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Extraction and Forecasting Time Series of Production Processes

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Recent Research in Control Engineering and Decision Making (ICIT 2019)

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Abstract

The manufacturing processes of the aircraft factory are analyzed to improve the quality of management decisions. Production processes models based on time series models are proposed. The applying of fuzzy smoothing of time series is considered. A new technique for extracting fuzzy trends for forecasting time series proposed. The use of type-2 fuzzy sets for making new models of time series with the aim of improving the quality of the forecast considered. An information system is being built to calculate the production capacity using these models. The system implements the algorithms for the calculation of a production capacity based on a methodology approved in the industry. The information extracted from the production processes is supposed to be used as a component of the models. An experiment with checking the quality of smoothing of time series is described. The experiment shows the possibility and advantages of modeling time series using type-2 fuzzy sets.

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Acknowledgements

The authors acknowledge that the work was supported by the framework of the state task of the Ministry of Education and Science of the Russian Federation No. 2.1182.2017/4.6 “Development of methods and means for automating the production and technological preparation of aggregate-assembly aircraft production in the conditions of a multi-product production program”. The reported study was funded by RFBR and the government of Ulyanovsk region according to the research projects No. 18-47-730022 and No. 18-47-732016.

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Authors and Affiliations

  1. Ulyanovsk State Technical University, Ulyanovsk, Russia

    Anton Romanov, Aleksey Filippov & Nadezhda Yarushkina

Authors
  1. Anton Romanov
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  2. Aleksey Filippov
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  3. Nadezhda Yarushkina
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Corresponding author

Correspondence to Anton Romanov .

Editor information

Editors and Affiliations

  1. Institute of Applied Information Technologies and Communication, Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Olga Dolinina

  2. Institute of Applied Information Technologies and Communication, Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Alexander Brovko

  3. Institute of Applied Information Technologies and Communication, Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Vitaly Pechenkin

  4. Institute of Applied Information Technologies and Communication, Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Alexey Lvov

  5. Department of Automation, Novosibirsk State Technical University, Novosibirsk, Russia

    Vadim Zhmud

  6. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

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Romanov, A., Filippov, A., Yarushkina, N. (2019). Extraction and Forecasting Time Series of Production Processes. In: Dolinina, O., Brovko, A., Pechenkin, V., Lvov, A., Zhmud, V., Kreinovich, V. (eds) Recent Research in Control Engineering and Decision Making. ICIT 2019. Studies in Systems, Decision and Control, vol 199. Springer, Cham. https://doi.org/10.1007/978-3-030-12072-6_16

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