Solving scheduling problems with integrated online sustainability observation using heuristic optimization

• Autorzy: Burduk Anna , Musiał Kamil , Balashov Artem , Batako Andre , Safonyk Andrii

Identyfikatory

DOI

10.24425/bpasts.2022.143830

• Języki publikacji: EN

Abstrakty

EN

The paper deals with the issue of production scheduling for various types of employees in a large manufacturing company where the decision-making process was based on a human factor and the foreman’s know-how, which was error-prone. Modern production processes are getting more and more complex. A company that wants to be competitive on the market must consider many factors. Relying only on human factors is not efficient at all. The presented work has the objective of developing a new employee scheduling system that might be considered a particular case of the job shop problem from the set of the employee scheduling problems. The Neuro-Tabu Search algorithm and the data gathered by manufacturing sensors and process controls are used to remotely inspect machine condition and sustainability as well as for preventive maintenance. They were used to build production schedules. The construction of the Neuro-Tabu Search algorithm combines the Tabu Search algorithm, one of the most effective methods of constructing heuristic algorithms for scheduling problems, and a self-organizing neural network that further improves the prohibition mechanism of the Tabu Search algorithm. Additionally, in the paper, sustainability with the use of Industry 4.0 is considered. That would make it possible to minimize the costs of employees’ work and the cost of the overall production process. Solving the optimization problem offered by Neuro-Tabu Search algorithm and real-time data shows a new way of production management.

Słowa kluczowe

EN

production scheduling; sustainable development; genetic algorithm; meta-heuristics; intelligent optimization methods of production systems; tabu search

PL

harmonogramowanie produkcji; zrównoważony rozwój; algorytm genetyczny; przeszukiwanie tabu; metaheurystyki; inteligentne metody optymalizacji systemów produkcyjnych

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2022
• Tom: Vol. 70, nr 6
• Strony: art. no. e143830
• Opis fizyczny: Bibliogr. 28 poz., rys., tab.

Twórcy

autor

Burduk Anna

• Wroclaw University of Science and Technology, Faculty of Mechanical Engineering, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

• https://orcid.org/0000-0003-2181-4380

autor

Musiał Kamil

• Wroclaw University of Science and Technology, Faculty of Mechanical Engineering, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

autor

Balashov Artem

• Wroclaw University of Science and Technology, Faculty of Mechanical Engineering, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

autor

Batako Andre

• Liverpool John Moores University, Faculty of Engineering and Technology,70 Mount Pleasant Liverpool L3 3AF, UK

autor

Safonyk Andrii

• National University of Water and Environmental Engineering, Department of Automation, Electrical Engineering and Computer-Integrated Technologies, Rivne 33000, Ukraine

• https://orcid.org/0000-0002-5020-9051

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).