ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 1. Vol. 29. 2023

DOI: 10.17587/it.29.39-46

P. A. Russkikh, Assistant Professor, O. V. Drozd, Ph.D., Associate Professor, D. V. Kapulin, Ph.D., Head of the Department,
Siberian Federal University, Krasnoyarsk, 660041, Russian Federation

The Method of Synchronous Scheduling of Multi-Product Make-to-Order Production

Make-to-order production needs flexibility, quality and synchronicity of planning. Numerous types of products and complex control parameters lead to high requirements for safety, stability and continuity of the production process, as well as strict requirements for instant production management. The need for a high reaction rate to changes in the production system, adaptability and traceability, must be ensured by methods of accurate and reliable control and management of production. The most difficulty is the stage of making a schedule for make-to-order multi-nomenclature productions. Existing systems of scheduling are often not connected in real time with the current production process, all this leads to a high level of unfinished orders. It is necessary to take a new look at the existing planning systems and search for an approach with the possibility of analyzing and optimizing the operational and production plan, taking into account the actual implementation of the provided production process. The research is aimed at developing a synchronous scheduling method suitable for a multi-nomenclature make-to-order production with a variable number of products, and designed to reduce order fulfillment time, reduce inventory and improve work efficiency by adapting to fluctuations in production and product life cycle and implementing an optimal production plan.
Keywords: make-to-order production, scheduling, small-scale production, synchronous planning

P. 39–46

References

1. Russkikh P. A., Kapulin D. V. Analysis of solutions for the creation and implementation of adaptive planning mechanisms for make-to-order production, Vestnik MGTU" STANKIN", 2021, vol. 1, pp. 46—50 (in Russian).
2. Kapulin D. V., Romanov N. V., Kazntsev M. A. Automated information system for operational planning of small-batch custom production with three-dimensional visualization, Devices and systems. Management, control, diagnostics, 2020, vol. 9. pp. 29—39 (in Russian).
3. Russkikh P. A., Kapulin D. V. Multi-agent model of multi-nomenclature small batch production. Vestnik of the South Ural State University. Series: Computer technologies, control, radio electronics, 2021, vol. 21, no. 4. pp. 69—80 (in Russian).
4. Kazantsev Μ. ΐ., Fokin Ε. I., Chemidov I. V. Intaegration of information systems in electronic production, Advances in modern radio electronics, 2018, vol. 12, pp. 9—12 (in Russian).
5. Fang J., Wei X. A knowledge support approach for the preliminary design of platform-based products in Engineering-To-Order manufacturing, Advanced Engineering Informatics, 2020, vol. 46, p. 101196.
6. Willner O., Powell D., Duchi A., Schonsleben P. Globally distributed engineering processes: Making the distinction between engineer-to-order and make-to-order, Procedia CIRP, 2014, vol. 17, pp. 663—668.
7. Briere-Cote A., Rivest L., Desrochers A. Adaptive generic product structure modelling for design reuse in engineer-to-order products, Computers in Industry, 2010, vol. 61, no. 1, pp. 53—65.
8. Tang L., Li F., Chen Z. L. Integrated scheduling of production and two-stage delivery of make-to-order products: Offline and online algorithms, INFORMS Journal on Computing, 2019, vol. 31, no. 3, pp. 493—514.
9. Sokolov B., Ivanov D., Dolgui A. Scheduling in industry 4.0 and cloud manufacturing. New York, Springer, 2020.
10. Zhang J., Deng T., Jiang H., Chen H., Qin S., Ding G. Bi-level dynamic scheduling architecture based on service unit digital twin agents, Journal of Manufacturing Systems, 2021, vol. 60, pp. 59—79.
11. Antonelli D., Stadnicka D. Combining factory simulation with value stream mapping: a critical discussion, Procedia CIRP, 2018, vol. 67, pp. 30—35.
12. Ouelhadj D., Petrovic S. A survey of dynamic scheduling in manufacturing systems, Journal of Scheduling, 2009, vol. 12, no. 4, pp. 417—431.
13. Cheng Y., Sun F., Zhang Y., Tao F. Task allocation in manufacturing: A review, Journal of Industrial Information Integration, 2019, vol. 15, pp. 207—218.
14. Demartini M., Tonelli F., Govindan K. An investigation into modelling approaches for industrial symbiosis: A literature review and research agenda, Cleaner Logistics and Supply Chain, 2022, vol. 3, p. 100020.
15. Khodabandelu A., Park J. W. Agent-based modeling and simulation in construction, Automation in Construction, 2021, vol. 131, p. 103882.
16. Antonelli D., Stadnicka D. Combining factory simulation with value stream mapping: a critical discussion, Procedia CIRP, 2018, vol. 67, pp. 30—35.
17. Roser C., Nakano M., Tanaka M. Tracking shifting bottlenecks, Japan-USA Symposium on Flexible Automation, 2002, pp. 745—750.
18. Huttmeir A., De Treville S., Van Ackere A., Monnier L., Prenninger J. Trading off between heijunka and just-in-sequence, International journal of production economics, 2009, vol. 118, no. 2, pp. 501—507.

To the contents