Challenges in Digital Twin Development for Cyber-Physical Production Systems

The recent advancement of information and communication technology makes digitalisation of an entire manufacturing shop-floor possible where physical processes are tightly intertwined with their cyber counterparts. This led to an emergence of a concept of digital twin, which is a realistic virtual copy of a physical object. Digital twin will be the key technology in Cyber-Physical Production Systems (CPPS) and its market is expected to grow significantly in the coming years. Nevertheless, digital twin is still relatively a new concept that people have different perspectives on its requirements, capabilities, and limitations. To better understand an effect of digital twin’s operations, mitigate complexity of capturing dynamics of physical phenomena, and improve analysis and predictability, it is important to have a development tool with a strong semantic foundation that can accurately model, simulate, and synthesise the digital twin. This paper reviews current state-of-art on tools and developments of digital twin in manufacturing and discusses potential design challenges.

[1]  Andreas Junghanns,et al.  The Functional Mockup Interface for Tool independent Exchange of Simulation Models , 2011 .

[2]  Aitor Ardanza,et al.  Virtualisation process of a sheet metal punching machine within the Industry 4.0 vision , 2016, International Journal on Interactive Design and Manufacturing (IJIDeM).

[3]  Rainer Fehling,et al.  A Concept of Hierarchical Petri Nets with Building Blocks , 1991, Applications and Theory of Petri Nets.

[4]  Fei Tao,et al.  Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison , 2018, IEEE Access.

[5]  Gianni Ferretti,et al.  Towards digital twins through object-oriented modelling: a machine tool case study , 2018 .

[6]  C. Ramchandani,et al.  Analysis of asynchronous concurrent systems by timed petri nets , 1974 .

[7]  Dawn M. Tilbury,et al.  A software-defined framework for the integrated management of smart manufacturing systems , 2018 .

[8]  Stavros Tripakis,et al.  Data-driven and model-based design , 2018, 2018 IEEE Industrial Cyber-Physical Systems (ICPS).

[9]  Edward H. Glaessgen,et al.  The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles , 2012 .

[10]  Gérard Berry,et al.  The Esterel Synchronous Programming Language: Design, Semantics, Implementation , 1992, Sci. Comput. Program..

[11]  Fei Tao,et al.  Digital twin-driven product design, manufacturing and service with big data , 2017, The International Journal of Advanced Manufacturing Technology.

[12]  Joseph Sifakis,et al.  Rigorous design of cyber-physical systems , 2012, 2012 International Conference on Embedded Computer Systems (SAMOS).

[13]  Lee Johnson,et al.  A Simulation-Based Digital Twin for Model-Driven Health Monitoring and Predictive Maintenance of an Automotive Braking System , 2017, Modelica.

[14]  Frits W. Vaandrager,et al.  Model learning , 2017, Commun. ACM.

[15]  Abdulmotaleb El Saddik,et al.  C2PS: A Digital Twin Architecture Reference Model for the Cloud-Based Cyber-Physical Systems , 2017, IEEE Access.

[16]  Sibin Mohan,et al.  SDCWorks: A Formal Framework for Software Defined Control of Smart Manufacturing Systems , 2018, 2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS).

[17]  Sankaran Mahadevan,et al.  A dynamic Bayesian network approach for digital twin , 2017 .

[18]  James Lyle Peterson,et al.  Petri net theory and the modeling of systems , 1981 .

[19]  Jianhua Liu,et al.  Digital twin-based smart production management and control framework for the complex product assembly shop-floor , 2018, The International Journal of Advanced Manufacturing Technology.

[20]  T. Henzinger.  The theory of hybrid automata , 1996, LICS 1996.

[21]  Edward A. Lee.  Cyber Physical Systems: Design Challenges , 2008, 2008 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC).

[22]  Rajeev Alur,et al.  The Theory of Timed Automata , 1991, REX Workshop.

[23]  Michael W. Grieves,et al.  Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems , 2017 .

[24]  Jim Woodcock,et al.  Integrated tool chain for model-based design of Cyber-Physical Systems: The INTO-CPS project , 2016, 2016 2nd International Workshop on Modelling, Analysis, and Control of Complex CPS (CPS Data).

[25]  Marc Priggemeyer,et al.  Experimentable Digital Twins—Streamlining Simulation-Based Systems Engineering for Industry 4.0 , 2018, IEEE Transactions on Industrial Informatics.

[26]  Peter A. Fritzson,et al.  Principles of object-oriented modeling and simulation with Modelica 2.1 , 2004 .

[27]  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 .

[28]  Lihui Wang,et al.  Human-robot collaborative assembly in cyber-physical production: Classification framework and implementation , 2017 .

[29]  Zoran A. Salcic,et al.  SystemJ: A GALS language for system level design , 2010, Comput. Lang. Syst. Struct..

[30]  Meng Zhang,et al.  Digital Twin Shop-Floor: A New Shop-Floor Paradigm Towards Smart Manufacturing , 2017, IEEE Access.