Modeling and simulation in intelligent manufacturing

Abstract With the continuous deepening of the application of information technology in the manufacturing field, the informatization of manufacturing systems has developed from unit digital manufacturing to integrated networked manufacturing, and then to comprehensive digital, networked and intelligent manufacturing. As a comprehensive information technology integrating computer, model theory, and scientific computing, the modeling and simulation technology plays an irreplaceable role in the development process of manufacturing informatization and is widely applied in all stages of product life cycle containing design, production, testing, maintenance, procurement and sales. This paper reviews and summarizes the research and application of modeling and simulation technology in manufacturing, and analyzes typical simulation techniques in manufacturing from aspects of manufacturing unit simulation, manufacturing integrated simulation and manufacturing intelligent simulation.

[1]  S. Muruganand,et al.  Design and Development of a Virtual Instrument for Hazardous Environment Monitoring and Control Using Lab VIEW , 2016, Intell. Autom. Soft Comput..

[2]  Vittaldas V. Prabhu,et al.  Simulation modeling for optimal control of additive manufacturing processes , 2016 .

[3]  Hark Hwang,et al.  Simplification methods for accelerating simulation-based real-time scheduling in a semiconductor wafer fabrication facility , 2003 .

[4]  Xiaowu Chen,et al.  A virtual environment for collaborative assembly , 2005, Second International Conference on Embedded Software and Systems (ICESS'05).

[5]  Violeta Holmes,et al.  Grid-connected PV virtual instrument system (GCPV-VIS) for detecting photovoltaic failure , 2016, 2016 4th International Symposium on Environmental Friendly Energies and Applications (EFEA).

[6]  Lars Mönch,et al.  Simulation-based assessment of machine criticality measures for a shifting bottleneck scheduling approach in complex manufacturing systems , 2007, Comput. Ind..

[7]  Tao Zhang,et al.  Real-time job shop scheduling based on simulation and Markov decision processes , 2017, 2017 Winter Simulation Conference (WSC).

[8]  Lida Xu,et al.  Diverse task scheduling for individualized requirements in cloud manufacturing , 2018, Enterp. Inf. Syst..

[9]  Luiz Fernando Bittencourt,et al.  CEPSim: Modelling and simulation of Complex Event Processing systems in cloud environments , 2016, Future Gener. Comput. Syst..

[10]  M. J. Pratt,et al.  Virtual prototypes and product models in mechanical engineering , 1995 .

[11]  Jun Park.  Augmented Reality Based Re-formable Mock-Up for Design Evaluation , 2008, 2008 International Symposium on Ubiquitous Virtual Reality.

[12]  Mohamed Al-Hussein,et al.  Integrated production planning and control system for a panelized home prefabrication facility using simulation and RFID , 2018 .

[13]  Loo Hay Lee,et al.  Simulation Optimization: A Review and Exploration in the New Era of Cloud Computing and Big Data , 2015, Asia Pac. J. Oper. Res..

[14]  Hyung-Jong Kim,et al.  Cost Estimation of Hybrid System Models in Simulation Based Acquisition , 2015, 2015 4th International Conference on Advanced Information Technology and Sensor Application (AITS).

[15]  Y. Rama Devi,et al.  A Study on Cloud Simulation Tools , 2015 .

[16]  Lin Zhang,et al.  Multi-task scheduling of distributed 3D printing services in cloud manufacturing , 2018 .

[17]  Marie Johansson,et al.  Finite element simulation of global structural behaviour of multifamily timber buildings using prefabricated volume modules , 2018 .

[18]  S. Zhang,et al.  Integrated process planning and scheduling: an enhanced ant colony optimization heuristic with parameter tuning , 2018, J. Intell. Manuf..

[19]  Víctor Anaya,et al.  Integrating Agent Based Simulation in the Design of Multi-Sided Platform Business Model: A Methodological Approach , 2018, 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC).

[20]  Darren J. Hartl,et al.  Computationally Efficient Analysis of SMA Sensory Particles Embedded in Complex Aerostructures Using a Substructure Approach , 2015 .

[21]  S. Mirdamadi,et al.  Discrete Event Simulation-Based Real-Time Shop Floor Control , 2007 .

[22]  Lei Ren,et al.  Real-Time Scheduling of Cloud Manufacturing Services Based on Dynamic Data-Driven Simulation , 2019, IEEE Transactions on Industrial Informatics.

[23]  Zhang Li,et al.  Model Engineering for Complex System Simulation , 2013 .

[24]  Simon J. E. Taylor,et al.  Simplifying the development of HLA-based distributed simulations with the HLA Development Kit software framework (DKF) , 2017, 2017 IEEE/ACM 21st International Symposium on Distributed Simulation and Real Time Applications (DS-RT).

[25]  Andreas Tolk,et al.  The next generation of modeling & simulation: integrating big data and deep learning , 2015, SummerSim.

[26]  Ali H. Diabat,et al.  A simulation-based Genetic Algorithm approach for the quay crane scheduling under uncertainty , 2016, Simul. Model. Pract. Theory.

[27]  Andrey Kutin,et al.  Simulation Modeling of Assembly Processes in Digital Manufacturing , 2018 .

[28]  Peigen Li,et al.  Toward New-Generation Intelligent Manufacturing , 2018 .

[29]  Andrew P. Sage,et al.  Simulation‐Based Acquisition , 2005 .

[30]  Eric J. Tuegel,et al.  The Airframe Digital Twin: Some Challenges to Realization , 2012 .

[31]  Heng Li,et al.  A production rescheduling expert simulation system , 2000, Eur. J. Oper. Res..

[32]  Suphunnika Ibbotson,et al.  Direct digital manufacturing: definition, evolution, and sustainability implications , 2015 .

[33]  Sreekanth Ramakrishnan,et al.  A framework for selecting and evaluating process improvement projects using simulation and optimization techniques , 2017, 2017 Winter Simulation Conference (WSC).

[34]  George Chryssolouris,et al.  A virtual reality-based experimentation environment for the verification of human-related factors in assembly processes , 2000 .

[35]  Lei Ren,et al.  Modelling and simulation of logistics service selection in cloud manufacturing , 2018 .

[36]  He Zhang,et al.  Digital Twin in Industry: State-of-the-Art , 2019, IEEE Transactions on Industrial Informatics.

[37]  Jeffrey S. Smith,et al.  Simulation for manufacturing system design and operation: Literature review and analysis , 2014 .

[38]  Mozafar Saadat,et al.  Agent Cooperation Mechanism for Decentralized Manufacturing Scheduling , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[39]  Lionel C. Briand,et al.  Environment modeling and simulation for automated testing of soft real-time embedded software , 2013, Software & Systems Modeling.

[40]  S. Michael Spottswood,et al.  Reengineering Aircraft Structural Life Prediction Using a Digital Twin , 2011 .

[41]  Andrew Y. C. Nee,et al.  GARDE: a gesture-based augmented reality design evaluation system , 2011 .

[42]  Yves Ducq,et al.  Model-based approaches for interoperability of next generation enterprise information systems: state of the art and future challenges , 2016, Information Systems and e-Business Management.

[43]  Dimitris Mourtzis,et al.  Simulation in Manufacturing: Review and Challenges , 2014 .

[44]  Xu Chen,et al.  Implementing on-line simulation upon the World-Wide Web , 1998, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274).

[45]  Huiyang Qu,et al.  Development and Credibility of Multi-disciplinary Virtual Prototype , 2016 .

[46]  S. N. Samy,et al.  A Framework for Modelling Reconfigurable Manufacturing Systems Using Hybridized Discrete-Event and Agent-based Simulation , 2015 .

[47]  Bernhard Dieber,et al.  Online simulation for flexible robotic manufacturing , 2018, 2018 7th International Conference on Industrial Technology and Management (ICITM).

[48]  Alberto Falcone,et al.  On the integration of HLA and FMI for supporting interoperability and reusability in distributed simulation , 2015, SpringSim.

[49]  Soemon Takakuwa,et al.  Simulation-based dynamic shop floor scheduling for a flexible manufacturing system in the industry 4.0 environment , 2017, 2017 Winter Simulation Conference (WSC).

[50]  Lin Zhang,et al.  A Dynamic Task Scheduling Method Based on Simulation in Cloud Manufacturing , 2016 .

[51]  Mayank Shekhar,et al.  Comparison of Various Cloud Simulation tools available in Cloud Computing , 2015 .

[52]  V. Vinod,et al.  Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system , 2011 .

[53]  Daniele Gianni,et al.  A model-driven method for building distributed simulation systems from business process models , 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

[54]  Hongjun Zhang,et al.  Design of OBDH Software Test Platform Based on QEMU , 2018, ICSINC 2018 Fall.

[55]  Lei Ren,et al.  An event-triggered dynamic scheduling method for randomly arriving tasks in cloud manufacturing , 2017, Int. J. Comput. Integr. Manuf..

[56]  Nicolas Perry,et al.  Including in HLA federation functional mockup units for supporting interoperability and reusability in distributed simulation , 2018, SummerSim.

[57]  Toly Chen,et al.  Estimating simulation workload in cloud manufacturing using a classifying artificial neural network ensemble approach , 2016 .

[58]  Raymond L. Smith,et al.  ENABLING INTELLIGENT PROCESSES IN SIMULATION UTILIZING THE TENSORFLOW DEEP LEARNING RESOURCES , 2018, 2018 Winter Simulation Conference (WSC).

[59]  Edward H. Glaessgen,et al.  Coupling Damage-Sensing Particles to the Digitial Twin Concept , 2014 .

[60]  Ronald Azuma,et al.  A Survey of Augmented Reality , 1997, Presence: Teleoperators & Virtual Environments.

[61]  Anna Syberfeldt,et al.  Integrating simulation-based optimization, lean, and the concepts of industry 4.0 , 2017, 2017 Winter Simulation Conference (WSC).

[62]  Andrew Howard,et al.  Design and use paradigms for Gazebo, an open-source multi-robot simulator , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[63]  Tao Zhang,et al.  REAL-TIME BATCHING IN JOB SHOPS BASED ON SIMULATION AND REINFORCEMENT LEARNING , 2018, 2018 Winter Simulation Conference (WSC).

[64]  S. H. Choi,et al.  A virtual prototyping system for rapid product development , 2004, Comput. Aided Des..

[65]  Hyung-Jong Kim,et al.  Size measurement of DEVS models for SBA effectiveness evaluation , 2013, WSC '13.

[66]  Dimitris Mourtzis,et al.  Digital manufacturing: History, perspectives, and outlook , 2009 .

[67]  Sotiris Makris,et al.  The role of simulation in digital manufacturing: applications and outlook , 2015, Int. J. Comput. Integr. Manuf..

[68]  George-Christopher Vosniakos,et al.  Design of a virtual reality training system for human–robot collaboration in manufacturing tasks , 2017 .

[69]  Yingguang Chu,et al.  Virtual prototyping for maritime crane design and operations , 2018 .

[70]  George Chryssolouris,et al.  A simulation-based hybrid backwards scheduling framework for manufacturing systems , 2006, Int. J. Comput. Integr. Manuf..

[71]  Gordon Wetzstein,et al.  Novel Optical Configurations for Virtual Reality: Evaluating User Preference and Performance with Focus-tunable and Monovision Near-eye Displays , 2016, CHI.

[72]  Aniruddha S. Gokhale,et al.  A simulation as a service cloud middleware , 2016, Ann. des Télécommunications.

[73]  Amos H. C. Ng,et al.  A simulation-based scheduling system for real-time optimization and decision making support , 2011 .

[74]  Barbara W. Mazziotti,et al.  Creating a flexible, simulation-based finite scheduling tool , 1997, WSC '97.

[75]  Lin Xiang,et al.  Two Kinds of Lathe Improvement Techniques Based on ANSYS Simulation Analysis , 2018, IOP Conference Series: Materials Science and Engineering.

[76]  Enzo Morosini Frazzon,et al.  Towards adaptive simulation-based optimization to select individual dispatching rules for production control , 2017, 2017 Winter Simulation Conference (WSC).

[77]  Venkata Dinavahi,et al.  Large-Scale Nonlinear Device-Level Power Electronic Circuit Simulation on Massively Parallel Graphics Processing Architectures , 2018, IEEE Transactions on Power Electronics.

[78]  Remzi Seker,et al.  Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook , 2016, Comput. Ind..

[79]  Harald Bucher,et al.  A Distributed Simulation Platform Using HLA for Complex Embedded Systems Design , 2015, 2015 IEEE/ACM 19th International Symposium on Distributed Simulation and Real Time Applications (DS-RT).

[80]  Nicolas Perry,et al.  Using High Level Architecture in the SEE Project for Industrial Context , 2017, SOHOMA.

[81]  Lei Ren,et al.  Cloud manufacturing: a new manufacturing paradigm , 2014, Enterp. Inf. Syst..

[82]  Appa Iyer Sivakumar,et al.  Simulation based multiobjective schedule optimization in semiconductor manufacturing , 2002, Proceedings of the Winter Simulation Conference.

[83]  Fei Qiao,et al.  A Novel Rescheduling Method for Dynamic Semiconductor Manufacturing Systems , 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[84]  Umut Durak,et al.  MOKA: an object-oriented framework for FMI co-simulation , 2015, SummerSim.

[85]  Michael C. Fu,et al.  Simulation-based work load and job release control for semiconductor manufacturing , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[86]  Zahir Irani,et al.  Enhancing simulation software for use in manufacturing , 2000 .

[87]  Jie Zhang,et al.  The modelling and operations for the digital twin in the context of manufacturing , 2018, Enterp. Inf. Syst..

[88]  Wang Xiao-hua.  Networked Modeling & Simulation Platform Based on Concept of Cloud Computing—Cloud Simulation Platform , 2009 .