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OR and analytics for digital, resilient, and sustainable manufacturing 4.0

  • 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.

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Metadaten
Document Type:Article
Language:English
Author:Erwin Pesch, Tsan-Ming Choi, Alexandre Dolgui, Dmitry Ivanov
Center:Center for Advanced Studies in Management (CASiM)
DOI:https://doi.org/10.1007/s10479-022-04536-3
Parent Title (English):Annals of Operations Research
ISSN:1572-9338
Volume:310
Year of Completion:2022
First Page:1
Last Page:6
Content Focus:Academic Audience
Peer Reviewed:Yes
Rankings:AJG Ranking / 3
VHB Ranking / B
SJR Ranking / Q1
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International