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Conference Time: 19th May 2022, 02:51:32pm CEST
 

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
Session
Regular Session : AI-based approaches for quality and performance improvement of production systems
Time:
Wednesday, 08/Sept/2021:
12:00pm - 2:00pm

Session Chair: Thomas Yeung
Session Chair: Rosanna Fornasiero
 Virtual location: Wednesday Room 1

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Presentations
ID: 233 / RS-07: 1
Regular Paper Submission
Data-driven Production Management: Machine Learning and Artificial Intelligence
Smart Manufacturing & Industry 4.0: Advanced, Digital and Smart Manufacturing
Keywords: Neural network, Quality control, Machine Learning, Manufacturing

A Neural Network Model for Quality Prediction in the Automotive Industry

Anders Risan, Mohamed Kais Msakni, Peter Schütz

The Norwegian University of Science and Technology, Norway


ID: 403 / RS-07: 2
Regular Paper Submission
Digital Supply Networks: Artificial Intelligence and Blockchain Technologies in Logistics and DSN
Data-driven Production Management: Machine Learning and Artificial Intelligence
Smart Manufacturing & Industry 4.0: Advanced, Digital and Smart Manufacturing
Keywords: Operations management, Artificial Intelligence, Big Data, process industry.

AI and BD in Process Industry: a literature review with an operational perspective

Rosanna Fornasiero1, David Nettleton2, Lorenz Kiebler3, Alicia Martinez de Yuso4, Chiara Eleonora De Marco5

1CNR, Italy; 2IRIS; 3IML Fraunhofer; 4ZLC; 5ciaotech


ID: 412 / RS-07: 3
Regular Paper Submission
Digital Supply Networks: Artificial Intelligence and Blockchain Technologies in Logistics and DSN, Intelligent Logistics Networks Management
Smart Manufacturing & Industry 4.0: Advanced, Digital and Smart Manufacturing, Cyber-Physical Production Systems and Digital Twins
Keywords: JSSP, Online Scheduling, MAPPO, MARL, Reinforcement Learning

Implementing an Online Scheduling Approach for Production with Multi Agent Proximal Policy Optimization (MAPPO)

Oliver Lohse, Noah Pütz, Korbinian Hörmann

Siemens AG, Germany


ID: 427 / RS-07: 4
Regular Paper Submission
Data-driven Production Management: Novel Production Planning & Control Approaches
Smart Manufacturing & Industry 4.0: Advanced, Digital and Smart Manufacturing, Connected, Smart Factories of the Future
Keywords: Operation Twins, Production-Intralogistics Synchronization, Production and Operations Management, Real-Time Visibility and Traceability, Industry 4.0, Smart Manufacturing

Operation Twins: Synchronized Production-Intralogistics for Industry 4.0 Manufacturing

Mingxing LI1, Daqiang Guo1,2, George Q. Huang1

1epartment of Industrial and Manufacturing Systems Engineering, HKU-ZIRI Lab for Physical Internet, The University of Hong Kong, Hong Kong S.A.R. (China); 2Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen



 
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