Analysis of Advanced Algorithms Master Production Schedule for Custom Manufacture of Furniture

D. E. Nyrkov; Aleksandr Starikov

doi:doi:10.12737/article_59c2124049cd45.48567850

UDC 63

Analysis of Advanced Algorithms Master Production Schedule for Custom Manufacture of Furniture

Published в Forestry Engineering Journal · Volume 7, Issue 3, 2017 · Pages 299–306 · Rubrics: Business Administration. Model engineering. Information science

DOI 10.12737/article_59c2124049cd45.48567850

Received: 20.09.2017 Accepted: 01.11.2017 Published: 01.11.2017 Language of publication: RUS

Authors

D. E. Nyrkov ¹ · Aleksandr Starikov ²

1 Voronezh State University of Forestry and Technologies named after G.F. Morozov (Department of Automation of Production Process, postgraduate)
Voronezh, Voronezh, Russian Federation

2 Voronezh State University of Forestry and Technologies named after G.F. Morozov (Department of Automation of Production Processes, Head of Department)
Voronezh, Voronezh, Russian Federation

ABSTRACT

The article discusses the algorithms employed in automated systems for master production scheduling in the applicability of their produce-to-order furniture. Small batch and custom production of furniture occupies a significant market share, as we do, and in the countries of Western Europe. Also, it is a prospective direction of development for other industries, focused on the end user. Most of the existing national planning systems designed for large-scale and mass production, in which the main role takes enterprise performance. Therefore, the main indicator, which is used by the optimization of scheduling, is the moment of completion of the last job. However, custom production is much more complex factors affecting the success of the enterprise as a whole: a key indicator in this case is the completion of all work no later than the specified time, not their early completion (within the terms established by treaties with customers). Also in the custom and small-scale production, it takes an important role time index spent on readjustment of the equipment associated with the transition to a different type of output. If these and other indicators do not have a significant role in large-scale production, the small-scale productions of these indicators have a significant impact on the performance of the enterprise, and they can no longer be neglected. In this paper, the three most promising mathematical algorithms (algorithm simulated annealing, genetic algorithm and artificial neural network), which allow us to optimize schedules based on several criteria applied to the problem of master production scheduling, customized production of furniture.

KEYWORDS

furniture industry custom production production planning simulated annealing genetic algorithm neural network.

Information Text References

Authors:

1. Voronezh State University of Forestry and Technologies named after G.F. Morozov (Department of Automation of Production Process, postgraduate)

Voronezh, Voronezh, Russian Federation

2. Voronezh State University of Forestry and Technologies named after G.F. Morozov (Department of Automation of Production Processes, Head of Department)

Voronezh, Voronezh, Russian Federation

Type:

Article

Pages:

from 299 to 306

Status:

Published

Subject area:

UDC 63

Language:

Russian, English

Keywords:

furniture industry, custom production, production planning, simulated annealing, genetic algorithm, neural network.

Text

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Автоматизированные системы управления предприятием (АСУП) существуют около 50 лет и уже прочно вошли во все сферы экономики, а современные промышленные предприятия практически невозможно представить без подобных систем. В настоящее время существует несколько англоязычных терминов (MES, MRP, MRP II, APS, ERP) в разной степени соответствующие понятию АСУП, которые представляют целые классы систем, отличающихся как принципами работы, так и степенью покрытия задач управления предприятиями.

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