
A. Bitar, S. Knopp, K. Tamssaouet (Planimize), L. Delcloy and R. Roussel (STMicroelectronics, Crolles)
European Journal of Operational Research – 2022
Tamssaouet.K, Dauzère-Pérès, S., Knopp, S., Bitar, A., & Yugma, C.
Computers & Operations Research – 2021
In this paper, a scheduling problem on non-identical parallel machines with auxiliary resources and sequence-dependent and machine-dependent setup times is studied. This problem can be found in various manufacturing contexts, and in particular in workshops of wafer manufacturing facilities. Three different criteria are defined and analyzed: The number of products completed before the end of a given time horizon, the weighted sum of completion times and the number of auxiliary resource moves. The first criterion is maximized, while the two others are minimized. The first and the third criteria are not classical in scheduling theory, but are justified in industrial settings…
Bitar, A., Dauzère-Pérès, S., & Yugma, C.
This paper addresses the job-shop scheduling problem in which the machines are not available during the whole planning horizon and with the objective of minimizing the makespan. The disjunctive graph model is used to represent job sequences and to adapt and extend known structural properties of the classical job-shop scheduling problem to the problem at hand. These results have been included in two metaheuristics (Simulated Annealing and Tabu Search) with specific neighborhood functions and diversification structures. Computational experiments on problem instances of the literature show that our Tabu Search approach outperforms Simulated Annealing and…
Tamssaouet, K., Dauzère-Pérès, S., & Yugma, C.
We consider a Flexible Job-Shop scheduling problem with batching machines, reentrant flows, sequence dependent setup times and release dates while considering different regular objective functions. Semiconductor manufacturing is probably one of the most prominent practical applications of such a problem. Existing disjunctive graph approaches for this combined problem rely on dedicated nodes to explicitly represent batches. To facilitate modifications of the graph, our new modeling reduces this complexity by encoding batching decisions into edge weights. An important contribution is an original algorithm that takes batching decisions “on the fly” during…
Knopp, S., Dauzère-Pérès, S., & Yugma, C.
Journal of Scheduling – 2016
Bitar, A., Dauzère-Pérès, S., & Yugma, C.
Winter Simulation Conference - 2020
Le Quéré, É., Dauzère-Pérès, S., Tamssaouet, K., Maufront, C., & Astie, S.
Winter Simulation Conference - 2018
Tamssaouet, K., Dauzère-Pérès, S., Yugma, C., Knopp, S., & Pinaton, J.
Proceedings of the Winter Simulation Conference - 2014.
Knopp, S., Dauzère-Pérès, S., & Yugma, C.
Proceedings of the Winter Simulation Conference - 2014
Bitar, A., Dauzère-Pérès, S., & Yugma, C.
European Mask and Lithography Conference EMLC 2024 – Grenoble, France
This paper presents the challenges and results of implementing an optimization-based scheduling engine in a high-mix 300mm fully automated semiconductor manufacturing facility. Efficient scheduling of lots on photolithography machines is crucial due to their high cost and critical role in production. Optimally managing the transportation, storage and inspection of a large number of masks is essential to ensure this efficiency. Initially deployed in the cleaning and diffusion work center, the optimization engine was adapted for photolithography and is operational since May 2024. This generic engine solves large multi-objective scheduling problems in minutes, considering diverse constraints related to processing and transportation resources, product quality, and global production targets. The successful deployment demonstrates the engine’s potential for full factory scheduling, with ongoing efforts to enhance its genericity, efficiency, and effectiveness.
Winter Simulation Conference 2023 – San Antonio, TX
This paper surveys the industrialization of an advanced optimization engine that was developed by Planimize and put into production in the cleaning and diffusion work center of the most advanced factory of a semiconductor manufacturing company. Hundreds of lots requiring several thousands operations in the work center must be scheduled on about 150 machines, while taking complex constraints into account, in particular hundreds of time constraints, and optimizing a collection of criteria. The optimization engine provides significantly better results, runs significantly faster, and can handle much larger problem instances than the previous Constraint Programming optimization engine used in the factory.
Bitar, A., Knopp, S., Tamssaouet, K. (Planimize), Delcloy, L. & Roussel, R. (STMicroelectronics, Crolles)
European Journal of Operational Research – 2023
The flexible job shop scheduling problem (FJSP) is an NP-hard combinatorial optimization problem, which has wide applications in the real world. The complexity and relevance of the FJSP have led to numerous research works on its modeling and resolution. This paper reviews some of the research of the past 30 years on the problem, by presenting and classifying the different criteria, constraints, configurations and solution approaches that have been considered. Recent emerging topics on complex shop scheduling, multi-criteria optimization and uncertain and dynamic environments are discussed. Finally, future research opportunities are proposed.
S. Dauzère-Pérès, J. Ding, L. Shen, K. Tamssaouet
European Journal of Operational Research – 2023
In this paper, we are concerned with the resolution of a multiobjective complex job-shop scheduling problem stemming from semiconductor manufacturing. To This article introduces a framework that unifies and generalizes well-known literature results related to local search for the job-shop and flexible job-shop scheduling problems. In addition to the choice of the metaheuristic and the neighborhood structure, the success of most of the influential local search approaches relies on the ability to quickly and efficiently rule out infeasible moves and evaluate the quality of the feasible neighbors…
K. Tamssaouet and S. Dauzère-Pérès
European Journal of Operational Research – 2022
Tamssaouet, K., Dauzère-Pérès, S., Knopp, S., Bitar, A., & Yugma, C.
Computers & Operations Research – 2021
In this paper, a scheduling problem on non-identical parallel machines with auxiliary resources and sequence-dependent and machine-dependent setup times is studied. This problem can be found in various manufacturing contexts, and in particular in workshops of wafer manufacturing facilities. Three different criteria are defined and analyzed: The number of products completed before the end of a given time horizon, the weighted sum of completion times and the number of auxiliary resource moves. The first criterion is maximized, while the two others are minimized. The first and the third criteria are not classical in scheduling theory, but are justified in industrial settings…
Bitar, A., Dauzère-Pérès, S., & Yugma, C.
This paper addresses the job-shop scheduling problem in which the machines are not available during the whole planning horizon and with the objective of minimizing the makespan. The disjunctive graph model is used to represent job sequences and to adapt and extend known structural properties of the classical job-shop scheduling problem to the problem at hand. These results have been included in two metaheuristics (Simulated Annealing and Tabu Search) with specific neighborhood functions and diversification structures. Computational experiments on problem instances of the literature show that our Tabu Search approach outperforms Simulated Annealing and…
Tamssaouet, K., Dauzère-Pérès, S., & Yugma, C.
European Journal of Operational Research – 2017
We consider a Flexible Job-Shop scheduling problem with batching machines, reentrant flows, sequence dependent setup times and release dates while considering different regular objective functions. Semiconductor manufacturing is probably one of the most prominent practical applications of such a problem. Existing disjunctive graph approaches for this combined problem rely on dedicated nodes to explicitly represent batches. To facilitate modifications of the graph, our new modeling reduces this complexity by encoding batching decisions into edge weights. An important contribution is an original algorithm that takes batching decisions “on the fly” during…
Knopp, S., Dauzère-Pérès, S., & Yugma, C.
Journal of Scheduling – 2016
Bitar, A., Dauzère-Pérès, S., & Yugma, C.
Winter Simulation Conference - 2020
Le Quéré, É., Dauzère-Pérès, S., Tamssaouet, K., Maufront, C., & Astie, S.
Winter Simulation Conference - 2018
Tamssaouet, K., Dauzère-Pérès, S., Yugma, C., Knopp, S., & Pinaton, J.
Proceedings of the Winter Simulation Conference - 2014.
Knopp, S., Dauzère-Pérès, S., & Yugma, C.
Proceedings of the Winter Simulation Conference - 2014
Bitar, A., Dauzère-Pérès, S., & Yugma, C.
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