Time Series Based Forecasting Methods in Production Systems: A Systematic Literature Review
Published 2022-06-30
Keywords
- Industrial forecasting,
- Machine learning,
- Neural network,
- Production system,
- Systematic literature review
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Abstract
Forecasting in production systems is used to anticipate their quality, efficiency, and yield. However, to the best of our knowledge, there exists no systematic review for industrial fore- casting approaches. Thus, this work aimed to address this gap through a systematic literature review. The quantitative results revealed that industrial forecasting models are mainly ap- plied in three economic sectors, with recurrent neural network models being the dominant approach. Moreover, this work proposes a classification of forecasting applications based on common characteristics found in reviewed sources. Several additional insights were pro- duced, and future research directions were elaborated. Hence, this systematic review fosters an understanding of the current state-of-the-art of industrial forecasting approaches and facili- tates future research initiatives.
Article history: Received (October 25, 2021); Revised (April 04, 2022); Accepted (May 5, 2022); Published online (May 12, 2022)