Time Series Based Forecasting Methods in Production Systems: A Systematic Literature Review
Published 2022-06-30
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Keywords
- Industrial forecasting,
- Machine learning,
- Neural network,
- Production system,
- Systematic literature review
How to Cite
Copyright (c) 2023 International Journal of Industrial Engineering and Management
This work is licensed under a Creative Commons Attribution 4.0 International License.
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)
