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Flexible Job-shop Scheduling for Semiconductor Manufacturing with Hybrid Answer Set Programming (Application Paper)

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Practical Aspects of Declarative Languages (PADL 2023)

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Abstract

The complex production processes in modern semiconductor manufacturing involve hundreds of operations on the route of a production lot, so that the period from lot release to completion can stretch over several months. Moreover, high-tech machines performing each of the operations are heterogeneous, may operate on individual wafers, lots or batches of lots in several stages, and require product-specific setups as well as dedicated maintenance procedures. This industrial setting is in sharp contrast to classical job-shop scheduling scenarios, where the production processes and machines are way less diverse and the primary focus is on solving methods for highly combinatorial yet abstract scheduling problems. In this work, we tackle the scheduling of realistic semiconductor manufacturing processes and model their elaborate requirements in hybrid Answer Set Programming, taking advantage of difference logic to incorporate machine processing, setup as well as maintenance times. While existing approaches schedule semiconductor manufacturing processes only locally, by applying greedy heuristics or isolatedly optimizing the allocation of particular machine groups, we study the prospects and limitations of scheduling at large scale.

This work was partially funded by KWF project 28472, cms electronics GmbH, FunderMax GmbH, Hirsch Armbänder GmbH, incubed IT GmbH, Infineon Technologies Austria AG, Isovolta AG, Kostwein Holding GmbH, and Privatstiftung Kärntner Sparkasse.

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Notes

  1. 1.

    Our encoding as well as test instances are available online at: https://github.com/prosysscience/FJSP-SMT2020.

References

  1. Abels, D., Jordi, J., Ostrowski, M., Schaub, T., Toletti, A., Wanko, P.: Train scheduling with hybrid answer set programming. Theory Pract. Logic Program. 21(3), 317–347 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  2. Abseher, M., Gebser, M., Musliu, N., Schaub, T., Woltran, S.: Shift design with answer set programming. Fundamenta Informaticae 147(1), 1–25 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  3. Balduccini, M.: Industrial-size scheduling with ASP+CP. In: Delgrande, J.P., Faber, W. (eds.) LPNMR 2011. LNCS (LNAI), vol. 6645, pp. 284–296. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-20895-9_33

    Chapter  Google Scholar 

  4. Banbara, M., et al.: teaspoon: solving the curriculum-based course timetabling problems with answer set programming. Ann. Oper. Res. 275(1), 3–37 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  5. Brucker, P., Schlie, R.: Job-shop scheduling with multi-purpose machines. Computing 45(4), 369–375 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  6. Ceylan, Z., Tozan, H., Bulkan, S.: A coordinated scheduling problem for the supply chain in a flexible job shop machine environment. Oper. Res. 21(2), 875–900 (2021). https://doi.org/10.1007/s12351-020-00615-0

    Article  Google Scholar 

  7. Chaudhry, I., Khan, A.: A research survey: review of flexible job shop scheduling techniques. Int. Trans. Oper. Res. 23(3), 551–591 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  8. Da Col, G., Teppan, E.C.: Industrial size job shop scheduling tackled by present day CP solvers. In: Schiex, T., de Givry, S. (eds.) CP 2019. LNCS, vol. 11802, pp. 144–160. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-30048-7_9

    Chapter  MATH  Google Scholar 

  9. Dodaro, C., Galatà, G., Grioni, A., Maratea, M., Mochi, M., Porro, I.: An ASP-based solution to the chemotherapy treatment scheduling problem. Theory Pract. Logic Program. 21(6), 835–851 (2021)

    Article  MathSciNet  Google Scholar 

  10. Eiter, T., Geibinger, T., Musliu, N., Oetsch, J., Skocovský, P., Stepanova, D.: Answer-set programming for lexicographical makespan optimisation in parallel machine scheduling. In: Proceedings of the Eighteenth International Conference on Principles of Knowledge Representation and Reasoning (KR 2021), pp. 280–290. AAAI Press (2021)

    Google Scholar 

  11. El-Kholany, M.M.S., Gebser, M., Schekotihin, K.: Problem decomposition and multi-shot ASP solving for job-shop scheduling. Theory Pract. Logic Program. 22(4), 623–639 (2022)

    Article  MathSciNet  MATH  Google Scholar 

  12. Francescutto, G., Schekotihin, K., El-Kholany, M.M.S.: Solving a multi-resource partial-ordering flexible variant of the job-shop scheduling problem with hybrid ASP. In: Faber, W., Friedrich, G., Gebser, M., Morak, M. (eds.) JELIA 2021. LNCS (LNAI), vol. 12678, pp. 313–328. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75775-5_21

    Chapter  Google Scholar 

  13. Gebser, M., et al.: Potassco user guide (2019). https://potassco.org

  14. Hassanzadeh, A., Rasti-Barzoki, M., Khosroshahi, H.: Two new meta-heuristics for a bi-objective supply chain scheduling problem in flow-shop environment. Appl. Soft Comput. 49, 335–351 (2016)

    Article  Google Scholar 

  15. Holthaus, O.: Efficient dispatching rules for scheduling in a job shop. Int. J. Prod. Econ. 48(1), 87–105 (1997)

    Article  MathSciNet  Google Scholar 

  16. Janhunen, T., Kaminski, R., Ostrowski, M., Schaub, T., Schellhorn, S., Wanko, P.: Clingo goes linear constraints over reals and integers. Theory Pract. Logic Program. 17(5–6), 872–888 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  17. Kopp, D., Hassoun, M., Kalir, A., Mönch, L.: SMT2020–a semiconductor manufacturing testbed. IEEE Trans. Semiconductor Manuf. 33(4), 522–531 (2020)

    Article  Google Scholar 

  18. Lifschitz, V.: Answer Set Programming. Springer, Heidelberg (2019). https://doi.org/10.1007/978-3-030-24658-7

    Book  MATH  Google Scholar 

  19. Ricca, F., et al.: Team-building with answer set programming in the Gioia-Tauro seaport. Theory Pract. Logic Program. 12(3), 361–381 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  20. Sahraeian, R., Rohaninejad, M., Fadavi, M.: A new model for integrated lot sizing and scheduling in flexible job shop problem. J. Ind. Syst. Eng. 10(3), 72–91 (2017)

    Google Scholar 

  21. Taillard, E.: Benchmarks for basic scheduling problems. Eur. J. Oper. Res. 64(2), 278–285 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  22. Tassel, P., Rbaia, M.: A multi-shot ASP encoding for the aircraft routing and maintenance planning problem. In: Faber, W., Friedrich, G., Gebser, M., Morak, M. (eds.) JELIA 2021. LNCS (LNAI), vol. 12678, pp. 442–457. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75775-5_30

    Chapter  Google Scholar 

  23. Waschneck, B., et al.: Optimization of global production scheduling with deep reinforcement learning. Procedia CIRP 72, 1264–1269 (2018)

    Article  Google Scholar 

  24. Xing, L., Chen, Y., Wang, P., Zhao, Q., Xiong, J.: A knowledge-based ant colony optimization for flexible job shop scheduling problems. Appl. Soft Comput. 10(3), 888–896 (2010)

    Article  Google Scholar 

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Authors and Affiliations

  1. University of Klagenfurt, Klagenfurt, Austria

    Ramsha Ali, Mohammed M. S. El-Kholany & Martin Gebser

  2. Cairo University, Cairo, Egypt

    Mohammed M. S. El-Kholany

  3. Graz University of Technology, Graz, Austria

    Martin Gebser

Authors
  1. Ramsha Ali
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  2. Mohammed M. S. El-Kholany
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  3. Martin Gebser
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Corresponding author

Correspondence to Martin Gebser .

Editor information

Editors and Affiliations

  1. University of Kiel, Kiel, Germany

    Michael Hanus

  2. Miami University, Oxford, OH, USA

    Daniela Inclezan

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Ali, R., El-Kholany, M.M.S., Gebser, M. (2023). Flexible Job-shop Scheduling for Semiconductor Manufacturing with Hybrid Answer Set Programming (Application Paper). In: Hanus, M., Inclezan, D. (eds) Practical Aspects of Declarative Languages. PADL 2023. Lecture Notes in Computer Science, vol 13880. Springer, Cham. https://doi.org/10.1007/978-3-031-24841-2_6

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  • DOI: https://doi.org/10.1007/978-3-031-24841-2_6

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