Conference Agenda

Session
Learning and Robust Decision Support Systems for Agile Manufacturing environments
Time:
Tuesday, 07/Sept/2021:
3:00pm - 5:00pm

Session Chair: Alexandre Dolgui
Session Chair: Simon Thevenin
Virtual location: Tuesday Room 5

Presentations
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

Michael Bojko, Susanne Franke, Luigi Pelliccia, Ralph Riedel

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

Dan Luo, Simon Thevenin, Alexandre Dolgui

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

Manuel Schneckenreither, Sebastian Windmueller, Stefan Haeussler

University of Innsbruck, Austria



ID: 199 / LRD-02: 4
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

Yumin He1, Yaohu Lin1, Hongbo Liu2, Mengpeng Guo3

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 / LRD-02: 5
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

Arthur Beltrame Canciglieri1,2, TainĂ¡ da Rocha1,2, Anderson Luis Szejka1, Osiris Canciglieri Junior1, Leandro dos Santos Coelho1,3

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