Version 1
: Received: 19 April 2024 / Approved: 26 April 2024 / Online: 28 April 2024 (07:13:37 CEST)
How to cite:
García-Mata, C.L.; Burtseva, L.; Werner, F. Optimal Scheduling for Automated Wetetch Stations with One Robot in Semiconductor Manufacturing via Constraint Answer Set Programming. Preprints2024, 2024041736. https://doi.org/10.20944/preprints202404.1736.v1
García-Mata, C.L.; Burtseva, L.; Werner, F. Optimal Scheduling for Automated Wetetch Stations with One Robot in Semiconductor Manufacturing via Constraint Answer Set Programming. Preprints 2024, 2024041736. https://doi.org/10.20944/preprints202404.1736.v1
García-Mata, C.L.; Burtseva, L.; Werner, F. Optimal Scheduling for Automated Wetetch Stations with One Robot in Semiconductor Manufacturing via Constraint Answer Set Programming. Preprints2024, 2024041736. https://doi.org/10.20944/preprints202404.1736.v1
APA Style
García-Mata, C.L., Burtseva, L., & Werner, F. (2024). Optimal Scheduling for Automated Wetetch Stations with One Robot in Semiconductor Manufacturing via Constraint Answer Set Programming. Preprints. https://doi.org/10.20944/preprints202404.1736.v1
Chicago/Turabian Style
García-Mata, C.L., Larysa Burtseva and Frank Werner. 2024 "Optimal Scheduling for Automated Wetetch Stations with One Robot in Semiconductor Manufacturing via Constraint Answer Set Programming" Preprints. https://doi.org/10.20944/preprints202404.1736.v1
Abstract
Scheduling and optimization have a central place in the research area of computing because it is increasingly important to achieve fully automated production processes to adjust manufacturing systems to the requirements of Industry 4.0. In this paper, we demonstrate how an automated wet-etch scheduling problem for a semiconductor industry can be solved by constraint answer set programming (CASP) and, its solver called clingcon. The considered scheduling problem includes a robot for lot transfers between the baths. CASP is a hybrid approach in automated reasoning that combines different research areas such as answer set programming, Constraint Processing and Satisfiability Modulo Theories. For a long time, exact methods such as constraint programming have displayed difficulties in solving real large-scale problem instances. Currently, the performance of state-of-the-art constrains solvers is comparatively better than a decade ago, and some complex combinatorial problems can be optimally solved. These theoretical and technical achievements open new horizons for declarative programming applications such as logistics. A successful solution to this problem is achieved and we found that in most cases tested, CASP is faster and obtains in most cases similar makespan values than solutions based on mixed integer linear programming and constraint paradigms.
Keywords
scheduling; optimization; knowledge representation and reasoning; constraint answer set programming; semiconductor manufacturing system
Subject
Computer Science and Mathematics, Discrete Mathematics and Combinatorics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
