TY  - JOUR
U1  - Zeitschriftenartikel, wissenschaftlich - begutachtet (reviewed)
A1  - Pesch, Erwin
A1  - Choi, Tsan-Ming
A1  - Dolgui, Alexandre
A1  - Ivanov, Dmitry
T1  - OR and analytics for digital, resilient, and sustainable manufacturing 4.0
JF  - Annals of Operations Research
N2  - This special issue publishes contributions from the operations research (OR) community in the following areas and at the intersections of those areas, namely manufacturing and supply chain digitalization, resilience, and sustainability. The application areas of OR and analytics to digital, resilient, and sustainable manufacturing systems may contain descriptive and diagnostic analyses, predictive simulation and prescriptive optimization, real time control, and adaptive learning. Examples of OR and analytics applications include logistics and supply chain control with real-time data, inventory control and management using sensing data, dynamic resource allocation in Industry 4.0 customized assembly systems, improving forecasting models using big data, machine learning techniques for process control, network visibility and risk control, optimizing systems based on predictive information (e.g., predictive maintenance), combining optimization and machine learning algorithms, and supply chain risk analytics.
Y1  - 2022
SN  - 1572-9338
SS  - 1572-9338
U6  - https://doi.org/10.1007/s10479-022-04536-3
DO  - https://doi.org/10.1007/s10479-022-04536-3
VL  - 310
SP  - 1
EP  - 6
ER  -