APMS 2021
International Conference Advances in Production Management Systems
September 5-9, 2021 | Nantes, France
Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Session Overview |
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Learning and Robust Decision Support Systems for Agile Manufacturing environments
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ID: 156
/ LRD-02: 1
Special session: Learning and Robust Decision Support Systems for Agile Manufacturing environments Keywords: Smart Factory, Prioritization, Scheduling, Decision Support Due date-related Order Prioritization for Scheduling with Decision Support in Dynamic Environments Department of Factory Planning and Factory Management, Chemnitz University of Technology, Germany ID: 585
/ LRD-02: 2
Special session: Learning and Robust Decision Support Systems for Agile Manufacturing environments Keywords: Digital twin, Industry 4.0, Material resource planning, Machining learning, Uncertainty A digital twin-driven methodology for material resource planning under uncertainties IMT Atlantique, LS2N-CNRS, La Chantrerie, 4 Rue Alfred Kastler, 44307 Nantes, France ID: 185
/ LRD-02: 3
Special session: Learning and Robust Decision Support Systems for Agile Manufacturing environments Keywords: Reinforcement learning, capacity planning, simulation Smart short term capacity planning: A reinforcement learning approach University of Innsbruck, Austria ID: 199
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Special session: Learning and Robust Decision Support Systems for Agile Manufacturing environments Keywords: Reactive Scheduling, Multi-criteria Decision Making, Decision Support System, Inductive Learning, Knowledge-based System. Reactive Scheduling by Intelligent DSS 1Beihang University, P. R. China; 2Avic Chengdu Civil Aircraft Co., Ltd, P. R. China; 3Beijing Shuguang Aviation Electric Co., Ltd., P. R. China ID: 567
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Regular Paper Submission Smart Manufacturing & Industry 4.0: Advanced, Digital and Smart Manufacturing, Connected, Smart Factories of the Future Keywords: Industry 4.0, Machine Learning, Quality Control, Failure Prediction, Smart manufacturing, Automaker Supplier Real-time machine learning automation applied to failure prediction in automakers supplier manufacturing system 1Industrial and Systems Engineering Graduate Program, Pontifical Catholic University of Parana, Curitiba, Brazil; 2Robert Bosch, Ind. Plant - Curitiba, Brazil; 3Department of Electrical Engineering, Federal University of Parana, Polytechnic Center, Curitiba, Brazil | ||
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