Research Papers

User-Guided Visual Analysis of Cyber-Physical Production Systems

[+] Author and Article Information
Tobias Post

Computer Graphics and HCI Group,
University of Kaiserslautern,
Kaiserslautern 67653, Germany
e-mail: tpost@rhrk.uni-kl.de

Rebecca Ilsen, Jan C. Aurich

Institute for Manufacturing Technology
and Production Systems,
University of Kaiserslautern,
Kaiserslautern 67653, Germany

Bernd Hamann

Department of Computer Science,
University of California (UC Davis),
Davis, CA 95616

Hans Hagen

Computer Graphics and HCI Group,
University of Kaiserslautern,
Kaiserslautern 67653, Germany

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received September 29, 2015; final manuscript received September 18, 2016; published online February 16, 2017. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 17(2), 021005 (Feb 16, 2017) (8 pages) Paper No: JCISE-15-1310; doi: 10.1115/1.4034872 History: Received September 29, 2015; Revised September 18, 2016

Modern cyber-physical production systems (CPPS) connect different elements like machine tools and workpieces. The constituent elements are often equipped with high-performance sensors as well as information and communication technology, enabling them to interact with each other. This leads to an increasing amount and complexity of data that requires better analysis tools to support system refinement and revision performed by an expert. This paper presents a user-guided visual analysis approach that can answer relevant questions concerning the behavior of cyber-physical systems. The approach generates visualizations of aggregated views that capture an entire production system as well as specific characteristics of individual data features. To show the applicability of the presented methodologies, an exemplary production system is simulated and analyzed.

Copyright © 2017 by ASME
Your Session has timed out. Please sign back in to continue.


Monostori, L. , 2014, “ Cyber-Physical Production Systems: Roots, Expectations and R&D Challenges,” Procedia CIRP, 17, pp. 9–13. [CrossRef]
Kagermann, H. , Wahlster, W. , and Helbig, J. , 2013, “ Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0: Final Report of the Industrie 4.0 Working Group,” acatech—National Academy of Science and Engineering, Munich, Germany.
Leitão, P. , 2009, “ Agent-Based Distributed Manufacturing Control: A State-of-the-Art Survey,” Eng. Appl. Artif. Intell., 22(7), pp. 979–991. [CrossRef]
Monostori, L. , Váncza, J. , and Kumara, S. , 2006, “ Agent-Based Systems for Manufacturing,” Ann. CIRP, 55(2), pp. 697–720. [CrossRef]
Sendler, U. , ed., 2013, Industrie 4.0: Beherrschung der industriellen Komplexität mit SysLM. Xpert.press, Springer, Berlin.
Reinhart, G. , Schindler, S. , Pohl, J. , and Rimpau, C. , 2009, “ Cycle-Oriented Manufacturing Technology Chain Planning,” Third International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV).
Malak, R. C. , Yang, X. , and Aurich, J. C. , 2011, “ Analysing and Planning of Engineering Changes in Manufacturing Systems,” 44th CIRP Conference on Manufacturing Systems, N. A. Duffie , and M. F. DeVries , eds., Page number(s) not provided.
Malak, R. C. , and Aurich, J. C. , 2013, “ Software Tool for Planning and Analyzing Engineering Changes in Manufacturing Systems,” Procedia CIRP, 12, pp. 348–353. [CrossRef]
Dorozhkin, D. V. , Vance, J. M. , Rehn, G. D. , and Lemessi, M. , 2012, “ Coupling of Interactive Manufacturing Operations Simulation and Immersive Virtual Reality,” Virtual Reality, 16(1), pp. 15–23. [CrossRef]
Sacco, M. , Dal Maso, G. , Milella, F. , Pedrazzoli, P. , Rovere, D. , and Terkaj, W. , 2011, “ Virtual Factory Manager,” Virtual and Mixed Reality (LNCS Sublibrary. SL 3, Information Systems and Applications, Vol. 6773–6774), R. Shumaker , ed., Springer, Heidelberg, Germany, pp. 397–406.
Chemnitz, M. , Krüger, J. , Patzlaff, M. , and Tuguldur, E.-O. , 2010, “ SOPRO—Advancements in the Self-Organising Production,” IEEE Conference on Emerging Technologies and Factory Automation (ETFA 2010), Sept. 13–16.
Zühlke, D. , 2009, “ Smartfactory—A Vision Becomes Reality,” IFAC Proc. Vol., 42(4), pp. 31–39.
Leitão, P. , and Restivo, F. , 2006, “ ADACOR: A Holonic Architecture for Agile and Adaptive Manufacturing Control,” Comput. Ind., 57(2), pp. 121–130. [CrossRef]
Ilsen, R. , Meissner, H. , and Aurich, J. C. , 2015, “ Virtual Test Field for Sustainability Assessment of Cybertronic Production Systems,” ASME Paper No. MSEC2015-9232.
Plonka, D. , 2000, “ FlowScan: A Network Traffic Flow Reporting and Visualization Tool,” 14th USENIX Conference on System Administration, USENIX Association, pp. 305–318.
Potter, K. , Wilson, A. , Bremer, P.-T. , Williams, D. , Doutriaux, C. , Pascucci, V. , and Johhson, C. R. , 2009, “ Ensemble-Vis: A Framework for the Statistical Visualization of Ensemble Data,” IEEE Workshop on Knowledge Discovery from Climate Data: Prediction, Extremes, Dec. 6, pp. 233–240.
Lu, C.-T. , Boedihardjo, A. P. , and Zheng, J. , 2006, “ AITVS: Advanced Interactive Traffic Visualization System,” IEEE Computer Society, Apr. 3–7, p. 167.
Taylor, T. , Paterson, D. , Glanfield, J. , Gates, C. , Brooks, S. , and McHugh, J. , 2009, “ FloVis: Flow Visualization System,” CATCH, Mar. 3–4, pp. 186–198.
The World Bank, 2011, “ Trademap Visualizer,” World Bank, Washington, DC.
Klosterman, R. E. , and Brail, R. K. , eds., 2001, Planning Support Systems: Integrating Geographic Information Systems, Models, and Visualization Tools, 1st ed., Esri Press, Redlands, CA.
Wu, P. Y. , and Acharya, S. , 2011, “ Visualizing Capacity and Load: A Production Planning Information System for Metal Ingot Casting,” CONISAR Proc., 4(1823).
Doil, F. , Schreiber, W. , Alt, T. , and Patron, C. , 2003, “ Augmented Reality for Manufacturing Planning,” Workshop on Virtual Environments 2003, ACM, pp. 71–76.
Zhang, P. , 1996, “ Visualizing Production Planning Data,” IEEE, Computer Graphics and Applications, Vol. 16(5), pp. 7–10. [CrossRef]
Ertek, G. , Kuruca, C. , Aydin, C. , Erel, B. F. , Dogan, H. , Duman, M. , MeteOcal , and Ok, Z. D. , 2004, “ Visual and Analytical Mining of Transactions Data for Production Planning and Marketing,” Intelligent Manufacturing Systems, pp. 848–859.
Farin, G. , ed., 2001, Curves and Surfaces for CAGD: A Practical Guide, 5th ed. (Morgan Kaufmann Series in Computer Graphics and Geometric Modelling), Morgan Kaufmann, San Francisco, CA, pp. 119–146.
Gouraud, H. , 1971, “ Continuous Shading of Curved Surfaces,” IEEE Trans. Computer, C-20(6), pp. 623–629. [CrossRef]
Peysakhovich, V. , Hurter, C. , and Telea, A. , 2015, “ Attribute-Driven Edge Bundling for General Graphs With Applications in Trail Analysis,” 2015 IEEE Pacific Visualization Symposium (PacificVis), Apr. 14–17, pp. 39–46.
Phan, D. , Xiao, L. , Yeh, R. , Hanrahan, P. , and Winograd, T. , 2005, “ Flow Map Layout,” IEEE Information Visualization (InfoVis), Oct. 23–25, pp. 219–224.


Grahic Jump Location
Fig. 1

Flow view of a virtual production system showing the geometric model of the factory and its machines, the product flow for all products color-coded by product type, and the machine workloads for all machines

Grahic Jump Location
Fig. 2

Detailed views of the product flow demonstrating the visualization of different properties like product types (left image), methods to reduce visual clutter (middle image), and waiting times of the products (right image)

Grahic Jump Location
Fig. 3

Sequence of product flows for a short temporal window moving forward in time (left to right image), resulting in products moving through the virtual factory

Grahic Jump Location
Fig. 4

Unsorted (top image) and sorted (bottom image) workload of the first drilling machine showing the development of the machine's queue with its individual products waiting to be processed

Grahic Jump Location
Fig. 5

Workload view showing a workload for each machine in the virtual factory, thereby guiding the user to machines potentially being overloaded or redundant at certain interesting points in time

Grahic Jump Location
Fig. 6

Production view for all products of type C showing inactive and processing phases of their three operations under different aspects of manufacturing time, manufacturing begin, and degree of completion



Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In