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A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

Ziqi Huang, Yang Shen, Jiayi Li, Marcel Fey, Christian Brecher
2021 Sensors  
in the fields of smart manufacturing and advanced robotics.  ...  As a digital replica of a physical entity, the basis of DT is the infrastructure and data, the core is the algorithm and model, and the application is the software and service.  ...  ., Fraunhofer IPT, as well as the Chair of Production Metrology and Quality Management, and Production Engineering of the Laboratory for Machine Tools and Production Engineering (WZL) for their permission  ... 
doi:10.3390/s21196340 pmid:34640660 fatcat:qy3qiazvqrejvfuixudd6ywqsq

A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

Ziqi Huang, Yang Shen, Jiayi Li, Marcel Fey, Christian Brecher
2021 Sensors 21(19)  
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY  ...  ., Fraunhofer IPT, as well as the Chair of Production Metrology and Quality Management, and Production Engineering of the Laboratory for Machine Tools and Production Engineering (WZL) for their permission  ...  Acknowledgments: The authors would like to thank the German Research Foundation DFG for the support within the Cluster of Excellence "Internet of Production"-390621612.  ... 
doi:10.18154/rwth-2021-09877 fatcat:yjhprcascvfutisat7olust3kq

Modeling and simulation for customer driven manufacturing system design and operations planning

Juhani Heilala, Jari Montonen, Arttu Salmela, Pas Jarvenpaa
2007 2007 Winter Simulation Conference  
Discrete event simulation, DES, has mainly been used as a production system analysis tool, to evaluate new production system concepts, layout and control logic.  ...  The simulation analysis gives a forecast of the future with given input values, thus production managers have time to react to potential problems and evaluate alternatives.  ...  ACKNOWLEDGMENTS The authors wish to acknowledge the financial support received from the Finnish Funding Agency for Technology and Innovation (TEKES), VTT, and Finnish industry.  ... 
doi:10.1109/wsc.2007.4419812 dblp:conf/wsc/HeilalaMSJ07 fatcat:xt6w6loyuzelfos6po6doksk2y

Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey

Weiming Shen, Lihui Wang, Qi Hao
2006 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
Therefore, there is a need for the integration of manufacturing process-planning and scheduling systems for generating more realistic and effective plans.  ...  Manufacturing scheduling is the process of selecting a process plan and assigning manufacturing resources for specific time periods to the set of manufacturing processes in the plan.  ...  The Manufacturing Scheduling and Control Testbed (MASCOT) [81] was a simulated testbed for manufacturing scheduling and control.  ... 
doi:10.1109/tsmcc.2006.874022 fatcat:dgqbnflcqbcftdeuhbpzyf2uoq

Event-Driven Online Machine State Decision for Energy-Efficient Manufacturing System Based on Digital Twin Using Max-Plus Algebra

Junfeng Wang, Yaqin Huang, Qing Chang, Shiqi Li
2019 Sustainability  
The data view, model view, and service view of a digital twin manufacturing system are formulated to describe the physical systems in virtual space, to perform simulation analysis, to make decisions, and  ...  For online energy-saving decisions about machines in serial manufacturing systems, an event-driven estimation method of an energy-saving window based on Max-plus Algebra is presented to put the target  ...  By creating the latest snapshot of the physical manufacturing system status based on the data-driven simulation method [16] , the forecasting application is adaptive and flexible to any change in terms  ... 
doi:10.3390/su11185036 fatcat:j4mmepx6izhvniaip3jchzwx44

Modelling for Digital Twins—Potential Role of Surrogate Models

Ágnes Bárkányi, Tibor Chován, Sándor Németh, János Abonyi
2021 Processes  
A number of examples of digital twin applications from both continuous processes and discrete manufacturing are presented to underline the potentials of utilising surrogate models.  ...  In this sense, the paper discusses what types of surrogate models are suitable for different practical problems as well as introduces the appropriate techniques for building and using these models.  ...  Potential Applications in Control, Safety and Risk Management Combining data-driven and physics-based models can help to describe the difference between physics-based mapping and experimental data.  ... 
doi:10.3390/pr9030476 fatcat:izcbxby7ajc3plvh7tzu63zoz4

Solving the Job-Shop Scheduling Problem in the Industry 4.0 Era

Matheus Leusin, Enzo Frazzon, Mauricio Uriona Maldonado, Mirko Kück, Michael Freitag
2018 Technologies  
This is possible through the development of an intelligent system based on the use of agents and the Internet of Things (IoT) to achieve real-time data exchange and decision making in the job-shop.  ...  The performance of the proposed framework is tested in a simulation study based on a real industrial case.  ...  Conflicts of Interest: The authors declare no conflict of interest. Technologies 2018, 6, 107  ... 
doi:10.3390/technologies6040107 fatcat:vo256ctzfberznq4g3dmlc7hra

Advances in Adaptive Scheduling in Industry 4.0

Dimitris Mourtzis
2022 Frontiers in Manufacturing Technology  
Concretely, the first part discusses the development of a Cloud-based production planning and control system for discrete manufacturing environments.  ...  shopping, through gathering customers' requirements, adaptive production, and logistics of vending machines replenishment and Internet of Things and Wireless Sensor Networks for Smart Manufacturing.  ...  Scheduling is critical for the design, control, and operation of manufacturing systems, as evidenced by the preceding.  ... 
doi:10.3389/fmtec.2022.937889 fatcat:o3kdutbvh5ddnarftxfpxq7b4y

A Review of Data-Driven Decision-Making Methods for Industry 4.0 Maintenance Applications

Alexandros Bousdekis, Katerina Lepenioti, Dimitris Apostolou, Gregoris Mentzas
2021 Electronics  
The current paper reviews the literature on data-driven decision-making in maintenance and outlines directions for future research towards data-driven decision-making for Industry 4.0 maintenance applications  ...  with simulation software, autonomous robots, and other additive manufacturing initiatives.  ...  operation and the manufacturing process; (ii) knowledge-based, relying on expert knowledge and being addressed by knowledge management systems; and (iii) data-driven, relying on data analytics and machine  ... 
doi:10.3390/electronics10070828 doaj:8accfa8ec357433dbb02cde449e3af6a fatcat:7q55ex2mezfstdllzfufryeo3a

Enabling technologies and frameworks for collaborative intelligent manufacturing

Weiming Shen, Daizhong Su
2008 International Journal of Production Research  
Mendikoa et al. proposed interesting inventive approaches for problems detection by determining potential failures in collaborative intelligent design and manufacturing systems.  ...  The proposed approaches were based on a methodology for failure causes analysis and failure prediction by means of AFD (Anticipatory Failure Determination) based on the TRIZ methodology.  ...  Schreck et al. presented an approach based on integrated use of several formalizations for efficient supervision and control of production facilities, including mathematical modeling, data-driven methods  ... 
doi:10.1080/00207540701737815 fatcat:xgnfdax2gnd5hoyjwl5uvzn7ga

Production rescheduling through product quality prediction

Maik Frye, Dávid Gyulai, Júlia Bergmann, Robert H. Schmitt
2021 10th CIRP Sponsored Conference on Digital Enterprise Technologies  
Scheduling can be well-supported by real-time data acquisition systems, resulting in decisions that rely on actual or predicted status of production environment and jobs in progress.  ...  Series of numerical experiments are presented to demonstrate potentials in prediction-based rescheduling, with early-stage scrap detection.  ...  This research was also supported by the Cooperative Doctoral Program of the Ministry for Innovation and Technology from the source of the National Research, Development and Innovation fund.  ... 
doi:10.18154/rwth-2021-11081 fatcat:gzis4242erdphhrupvnfb4xutq

Coupling predictive scheduling and reactive control in manufacturing hybrid control architectures: state of the art and future challenges

Olivier Cardin, Damien Trentesaux, André Thomas, Pierre Castagna, Thierry Berger, Hind Bril El-Haouzi
2015 Journal of Intelligent Manufacturing  
Nowadays, industrials are seeking for models and methods that are not only able to provide efficient overall production performance, but also for reactive systems facing a growing set of unpredicted events  ...  One important research activity in that field focuses on holonic/multi-agent control systems that couple predictive/proactive and reactive mechanisms into agents/holons.  ...  The HCA must also interoperate with existing data bases and manufacturing systems as well as interoperate with human supervisors. b.  ... 
doi:10.1007/s10845-015-1139-0 fatcat:sawrik5sg5akzghtjefwatkmnm

Production rescheduling through product quality prediction

Maik Frye, Dávid Gyulai, Júlia Bergmann, Robert H. Schmitt
2021 Procedia Manufacturing  
Scheduling can be well-supported by real-time data acquisition systems, resulting in decisions that rely on actual or predicted status of production environment and jobs in progress.  ...  Scheduling can be well-supported by real-time data acquisition systems, resulting in decisions that rely on actual or predicted status of production environment and jobs in progress.  ...  This research was also supported by the Cooperative Doctoral Program of the Ministry for Innovation and Technology from the source of the National Research, Development and Innovation fund.  ... 
doi:10.1016/j.promfg.2021.07.022 fatcat:suktaeeti5cexcheqogf6bil3u

Improvement of Delivery Reliability by an Intelligent Control Loop between Supply Network and Manufacturing

Dennis Bauer, Thomas Bauernhansl, Alexander Sauer
2021 Applied Sciences  
In addition to the requirements, the concept describes the structure of the system as a control loop, a reinforcement learning-based controlling element as the central decision-making component, and the  ...  integration into the existing production IT landscape of a company as well as with latest internet of things (IoT) devices and cyber-physical systems.  ...  Presently, common PPC methods mostly use simulation and analytic approaches based on the planning objects to find optimal schedules.  ... 
doi:10.3390/app11052205 doaj:5b29f6e9426b4c2c8699aec507af1d74 fatcat:hqeharxfardtrhjhmcc7ukkm2i

Production Scheduling in Complex Job Shops from an Industrie 4.0 Perspective: A Review and Challenges in the Semiconductor Industry

Bernd Waschneck, Thomas Bauernhansl, Thomas Altenmüller, Andreas Kyek
2017 Zenodo  
Based on the literature review, the authors' experience in the semiconductor industry and feedback and discussions with industry experts, this paper identies challenges in production control.  ...  While this review and certain challenges are motivated by semiconductor fabrication plants, the paper serves as a general overview of the state-of-the-art in job shop scheduling.  ...  The authors gratefully acknowledge the financial support from the EU project "SemI40 -Power Semiconductor and Electronics Manufacturing 4.0" and from the Infineon Technologies AG for funding and supporting  ... 
doi:10.5281/zenodo.495155 fatcat:5yte6zygabc65clmevycufluma
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