Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32759
Challenges for Interface Designers in Designing Sensor Dashboards in the Context of Industry 4.0

Authors: Naveen Kumar, Shyambihari Prajapati

Abstract:

Industry 4.0 is the fourth industrial revolution that focuses on interconnectivity of machine to machine, human to machine and human to human via Internet of Things (IoT). Technologies of industry 4.0 facilitate communication between human and machine through IoT and forms Cyber-Physical Production System (CPPS). In CPPS, multiple shop floors sensor data are connected through IoT and displayed through sensor dashboard to the operator. These sensor dashboards have enormous amount of information to be presented which becomes complex for operators to perform monitoring, controlling and interpretation tasks. Designing handheld sensor dashboards for supervision task will become a challenge for the interface designers. This paper reports emerging technologies of industry 4.0, changing context of increasing information complexity in consecutive industrial revolutions and upcoming design challenges for interface designers in context of Industry 4.0. Authors conclude that information complexity of sensor dashboards design has increased with consecutive industrial revolutions and designs of sensor dashboard causes cognitive load on users. Designing such complex dashboards interfaces in Industry 4.0 context will become main challenges for the interface designers.

Keywords: Industry 4.0, sensor dashboard design, Cyber-physical production system, Interface designer.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.3455623

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 606

References:


[1] Da, X. L., We, H., & Li, S. (2014). Internet of Things in Industries: A Survey. IEEE transaction on industrial informatics, pp (2233-2243).
[2] Lee, J., Bagheri, B., & Hung-An Kao. (2015). A Cyber-Physical Systems architecture for Industry 4.0 based manufacturing systems. Manufacturing Letters, pp (18-23).
[3] MacDougall, W. (2014). Industry 4.0: Smart manufacturing for the future. Berlin, Germany: GTAI.
[4] Wittenberg, C. (2015). Cause the Trend Industry 4.0 in the Automated Industry to New Requirements on User Interfaces? In International Conference on Human-Computer Interaction (pp. 238-245). Springer, Cham.
[5] Dewa, M. T., Matope, S., Van Der Merwe, A. F., &Nyanga, L. (2014). Holonic Control System: A proposed solution for managing dynamic events in a distributed manufacturing environment.
[6] Leitao, P., & Restivo, F. J. (2008). Implementation of a holonic control system in a flexible manufacturing system. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 38(5), 699-709.
[7] Vrba, P., Kadera, P., Jirkovský, V., Obitko, M., &Mařík, V. (2011). New trends of visualization in smart production control systems. In International Conference on Industrial Applications of Holonic and Multi-Agent Systems, pp. 72-83. Springer, Berlin, Heidelberg.
[8] Sackett, P. J., Al-Gaylani, M. F., Tiwari, A., & Williams, D. (2006). A review of data visualization: opportunities in manufacturing sequence management. International Journal of Computer Integrated Manufacturing, 19(7), 689-704.
[9] Sackett, P.J. and Williams, D. (2003) Data visualization in manufacturing decision making. Journal of Advanced manufacturing Systems, 2, 163–185.
[10] Somnath, Arjun & Biswas, Pradipta (2018). Personalizing large scale data visualization and interaction. UMAP '18- Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization. ACM digital Library
[11] Biswas, P., Roy, S., Prabhakar, G., Rajesh, J., Arjun, S., Arora, M., ... & Chakrabarti, A. (2017). Interactive sensor visualization for smart manufacturing system. In Proceedings of the 31st British Computer Society Human Computer Interaction Conference (p. 99). BCS Learning & Development Ltd.
[12] Zuehike, D. (2010). SmartFactory - Towards a factory-of-things. Annual reviews in control, 34(1), 129-138.
[13] Gorecky, D., Schmitt, M., Loskyll, M., & Zühlke, D. (2014). Human machine interaction in Industry 4.0 era. 12th IEEE International Conference on industrial informatics (pp. 289-294). Porto Alegre, Brazil: IEEE.
[14] Meixner, G., Petersen, N., & & Koessling, H. (2010). User interaction evolution in the SmartFactoryKL. In Proceedings of the 24th BCS Interaction Specialist Group Conference pp. (211–220). Dundee, UK. British Computer Society
[15] Deane, P. (1965). The first industrial revolution. Cambridge, UK: Cambridge university press.
[16] Kumar, N. & Kumar, J. (2019). Efficiency 4.0 for Industry 4.0. Journal of Human Technology, 15 (1), 55-78. DOI:10.17011/ht/urn.201902201608
[17] Greenwood. (1997). The third industrial revolution: technology, productivity, and income inequality. Washington, D.C., US: American Enterprise Institute.
[18] Donderi, D. (2006). Visual complexity: a review. Psychological bulletin, 132(1), 73.
[19] Chang, D., Dooley, L., & Tuovinen, J. E. (2002, July). Gestalt theory in visual screen design: a new look at an old subject. In Proceedings of the Seventh world conference on computers in education conference on Computers in education: Australian topics-Volume 8 (pp. 5-12). Australian Computer Society, Inc.
[20] Kumar, N & Kumar, J. (2019). Proposal of a User's Cognitive Load-Centric Methodology for HCI Based Control Panel Design. In Handbook of Research on Human-Computer Interfaces and New Modes of Interactivity (pp. 333-360). IGI Global.
[21] Kumar, N., & Kumar, J. (2019). Selection of Control Panel Design Using Cognitive Load Parameters Based on Physiological Data: An Experimental Study. The Design Journal, 1-20.
[22] Cowan, N. (2016). Working Memory Capacity: Classic Edition. Routledge.
[23] Bicocchi, N., Cabri, G., Mandreoli, F., & Mecella, M. (2018, September). Dealing with data and software interoperability issues in digital factories. In Proceedings of the 25th International Conference on Transdisciplinary Engineering (TE2018) (pp. 13-22).