УДК 658.51
doi:10.21202/1993-047X.14.2020.2.235-248
SYNCHRONOUS PLANNING METHODS FOR IMPROVING MAKE-TO-ORDER PRODUCTION PROCESSES: TOWARDS DIGITAL TRANSFORMATION
Elena E. Noskova1, Denis V. Kapulin2, Polina A. Russkikh3
1, 2, 3 Siberian Federal University, Krasnoyarsk, Russia
1 enoskova@sfu-kras.ru, orcid.org/0000-0002-2785-815X
2 dkapulin@sfu-kras.ru, orcid.org/0000-0002-4260-1408
3 prusskikh@sfu-kras.ru, orcid.org/0000-0003-2858-2893
Abstract. The ability to collect and accumulate large amounts of data has become a strategic asset for enterprises. Modern manufacturing must be guided by the development of integrated analysis and modeling, which make better use of the huge amounts of data produced by manufacturing systems. To be efficient, industrial enterprises must move beyond tracking and data collection and instead focus on the efficient use of manufacturing resources. The lack of effective planning methods is one of the reasons for the uneven use of production capacities, the occurrence of unplanned downtime and various kinds of losses. Small-scale production to order is characterized by a weak specialization of jobs, the versatility of the equipment used with a wide range of components used. The article analyzes the existing information systems for scheduling workshops, their application for small-scale custom production. A study was made of the effectiveness of the application of the developed algorithms for different levels of planning – inter-shop and shop, depending on the size of the portfolio of orders and the number of technological operations.
Keywords: creativity, British fine art, social network Instagram, artist, artwork, audience
Acknowledgments: the work was financially supported by the Russian Foundation for Basic Research, Project № 20-07-00226 “Study of options for building the architecture of an information system for synchronous planning of order-based assembly production.”
For citation: Noskova E. E., Kapulin D. V., Russkih P. A. Synchronous planning methods for improving make-to-order production processes: towards digital transformation // Digitalization. 2022, 3 (2), pp. 41—48. [in Russian]. https://doi.org/10.37993/2712-8733- 2022-3-2-41-48. EDN: ETFWSU
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