A Survey on Automatic Model Generation for Material Flow Simulation in Discrete Manufacturing

Abstract Adaptivity of production systems is acknowledged as a key competition factor in the manufacturing industry. In order to decrease reaction time and increase cost efficiency, changes to a production system are often planned and validated using material flow simulation. However, repeated manual synchronization of the simulation model with the real manufacturing environment is time-consuming and error-prone. Automatic simulation model generation (ASMG) could overcome these issues. In contrast to recent surveys on ASMG, we focus on information retrieval. Accordingly, we constitute the state of the art of this problem domain and outline future research directions.

[1]  Leon F. McGinnis,et al.  Automatic generation of simulation models for semiconductor manufacturing , 2007, 2007 Winter Simulation Conference.

[2]  Csaba Kardos,et al.  Applying model-reconstruction by exploring MES and PLC data for simulation support of production systems , 2012, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC).

[3]  L. Monostori,et al.  Generic data structure and validation methodology for simulation of manufacturing systems , 2016, Int. J. Comput. Integr. Manuf..

[4]  Siegfried Wirth,et al.  Datenbankbasierte Generierung von Simulationsmodellen zur Planung von Produktionssystemen , 2000, SimVis.

[5]  C. McLean,et al.  Data driven design and simulation system based on XML , 2003, Proceedings of the 2003 Winter Simulation Conference, 2003..

[6]  Rodolfo Faglia,et al.  Automating the Simulation of SME Processes through a Discrete Event Parametric Model , 2015 .

[7]  Blaž Rodič,et al.  Industry 4.0 and the New Simulation Modelling Paradigm , 2017 .

[8]  Anders Skoogh,et al.  A data-driven algorithm to predict throughput bottlenecks in a production system based on active periods of the machines , 2018, Comput. Ind. Eng..

[9]  Botond Kádár,et al.  Enhanced control of complex production structures by tight coupling of the digital and the physical worlds , 2010 .

[10]  Perakath C. Benjamin,et al.  Comparison of manual and automated simulation generation approaches and their use for construction applications , 2010, Proceedings of the 2010 Winter Simulation Conference.

[11]  Damian Krenczyk,et al.  Integration of manufacturing operations management tools and discrete event simulation , 2018, IOP Conference Series: Materials Science and Engineering.

[12]  Gergely Popovics,et al.  Automatic Simulation Model Generation Based on PLC Codes and MES Stored Data , 2012 .

[13]  Alexander Fay,et al.  Automated generation of simulation models for control code tests , 2013 .

[14]  Jonathan Fournier.  Model building with Core Manufacturing Simulation Data , 2011, Proceedings of the 2011 Winter Simulation Conference (WSC).

[15]  Enzo Morosini Frazzon,et al.  Data-driven production control for complex and dynamic manufacturing systems , 2018 .

[16]  Maribel Yasmina Santos,et al.  Setting an Industry 4.0 Research and Development Agenda for Simulation – a Literature Review , 2018, International Journal of Simulation Modelling.

[17]  Sanjay Jain,et al.  Standards based generation of a virtual factory model , 2016, 2016 Winter Simulation Conference (WSC).

[18]  Patrick Charpentier,et al.  From Spatio-Temporal Data to Manufacturing System Model , 2014 .

[19]  Csaba Haraszkó,et al.  DES Configurators for Rapid Virtual Prototyping and Optimisation of Manufacturing Systems , 2015 .

[20]  Karsten Mecklenburg.  Seamless integration of layout and simulation , 2001, Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304).

[21]  Richard A. Wysk,et al.  Automatic simulation model generation for simulation-based, real-time shop floor control , 2001, Comput. Ind..

[22]  Herwig Winkler,et al.  Integrating the Digital Twin of the manufacturing system into a decision support system for improving the order management process , 2018 .

[23]  Urbas Leon,et al.  Automatic Model Generation for Virtual Commissioning based on Plant Engineering Data , 2014 .

[24]  Benny Tjahjono,et al.  Practical approach to experimentation in a simulation study , 2008, 2008 Winter Simulation Conference.

[25]  Cathal Heavey,et al.  Test Implementation and Initialisation of a Simulation Model Using CMSD , 2014 .

[26]  Jan Fischer,et al.  Integrating material flow simulation tools in a service-oriented industrial context , 2017, 2017 IEEE 15th International Conference on Industrial Informatics (INDIN).

[27]  Albert T. Jones,et al.  Automatic generation of simulation models from neutral libraries: an example , 2000, 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165).

[28]  Oliver Rose,et al.  A general model description for discrete processes , 2011, Proceedings of the 2011 Winter Simulation Conference (WSC).

[29]  Jürgen Gausemeier,et al.  Approach for the Conceptual Design Validation of Production Systems using Automated Simulation-Model Generation , 2013, CSER.

[30]  Christoph Herrmann,et al.  Process chain simulation to foster energy efficiency in manufacturing , 2009 .

[31]  Björn Johansson,et al.  Manufacturing Systems , 1999 .

[32]  Patrick Charpentier,et al.  Generation of an adaptive simulation driven by product trajectories , 2012, J. Intell. Manuf..

[33]  Gunnar Bolmsjö,et al.  Database driven factory simulation: a proof-of-concept demonstrator , 2001, Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304).

[34]  Luís M. S. Dias,et al.  Layout and process optimisation: using computer-aided design (CAD) and simulation through an integrated systems design tool , 2014, Int. J. Simul. Process. Model..

[35]  Leon F. McGinnis,et al.  Automated production system simulations using commercial off-the-shelf simulation tools , 2016, 2016 Winter Simulation Conference (WSC).

[36]  Sugato Bagchi,et al.  A full-factory simulator as a daily decision-support tool for 300MM wafer fabrication productivity , 2008, 2008 Winter Simulation Conference.

[37]  Sang C. Park,et al.  Plant model generation for PLC simulation , 2010 .

[38]  Björn Johansson,et al.  Input data management in simulation - Industrial practices and future trends , 2012, Simul. Model. Pract. Theory.

[39]  Qing Chang,et al.  Data driven production modeling and simulation of complex automobile general assembly plant , 2011, Comput. Ind..

[40]  Rolf Steinhilper,et al.  The Digital Twin: Realizing the Cyber-Physical Production System for Industry 4.0☆ , 2017 .

[41]  Alexander Verbraeck,et al.  From data to simulation models: Component-based model generation with a data-driven approach , 2011, Proceedings of the 2011 Winter Simulation Conference (WSC).

[42]  Pavel Vik,et al.  Automatic generation of computer models through the integration of production systems design software tools , 2010 .

[43]  A. Calabrese,et al.  Towards fully-facilitated discrete event simulation modelling: Addressing the model coding stage , 2017, Eur. J. Oper. Res..

[44]  Panagiotis Barlas,et al.  Automating simulation: an open source software for automated input data in discrete event simulation projects , 2015 .

[45]  Cathal Heavey,et al.  Automation of input data to discrete event simulation for manufacturing: A review , 2016, Int. J. Model. Simul. Sci. Comput..

[46]  Cathal Heavey,et al.  An open source tool for automated input data in simulation , 2015 .

[47]  YOUNG JUN SON,et al.  Simulation-based shop floor control: formal model, model generation and control interface , 2003 .

[48]  Wilhelm Dangelmaier,et al.  Stochastic Generation of Discrete-Event Simulation Models , 2008, Tenth International Conference on Computer Modeling and Simulation (uksim 2008).

[49]  Terrence D. Perera,et al.  Automated data collection for simulation? , 2002, Simul. Pract. Theory.

[50]  Charles R. McLean,et al.  An architecture for a generic data-driven machine shop simulator , 2002, Proceedings of the Winter Simulation Conference.

[51]  Pierre Castagna,et al.  Proposal of an Approach to Automate the Generation of a Transitic System's Observer and Decision Support using Model Driven Engineering , 2011 .

[52]  Andrew A. West,et al.  A data-driven simulation to support remanufacturing operations , 2019, Comput. Ind..