A Digital Twin-Based Distributed Manufacturing Execution System for Industry 4.0 with AI-Powered On-The-Fly Replanning Capabilities
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[1] Digital Transformation: Core Technologies and Emerging Topics from a Computer Science Perspective , 2023 .
[2] P. Renna. Special Issue: “The Planning and Scheduling of Manufacturing Systems” , 2022, Applied Sciences.
[3] M. Pekarcikova,et al. Comparing Modern Manufacturing Tools and Their Effect on Zero-Defect Manufacturing Strategies , 2022, Applied Sciences.
[4] Mohamed Rafik N. Qureshi. Evaluating Enterprise Resource Planning (ERP) Implementation for Sustainable Supply Chain Management , 2022, Sustainability.
[5] M. Segovia,et al. Design, Modeling and Implementation of Digital Twins , 2022, Sensors.
[6] Petr Novák,et al. Digitalized Automation Engineering of Industry 4.0 Production Systems and Their Tight Cooperation with Digital Twins , 2022, Processes.
[7] H. Najjaran,et al. Intelligent manufacturing execution systems: A systematic review , 2022, Journal of Manufacturing Systems.
[8] Nikolaos Papakonstantinou,et al. Roadmap to semi-automatic generation of digital twins for brownfield process plants , 2021, J. Ind. Inf. Integr..
[9] S. Ogonowski,et al. Security Challenges in Industry 4.0 PLC Systems , 2021, Applied Sciences.
[10] Laith A. Hadidi,et al. Impact of Industry 4.0 and Lean Manufacturing on the Sustainability Performance of Plastic and Petrochemical Organizations in Saudi Arabia , 2021, Sustainability.
[11] F. Allgöwer,et al. Model Predictive Control for Flexible Job Shop Scheduling in Industry 4.0 , 2021, Applied Sciences.
[12] Paolo Renna,et al. A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems , 2021, Applied Sciences.
[13] A. Hellmich,et al. Digital Twins for High-Tech Machining Applications—A Model-Based Analytics-Ready Approach , 2021, Journal of Manufacturing and Materials Processing.
[14] Vicente Rodríguez-Montequín,et al. Development of a Steel Plant Rescheduling Algorithm Based on Batch Decisions , 2021, Applied Sciences.
[15] Yuansong Qiao,et al. Digital Twin: Origin to Future , 2021, Applied System Innovation.
[16] Achim Rettberg,et al. A Methodology for Digital Twin Modeling and Deployment for Industry 4.0 , 2021, Proceedings of the IEEE.
[17] Christian Huemer,et al. Leveraging Iterative Plan Refinement for Reactive Smart Manufacturing Systems , 2021, IEEE Transactions on Automation Science and Engineering.
[18] Raymond Chiong,et al. Energy-efficient production scheduling through machine on/off control during preventive maintenance , 2021, Eng. Appl. Artif. Intell..
[19] Vladimir Modrak,et al. Implementing Industry 4.0 in SMEs , 2021 .
[20] Yinghao Zhao,et al. Robust and Efficient Trajectory Replanning Based on Guiding Path for Quadrotor Fast Autonomous Flight , 2021, Remote. Sens..
[21] Zhong Fan,et al. Digital Twin: Enabling Technologies, Challenges and Open Research , 2019, IEEE Access.
[22] Bernhard Wally,et al. The Digital Twin as a Core Component for Industry 4.0 Smart Production Planning , 2020 .
[23] N. Wild,et al. Investigating the Potential of Smart Manufacturing Technologies , 2020, ISM.
[24] Alexander Fay,et al. The development of a digital twin for machining processes for the application in aerospace industry , 2020 .
[25] Christian Huemer,et al. A Graphical Toolkit for IEC 62264-2 , 2020 .
[26] G. Reinhart. Handbuch Industrie 4.0 , 2020 .
[27] Bernhard Wally,et al. Flexible Production Systems: Automated Generation of Operations Plans Based on ISA-95 and PDDL , 2019, IEEE Robotics and Automation Letters.
[28] Luca Fumagalli,et al. Flexible Automation and Intelligent Manufacturing , FAIM 2017 , 27-30 June 2017 , Modena , Italy A review of the roles of Digital Twin in CPS-based production systems , 2017 .
[29] K. Voigt,et al. Sustainable Industrial Value Creation: Benefits and Challenges of Industry 4.0 , 2017, Digital Disruptive Innovation.
[30] A Min Tjoa,et al. Industrial Applications of Holonic and Multi-Agent Systems: 9th International Conference, HoloMAS 2019, Linz, Austria, August 26–29, 2019, Proceedings , 2019, HoloMAS.
[31] Guido Ignacio Novoa-Flores,et al. A Vehicle Routing Problem with Periodic Replanning , 2018, Proceedings.
[32] Andrew Kusiak,et al. Data-driven smart manufacturing , 2018, Journal of Manufacturing Systems.
[33] Li Da Xu,et al. Industry 4.0: state of the art and future trends , 2018, Int. J. Prod. Res..
[34] Wilfried Sihn,et al. Digital Twin in manufacturing: A categorical literature review and classification , 2018 .
[35] Rolf Steinhilper,et al. The Digital Twin: Realizing the Cyber-Physical Production System for Industry 4.0☆ , 2017 .
[36] Birgit Vogel-Heuser,et al. Handbuch Industrie 4.0 Bd.4, Allgemeine Grundlagen , 2017, Handbuch Industrie 4.0.
[37] Birgit Vogel-Heuser,et al. Evolution of software in automated production systems: Challenges and research directions , 2015, J. Syst. Softw..
[38] Erwin Rauch,et al. Trends towards Distributed Manufacturing Systems and modern forms for their design , 2015 .
[39] Alexandre Sousa,et al. Toward Automated Planning Algorithms Applied to Production and Logistics , 2013 .
[40] Steve Evans,et al. Industrial sustainability: challenges, perspectives, actions , 2013 .
[41] Hakki Ozgur Unver,et al. An ISA-95-based manufacturing intelligence system in support of lean initiatives , 2013 .
[42] Alexander Fay,et al. Automated generation of simulation models for control code tests , 2013 .
[43] Thilo Sauter,et al. Functional Analysis of Manufacturing Execution System Distribution , 2011, IEEE Transactions on Industrial Informatics.
[44] Egon Berghout,et al. Management of lifecycle costs and benefits: Lessons from information systems practice , 2011, Comput. Ind..
[45] Malte Helmert,et al. The Fast Downward Planning System , 2006, J. Artif. Intell. Res..
[46] Vladimír Marík,et al. Industrial adoption of agent-based technologies , 2005, IEEE Intelligent Systems.
[47] Nils J. Nilsson,et al. A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..