Digital twin-enabled smart industrial systems: a bibliometric review

References

• Alam, K. M., and A. El Saddik. 2017. “C2PS: A Digital Twin Architecture Reference Model for the Cloud-based Cyber-physical Systems.” IEEE Access 5: 2050–2062. doi:https://doi.org/10.1109/ACCESS.2017.2657006.
   Web of Science ®Google Scholar
• Bao, J., D. Guo, L. Jie, and J. Zhang. 2018. The Modelling and Operations for the Digital Twin in the Context of Manufacturing’. Enterprise Information Systems 00 (00), 1–23. Taylor & Francis. doi:https://doi.org/10.1080/17517575.2018.1526324.
   Google Scholar
• Batagelj, V., and A. Mrvar. 1998. “Pajek-program for Large Network Analysis.” Connections 21 (2): 47–57.
   Google Scholar
• Boschert, S., and R. Rosen. 2016. “Digital Twin—the Simulation Aspect.” In Mechatronic Futures, 59–74. Cham: Springer.
   Google Scholar
• Ciano, M. P., R. Pozzi, T. Rossi, and F. Strozzi. 2019. “How IJPR Has Addressed “Lean”: A Literature Review Using Bibliometric Tools.” International Journal of Production Research. doi:https://doi.org/10.1080/00207543.2019.1566667.
   PubMed Web of Science ®Google Scholar
• Colicchia, C., and F. Strozzi. 2012. “Supply Chain Risk Management: A New Methodology for A Systematic Literature Review.” Supply Chain Management 17 (4): 403–418. doi:https://doi.org/10.1108/13598541211246558.
   Web of Science ®Google Scholar
• Davis, J., T. Edgar, J. Porter, J. Bernaden, and M. Sarli. 2012. “Smart Manufacturing, Manufacturing Intelligence and Demand-dynamic Performance.” Computers & Chemical Engineering 47: 145–156. doi:https://doi.org/10.1016/j.compchemeng.2012.06.037.
   Web of Science ®Google Scholar
• Ding, K., F. T. Chan, X. Zhang, G. Zhou, and F. Zhang. 2019. “Defining a Digital Twin-based Cyber-Physical Production System for Autonomous Manufacturing in Smart Shop Floors.” International Journal of Production Research
   PubMed Web of Science ®Google Scholar
• Dröder, K., P. Bobka, T. Germann, F. Gabriel, and F. Dietrich. 2018. “A Machine Learning-Enhanced Digital Twin Approach for Human-Robot-Collaboration.” Procedia CIRP 76: 187–192. doi:https://doi.org/10.1016/j.procir.2018.02.010.
   Google Scholar
• Durão, L. F. C., S. Haag, R. Anderl, K. Schützer, and E. Zancul. 2018. “Digital Twin Requirements in the Context of Industry 4.0.” In IFIP International Conference on Product Lifecycle Management, 204–214. Cham: Springer, July.
   Google Scholar
• Gabor, T., L. Belzner, M. Kiermeier, M. T. Beck, and A. Neitz. 2016. “A Simulation-based Architecture for Smart Cyber-physical Systems.” In 2016 IEEE International Conference on Autonomic Computing (ICAC), 374–379. IEEE, July.
   Google Scholar
• Glaessgen, E., and D. Stargel. 2012. “The Digital Twin Paradigm for Future NASA and US Air Force Vehicles.” In 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA, 1818.
   Google Scholar
• Haag, S., and R. Anderl. 2018. “Digital twin–Proof of Concept.” Manufacturing Letters 15: 64–66. doi:https://doi.org/10.1016/j.mfglet.2018.02.006.
   Google Scholar
• Hermann, M., T. Pentek, and B. Otto. 2016. “Design Principles for Industrie 4.0 Scenarios.” In 2016 49th Hawaii International Conference on System Sciences (HICSS), 3928–3937. IEEE, January.
   Google Scholar
• Holler, M., F. Uebernickel, and W. Brenner. 2016. “Digital Twin Concepts in Manufacturing Industries - A Literature Review and Avenues for Further Research”, no. 2002, 1–9.
   Google Scholar
• Hummon, N. P., and P. Dereian. 1989. “Connectivity in a Citation Network: The Development of DNA Theory.” Social Networks. doi:https://doi.org/10.1016/0378-8733(89)90017-8.
   Google Scholar
• Jeon, B., and S. H. Suh. 2018. “Design Considerations and Architecture for Cooperative Smart Factory: MAPE/BD Approach.” Procedia Manufacturing 26: 1094–1106. doi:https://doi.org/10.1016/j.promfg.2018.07.146.
   Google Scholar
• Jo, S. K., D. H. Park, H. Park, and S. H. Kim. 2018. “Smart Livestock Farms Using Digital Twin: Feasibility Study.” In 2018 International Conference on Information and Communication Technology Convergence (ICTC), 1461–1463. IEEE, October.
   Google Scholar
• Joordens, M., and M. Jamshidi. 2018. “On the Development of Robot Fish Swarms in Virtual Reality with Digital Twins.” In 2018 13th Annual Conference on System of Systems Engineering (Sose), 411–416. IEEE, June.
   Google Scholar
• Kleinberg, J. 2003. “Bursty and Hierarchical Structure in Streams.” Data Mining and Knowledge Discovery 7 (4): 373–397. doi:https://doi.org/10.1023/A:1024940629314.
   Web of Science ®Google Scholar
• Kousi, N., C. Gkournelos, S. Aivaliotis, C. Giannoulis, G. Michalos, and S. Makris. 2019. “Digital Twin for Adaptation of Robots’ Behavior in Flexible Robotic Assembly Lines.” Procedia Manufacturing 28: 121–126.
   Google Scholar
• Kraft, E. M. 2016. “The Air Force Digital Thread/digital Twin-life Cycle Integration and Use of Computational and Experimental Knowledge.” In 54th AIAA Aerospace Sciences Meeting, San Diego, CA, 0897.
   Google Scholar
• Kuehn, W. 2018. “Digital Twins for Decision Making in Complex Production and Logistic Enterprises.” International Journal of Design & Nature and Ecodynamics 13 (3): 260–271. doi:https://doi.org/10.2495/DNE-V13-N3-260-271.
   Google Scholar
• Kuts, V., T. Otto, T. Tähemaa, K. Bukhari, and T. Pataraia. 2018. “November. Adaptive Industrial Robots Using Machine Vision.” In ASME 2018 International Mechanical Engineering Congress and Exposition, V002T02A093–V002T02A093. American Society of Mechanical Engineers.
   Google Scholar
• Lee, J., Ardakani, H.D., Yang, S. and Bagheri, B., 2015. Industrial Big Data Analytics and Cyber-physical Systems for Future Maintenance & Service Innovation. Procedia Cirp, 38: 3–7. doi:https://doi.org/10.1016/j.procir.2015.08.026.
   Google Scholar
• Lee, P. C., H. N. Su. 2010. “Investigating the Structure of Regional Innovation System Research through Keyword Co-Occurrence and Social Network Analysis.” Innovation: Management, Policy and Practice. doi:https://doi.org/10.5172/impp.12.1.26.
   Google Scholar
• Leng, J., H. Zhang, D. Yan, Q. Liu, X. Chen, and D. Zhang. 2019. “Digital Twin-driven Manufacturing Cyber-physical System for Parallel Controlling of Smart Workshop.” Journal of Ambient Intelligence and Humanized Computing 10 (3): 1155–1166. doi:https://doi.org/10.1007/s12652-018-0881-5.
   Web of Science ®Google Scholar
• Li, J. Q., F. R. Yu, G. Deng, C. Luo, Z. Ming, and Q. Yan. 2017. “Industrial Internet: A Survey on the Enabling Technologies, Applications, and Challenges.” IEEE Communications Surveys & Tutorials 19 (3): 1504–1526. doi:https://doi.org/10.1109/COMST.2017.2691349.
   Web of Science ®Google Scholar
• Liu, J., H. Zhou, G. Tian, X. Liu, and X. Jing. 2018. “Digital Twin-Based Process Reuse and Evaluation Approach for Smart Process Planning.” International Journal of Advanced Manufacturing Technology 1619–1634. doi:https://doi.org/10.1007/s00170-018-2748-5.
   Google Scholar
• Liu, J. S., and L. Y. Y. Lu. 2012. “An Integrated Approach for Main Path Analysis: Development of the Hirsch Index as an Example.” Journal of the American Society for Information Science and Technology. doi:https://doi.org/10.1002/asi.21692.
   Google Scholar
• Liu, Z., N. Meyendorf, and N. Mrad. 2018. “The Role of Data Fusion in Predictive Maintenance Using Digital Twin.” In AIP Conference Proceedings, Vol. 1949, No. 1, 020023. AIP Publishing, April.
   Google Scholar
• Lu, Y., Q. Min, Z. Liu, and Y. Wang. 2019. “An IoT-enabled Simulation Approach for Process Planning and Analysis: A Case from Engine Re-manufacturing Industry.” International Journal of Computer Integrated Manufacturing 32 (4-5): 413-429.
   Google Scholar
• Lucio-Arias, D., and L. Leydesdorff. 2008. “Main-Path Analysis and Path-Dependent Transitions in HistCiteTM-Based Historiograms.” Journal of the American Society for Information Science and Technology. doi:https://doi.org/10.1002/asi.20903.
   Google Scholar
• Mavris, D. N., M. G. Balchanos, O. J. Pinon-Fischer, and W. J. Sung. 2018. “Towards a Digital Thread-enabled Framework for the Analysis and Design of Intelligent Systems.” In 2018 AIAA Information Systems-AIAA Infotech@ Aerospace, Kissimmee, Florida,1367.
   Google Scholar
• Miller, A. M., R. Alvarez, and N. Hartman. 2018. “Towards an Extended Model-based Definition for the Digital Twin.” Computer-Aided Design and Applications 15 (6): 880–891. doi:https://doi.org/10.1080/16864360.2018.1462569.
   Google Scholar
• Misra, P., Y. Simmhan, and J. Warrior. 2015. “Towards a Practical Architecture for the Next Generation Internet of Things.” arXiv Preprint arXiv:1502.00797.
   Google Scholar
• Mongeon, P., and P.-H. Adèle. 2016. “The Journal Coverage of Web of Science and Scopus: A Comparative Analysis.” Scientometrics 106 (1): 213–228. doi:https://doi.org/10.1007/s11192-015-1765-5.
   Web of Science ®Google Scholar
• Moreno, A., G. Velez, A. Ardanza, I. Barandiaran, Á. R. de Infante, and R. Chopitea. 2017. “Virtualisation Process of a Sheet Metal Punching Machine within the Industry 4.0 Vision.” International Journal on Interactive Design and Manufacturing (Ijidem) 11 (2): 365–373. doi:https://doi.org/10.1007/s12008-016-0319-2.
   Google Scholar
• Morgan, J., and G. E. O’Donnell. 2017. “Enabling a Ubiquitous and Cloud Manufacturing Foundation with Field-level Service-oriented Architecture.” International Journal of Computer Integrated Manufacturing 30 (4–5): 442–458.
   Web of Science ®Google Scholar
• Mukherjee, T., and T. DebRoy. 2019. “A Digital Twin for Rapid Qualification of 3D Printed Metallic Components.” Applied Materials Today 14: 59–65. doi:https://doi.org/10.1016/j.apmt.2018.11.003.
   Web of Science ®Google Scholar
• Negri, E., L. Fumagalli, and M. Macchi. 2017. “A Review of the Roles of Digital Twin in Cps-based Production Systems.” Procedia Manufacturing 11: 939–948. doi:https://doi.org/10.1016/j.promfg.2017.07.198.
   Google Scholar
• Nikolakis, N., K. Alexopoulos, E. Xanthakis, and G. Chryssolouris. 2019. “The Digital Twin Implementation for Linking the Virtual Representation of Human-based Production Tasks to Their Physical Counterpart in the Factory-floor.” International Journal of Computer Integrated Manufacturing 32 (1): 1–12. doi:https://doi.org/10.1080/0951192X.2018.1529430.
   Web of Science ®Google Scholar
• Oyekan, J. O., W. Hutabarat, A. Tiwari, R. Grech, M. H. Aung, M. P. Mariani, C. Dupuis, T. Ricaud, S. Singh, and C. Dupuis. 2019. “The Effectiveness of Virtual Environments in Developing Collaborative Strategies between Industrial Robots and Humans.” Robotics and Computer-Integrated Manufacturing 55: 41–54. doi:https://doi.org/10.1016/j.rcim.2018.07.006.
   Web of Science ®Google Scholar
• Park, K. J., R. Zheng, and X. Liu 2012. “Cyber-physical Systems: Milestones and Research Challenges.”
   Google Scholar
• Park, K. T., S. J. Im, Y. S. Kang, S. D. Noh, Y. T. Kang, and S. G. Yang. 2019. “Service-oriented Platform for Smart Operation of Dyeing and Finishing Industry.” International Journal of Computer Integrated Manufacturing 32 (3): 307–326. doi:https://doi.org/10.1080/0951192X.2019.1572225.
   Web of Science ®Google Scholar
• Petković, T., D. Puljiz, I. Marković, and B. Hein. 2019. “Human Intention Estimation Based on Hidden Markov Model Motion Validation for Safe Flexible Robotized Warehouses.” Robotics and Computer-Integrated Manufacturing 57: 182–196. doi:https://doi.org/10.1016/j.rcim.2018.11.004.
   Web of Science ®Google Scholar
• Pollack, J., and D. Adler. 2015. “Emergent Trends and Passing Fads in Project Management Research: A Scientometric Analysis of Changes in the Field.” International Journal of Project Management. doi:https://doi.org/10.1016/j.ijproman.2014.04.011.
   Google Scholar
• Pozzi, R., and F. Strozzi. 2018. “How Assembly Systems are Adopting the Technologies of I40: A Preliminary Landscape.” XXII Summer School “Francesco Turco” – Industrial Systems Engineering 2018: 369–375.
   Google Scholar
• Preuveneers, D., W. Joosen, and E. Ilie-Zudor. 2018. “Robust Digital Twin Compositions for Industry 4.0 Smart Manufacturing Systems.” In 2018 IEEE 22nd International Enterprise Distributed Object Computing Workshop (EDOCW), 69–78. IEEE, October.
   Google Scholar
• Qi, Q., and F. Tao. 2018. “Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison.” Ieee Access 6: 3585–3593. doi:https://doi.org/10.1109/ACCESS.2018.2793265.
   Web of Science ®Google Scholar
• Rios, J., J. C. Hernandez, M. Oliva, and F. Mas. 2015. “Product Avatar as Digital Counterpart of a Physical Individual Product: Literature Review and Implications in an Aircraft BT - 22nd ISPE Inc.” In International Conference on Concurrent Engineering, CE 2015, 657–666, July 20, 2015 - July 23, 2015ʹ 2 (July). doi:https://doi.org/10.3233/978-1-61499-544-9-657.
   Google Scholar
• Rodič, B. 2017. “Industry 4.0 And the New Simulation Modelling Paradigm.” Organizacija 50 (3): 193–207. doi:https://doi.org/10.1515/orga-2017-0017.
   Web of Science ®Google Scholar
• Rosen, R., G. Von Wichert, G. Lo, and K. D. Bettenhausen. 2015. “About the Importance of Autonomy and Digital Twins for the Future of Manufacturing.” IFAC-PapersOnLine 48 (3): 567–572. doi:https://doi.org/10.1016/j.ifacol.2015.06.141.
   Google Scholar
• Sajid, A., H. Abbas, and K. Saleem. 2016. “Cloud-assisted IoT-based SCADA Systems Security: A Review of the State of the Art and Future Challenges.” IEEE Access 4: 1375–1384. doi:https://doi.org/10.1109/ACCESS.2016.2549047.
   Web of Science ®Google Scholar
• Sarma, A. C., and J. Girão. 2009. “Identities in the Future Internet of Things.” Wireless Personal Communications 49 (3): 353–363. doi:https://doi.org/10.1007/s11277-009-9697-0.
   Web of Science ®Google Scholar
• Schleich, B., N. Anwer, L. Mathieu, and S. Wartzack. 2017. “Shaping the Digital Twin for Design and Production Engineering.” CIRP Annals 66 (1): 141–144.
   Web of Science ®Google Scholar
• Schroeder, G., C. Steinmetz, C. E. Pereira, I. Muller, N. Garcia, D. Espindola, and R. Rodrigues. 2017. “Visualising the Digital Twin Using Web Services and Augmented Reality.” In IEEE International Conference on Industrial Informatics (INDIN), 522–527. IEEE. doi:https://doi.org/10.1109/INDIN.2016.7819217.
   Google Scholar
• Schroeder, G. N., C. Steinmetz, C. E. Pereira, and D. B. Espindola. 2016. “Digital Twin Data Modeling with AutomationML and a Communication Methodology for Data Exchange.” IFAC-PapersOnLine 49 (30): 12–17. Elsevier B.V. doi:https://doi.org/10.1016/j.ifacol.2016.11.115.
   Google Scholar
• Schroeder, G. N., C. Steinmetz, C. E. Pereira, and D. B. Espindola. 2016b. “Digital Twin Data Modeling with Automationml and a Communication Methodology for Data Exchange.” IFAC-PapersOnLine 49 (30): 12–17. doi:https://doi.org/10.1016/j.ifacol.2016.11.115.
   Google Scholar
• Schuh, G., P. Jussen, and T. Harland. 2018. “The Digital Shadow of Services: A Reference Model for Comprehensive Data Collection in MRO Services of Machine Manufacturers.” Procedia CIRP 73: 271–277. doi:https://doi.org/10.1016/j.procir.2018.03.318.
   Google Scholar
• Sci2 Team. 2009. “Science of Science (Sci2) Tool.„ Indiana University and SciTech Strategies. https://sci2.cns.iu.edu
   Google Scholar
• Shafto, M., M. Conroy, R. Doyle, E. Glaessgen, C. Kemp, J. LeMoigne, and L. Wang. 2010. “Draft Modeling, Simulation, Information Technology & Processing Roadmap.” Technology Area 11.
   Google Scholar
• Strozzi, F., C. Colicchia, A. Creazza, and N. Carlo. 2017. “Literature Review on the “Smart Factory” Concept Using Bibliometric Tools.” International Journal of Production Research 55 (22): 1–20. Taylor & Francis. doi:https://doi.org/10.1080/00207543.2017.1326643.
   Web of Science ®Google Scholar
• Strozzi, F., F. Bono, and E. Gutierrez. 2014. “Bibliometric and Citation Network Analysis: Percolation and Graph Spectral Analysis in the Framework of Wireless Sensor Network Technology.” In EUR Scientific and Technical Research Series, JRC92443. Luxemburg.
   Google Scholar
• Tao, F., J. Cheng, Q. Qi, M. Zhang, H. Zhang, and F. Sui. 2018. “Digital Twin-driven Product Design, Manufacturing and Service with Big Data.” The International Journal of Advanced Manufacturing Technology 94 (9–12): 3563–3576. doi:https://doi.org/10.1007/s00170-017-0233-1.
   Web of Science ®Google Scholar
• Tao, F., and M. Zhang. 2017. “Digital Twin Shop-floor: A New Shop-floor Paradigm Towards Smart Manufacturing.” Ieee Access 5: 20418–20427. doi:https://doi.org/10.1109/ACCESS.2017.2756069.
   Web of Science ®Google Scholar
• Taylor, S. J. 2019. “Distributed Simulation: State-of-the-art and Potential for Operational Research.” European Journal of Operational Research 273 (1): 1–19. doi:https://doi.org/10.1016/j.ejor.2018.04.032.
   Web of Science ®Google Scholar
• Tuegel, E. 2012. “The Airframe Digital Twin: Some Challenges to Realization.” In 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA, 1812.
   Google Scholar
• Tuegel, E. J., A. R. Ingraffea, T. G. Eason, and S. M. Spottswood. 2011. “Reengineering Aircraft Structural Life Prediction Using a Digital Twin.” International Journal of Aerospace Engineering 2011. doi:https://doi.org/10.1155/2011/154798.
   Google Scholar
• Uhlemann, T. H. J., C. Lehmann, and R. Steinhilper. 2017. “The Digital Twin: Realizing the Cyber-physical Production System for Industry 4.0.” Procedia Cirp 61: 335–340. doi:https://doi.org/10.1016/j.procir.2016.11.152.
   Google Scholar
• Vachálek, J., L. Bartalský, O. Rovný, D. Šišmišová, M. Morháč, and M. Lokšík. 2017. “The Digital Twin of an Industrial Production Line within the Industry 4.0 Concept.” In 2017 21st International Conference on Process Control (PC), 258–262. IEEE, June.
   Google Scholar
• Waltman, L., N. J. van Eck, and E. C. Noyons. 2010. “A Unified Approach to Mapping and Clustering of Bibliometric Networks.” Journal of Informetrics 4 (4): 629–635. doi:https://doi.org/10.1016/j.joi.2010.07.002.
   Web of Science ®Google Scholar
• Wan, J., H. Cai, and K. Zhou. 2015. “Industrie 4.0: Enabling Technologies.” In Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things, 135–140. IEEE, January.
   Google Scholar
• Wan, J., M. Reddy, and D. Longman. 2011. “Understanding Student Engagement in 3D Virtual Learning Environments.” International Journal of Technology Enhanced Learning 3 (5): 468–481. doi:https://doi.org/10.1504/IJTEL.2011.042099.
   Google Scholar
• Wang, L., M. Törngren, and M. Onori. 2015. “Current Status and Advancement of Cyber-physical Systems in Manufacturing.” Journal of Manufacturing Systems 37: 517–527. doi:https://doi.org/10.1016/j.jmsy.2015.04.008.
   Web of Science ®Google Scholar
• Wärmefjord, K., R. Söderberg, L. Lindkvist, B. Lindau, and J. S. Carlson. 2017. “November. Inspection Data to Support a Digital Twin for Geometry Assurance.” In ASME 2017 International Mechanical Engineering Congress and Exposition, V002T02A101–V002T02A101. American Society of Mechanical Engineers.
   Google Scholar
• Wuest, T., K. Hribernik, and K. D. Thoben. 2014. “Capturing, managing and sharing product information along the lifecycle for design improvement.„ In Proceedings of the 10th International Workshop on Integrated Design Engineering.
   Google Scholar
• Yun, S., J. H. Park, H. S. Kim, and W. T. Kim. 2018. “Importance-aware SDN Control Mechanism for Real-time Data Distribution Services.” In 2018 International Conference on Information and Communication Technology Convergence (ICTC), 1113–1118. IEEE, October.
   Google Scholar
• Yun, S., J. H. Park, and W. T. Kim. 2017. “Data-centric Middleware Based Digital Twin Platform for Dependable Cyber-physical Systems.” In 2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN), 922–926. IEEE, July.
   Google Scholar
• Zambal, S., C. Eitzinger, M. Clarke, J. Klintworth, and P. Y. Mechin. 2018. “A Digital Twin for Composite Parts Manufacturing: Effects of Defects Analysis Based on Manufacturing Data.” In 2018 IEEE 16th International Conference on Industrial Informatics (INDIN), 803–808. IEEE, July.
   Google Scholar
• Zawadzki, P., and K. Żywicki. 2016. “Smart Product Design and Production Control for Effective Mass Customization in the Industry 4.0 Concept.” Management and Production Engineering Review 7 (3): 105–112.
   Web of Science ®Google Scholar
• Zhang, H., Q. Liu, X. Chen, D. Zhang, and J. Leng. 2017. “A Digital Twin-Based Approach for Designing and Multi-Objective Optimization of Hollow Glass Production Line.” IEEE Access 5: 26901–26911. doi:https://doi.org/10.1109/ACCESS.2017.2766453.
   Web of Science ®Google Scholar
• Zhao, D., and A. Strotmann. 2015. “Analysis and Visualization of Citation Networks.” Synthesis Lectures on Information Concepts, Retrieval, and Services 7 (1): 1–207. doi:https://doi.org/10.2200/S00624ED1V01Y201501ICR039.
   Google Scholar
• Zheng, P., T. J. Lin, C. H. Chen, and X. Xu. 2018. “A Systematic Design Approach for Service Innovation of Smart Product-service Systems.” Journal of Cleaner Production 201: 657–667.
   Web of Science ®Google Scholar
• Zhuang, C., J. Liu, and H. Xiong. 2018. “Digital Twin-based Smart Production Management and Control Framework for the Complex Product Assembly Shop-floor.” The International Journal of Advanced Manufacturing Technology 96 (1–4): 1149–1163.
   Web of Science ®Google Scholar