Fig. 1
Fig. 2
Fig. 3
Research subareas of forecasting in production engineering
| CLUSTER | GROUP OF METHODS | RESEARCH SUBAREAS | MAIN RESEARCH ISSUES |
|---|---|---|---|
| A | classical methods | the possibility of obtain-ing information that objectively reflects the economic situation of an enterprise | • forecasting of the prime cost of production based on the cal culation of the complex influence of production factors on this indicator (Yureneva et al., 2020; Kuladzhi et al., 2017; Trubaev and Tarasyuk, 2017; Mustavaeva, 2007); • prediction of production volume (Tkachev et al., 2018; Mustavaeva, 2007; Dupré et al., 2020; Artun et al., 2014); • operational cost management (Barinova and Shikhova, 2016, Yureneva and Barinova, 2016; Shim et al., 2009) |
| B | artificial intelli- gence methods | adaptive modelling of production processes | • improve management processes (Alva et al. 2020; Tariq et al., 2019; Sarma et al., 2018; Tariq, 2018; Jain et al., 2018); • predict cycle times of a common operation (Onaran and Yanik, 2020; Gyulai et al., 2020; Okubo et al., 2020; Wang and Jiang, 2019; Susanto et al., 2012; Eraslan, 2009) |
| C | hybrid methods | predictive modelling and probabilistic forecasting | • planning of production volume (Elgharbi et al., 2020; Li et al., 2018; Wu et al., 2017) |