Extraction and forecasting time series of production processes

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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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Romanov, A., Filippov, A., & Yarushkina, N. (2019). Extraction and forecasting time series of production processes. In Studies in Systems, Decision and Control (Vol. 199, pp. 173–184). Springer International Publishing. https://doi.org/10.1007/978-3-030-12072-6_16

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