Skip to main content
SpringerLink
Log in

Interfaces, Interactions, and Industry 4.0: A Framework for the User-Centered Design of Industrial User Interfaces in the Internet of Production

  • Chapter
  • First Online:
Human-Technology Interaction

Abstract

The Digital Transformation is changing production and creates both new opportunities and requirements to support human operators in their work. To fully exploit the benefits, the integration of digital technology in the work processes needs to be balanced with the human factor by understanding users’ requirements and integrating these in the work processes. This article presents a broad series of prototypical Industrial User Interfaces as well as approaches and methods to investigate user interaction and workers’ requirements. The presented work is based on research activities from RWTH Aachen University’s Cluster of Excellence “Internet of Production” which combines multidisciplinary expertise to work on the future of digital production technology. Along different use cases we present the usage context, specific research question, and the methodological approaches as well as advantages and challenges for evaluating the interface. On the one hand, the article provides an overview of Industrial User Interfaces—from shop floor to strategic dimensions of production—and examples of the breadth of future Industrial User Interfaces (e.g., computer, VR, or Human-Robot-Interaction). On the other hand, it gives insights into current research challenges and their application in industry. We conclude with a research framework building on factors from the underlying production system, the interface, and the users that can inform future research on Industrial User Interfaces.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 84.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://www.iop.rwth-aachen.de/

References

  1. Liao, Y., Deschamps, F., de Loures, E. F. R., & Ramos, L. F. P. (2017). Past, present and future of Industry 4.0: A systematic literature review and research agenda proposal. International Journal of Production Research, 55, 3609–3629. https://doi.org/10.1080/00207543.2017.1308576

    Article  Google Scholar 

  2. Bruner, J. (2013). Industrial Internet - The machines are talking. Reilly Media.

    Google Scholar 

  3. Jeschke, S., Brecher, C., Meisen, T., Özdemir, D., & Eschert, T. (2017). Industrial Internet of things and cyber manufacturing systems. In Industrial Internet of things (pp. 3–19). Springer. https://doi.org/10.1007/978-3-319-42559-7_1

    Chapter  Google Scholar 

  4. Sisinni, E., Saifullah, A., Han, S., Jennehag, U., & Gidlund, M. (2018). Industrial internet of things: Challenges, opportunities, and directions. IEEE Transactions on Industrial Informatics, 14, 4724–4734. https://doi.org/10.1109/TII.2018.2852491

    Article  Google Scholar 

  5. Brauner, P., Dalibor, M., Jarke, M., Kunze, I., Koren, I., Lakemeyer, G., Liebenberg, M., Michael, J., Pennekamp, J., Quix, C., Rumpe, B., Van Aalst, W., Der Wehrle, K., Wortmann, A., & Ziefle, M. (2021). A computer science perspective on digital transformation in production. ACM Transactions on Internet of Things (TIOT), 3, 1–32.

    Google Scholar 

  6. Pennekamp, J., Glebke, R., Henze, M., Meisen, T., Quix, C., Hai, R., Gleim, L., Niemietz, P., Rudack, M., Knape, S., Epple, A., Trauth, D., Vroomen, U., Bergs, T., Brecher, C., Buhrig-Polaczek, A., Jarke, M., & Wehrle, K. (2019). Towards an infrastructure enabling the Internet of production. In 2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS) (pp. 31–37). IEEE. https://doi.org/10.1109/ICPHYS.2019.8780276

    Chapter  Google Scholar 

  7. Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019). Digital twin in industry: State-of-the-art. IEEE Transactions on Industrial Informatics, 15, 2405–2415. https://doi.org/10.1109/TII.2018.2873186

    Article  Google Scholar 

  8. Kadir, B. A., Broberg, O., & da Conceição, C. S. (2019). Current research and future perspectives on human factors and ergonomics in industry 4.0. Computers & Industrial Engineering, 137, 106004. https://doi.org/10.1016/j.cie.2019.106004

    Article  Google Scholar 

  9. Frazzon, E. M., Hartmann, J., Makuschewitz, T., & Scholz-Reiter, B. (2013). Towards socio-cyber-physical systems in production networks. Procedia CIRP, 7, 49–54. https://doi.org/10.1016/j.procir.2013.05.009

    Article  Google Scholar 

  10. Hermann, M., Pentek, T., & Otto, B. (2016). Design principles for Industrie 4.0 scenarios. In 2016 49th Hawaii International Conference on System Sciences (HICSS) (pp. 3928–3937). IEEE. https://doi.org/10.1109/HICSS.2016.488

    Chapter  Google Scholar 

  11. Kagermann, H. (2015). Change through digitization—Value creation in the age of Industry 4.0. In Management of permanent change (pp. 23–45). Springer.

    Google Scholar 

  12. Santoni de Sio, F., & Mecacci, G. (2021). Four responsibility gaps with artificial intelligence: Why they matter and how to address them. Philosophy & Technology. https://doi.org/10.1007/s13347-021-00450-x

  13. Baethge-Kinsky, V. (2020). Digitized industrial work: Requirements, opportunities, and problems of competence development. Frontiers in Sociology, 5. https://doi.org/10.3389/fsoc.2020.00033

  14. Hirsch-Kreinsen, H. (2016). Digitization of industrial work: Development paths and prospects. Journal for Labour Market Research., 49, 1–14. https://doi.org/10.1007/s12651-016-0200-6

    Article  Google Scholar 

  15. Paelke, V., & Röcker, C. (2015). User interfaces for cyber-physical systems: Challenges and possible approaches. In International Conference on Design, User Experience, and Usability (DUXU) (pp. 75–85). Springer. https://doi.org/10.1007/978-3-319-20886-2_8

    Chapter  Google Scholar 

  16. Mittelstädt, V., Brauner, P., Blum, M., & Ziefle, M. (2015). On the visual design of ERP systems – The role of information complexity, presentation and human factors. In 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015) and the Affiliated Conferences, AHFE 2015 (pp. 270–277). IEEE. https://doi.org/10.1016/j.promfg.2015.07.207

    Chapter  Google Scholar 

  17. Wilkesmann, M., & Wilkesmann, U. (2018). Industry 4.0 – Organizing routines or innovations? VINE Journal of Information and Knowledge Management Systems, 48, 238–254. https://doi.org/10.1108/VJIKMS-04-2017-0019

    Article  Google Scholar 

  18. Karabey, B. (2012). Big data and privacy issues. In International symposium on information management in a changing world (p. 3). Springer.

    Google Scholar 

  19. Ziefle, M., Halbey, J., & Kowalewski, S. (2016). Users’ willingness to share data on the Internet: Perceived benefits and caveats. In Proceedings of the International Conference on Internet of Things and Big Data (pp. 255–265). SCITEPRESS - Science and and Technology Publications. https://doi.org/10.5220/0005897402550265

    Chapter  Google Scholar 

  20. Hoff, K. A., & Bashir, M. (2015). Trust in automation: Integrating empirical evidence on factors that influence trust. Human Factors, 57, 407–434. https://doi.org/10.1177/0018720814547570

    Article  Google Scholar 

  21. Brauner, P., Philipsen, R., Calero Valdez, A., Ziefle, M., & Philipsen, R. (2019). What happens when decision support systems fail?—The importance of usability on performance in erroneous systems. Behaviour & Information Technology, 38, 1225–1242. https://doi.org/10.1080/0144929X.2019.1581258

    Article  Google Scholar 

  22. Biermann, H., Brauner, P., & Ziefle, M. (2021). How context and design shape human-robot trust and attributions. Paladyn Journal of Behavioural Robotics., 12, 74–86. https://doi.org/10.1515/pjbr-2021-0008

    Article  Google Scholar 

  23. Philipsen, R., Brauner, P., Valdez, A. C., & Ziefle, M. (2018). Evaluating strategies to restore trust in decision support systems in cross-company cooperation. In W. Karwowski, S. Trzcielinski, B. Mrugalska, M. Di Nicolantonio, & E. Rossi (Eds.), Advances in manufacturing, production management and process control. AHFE 2018. Advances in intelligent systems and computing (pp. 115–126). Springer. https://doi.org/10.1007/978-3-319-94196-7_11

    Chapter  Google Scholar 

  24. Courage, C., & Baxter, K. (2005). Understanding your users: A practical guide to user requirements methods. Tools & Techniques. Morgan Kaufmann Publishers.

    Google Scholar 

  25. Shneiderman, B., & Plaisant, C. (2004). Designing the user interface: Strategies for effective human-computer interaction (4th ed.). Pearson Addison Wesley.

    Google Scholar 

  26. Dix, A., Finlay, J., Abowd, G. D., & Beale, R. (Eds.). (2003). Human computer interaction. Pearson.

    Google Scholar 

  27. DIN/EN/ISO 9241–11. (1998). Ergonomic requirements for office work with visual display terminals (VDTs): Guidance on usability specifications and measures.

    Google Scholar 

  28. DIN EN ISO 9241-110. (2006). Ergonomie der Mensch-System-Interaktion – Teil 110: Grundsätze der Dialoggestaltung (ISO 9241-110:2006). Deutsche Fassung EN ISO, 2006, 9241.

    Google Scholar 

  29. International Organization for Standardization: ISO 9241-210:2010. (2019). Ergonomics of human-system interaction - Part 210: Human-Centred Design for Interactive Systems. ISO.

    Google Scholar 

  30. Ardanza, A., Moreno, A., Segura, Á., de la Cruz, M., & Aguinaga, D. (2019). Sustainable and flexible industrial human machine interfaces to support adaptable applications in the Industry 4.0 paradigm. International Journal of Production Research., 57, 4045–4059. https://doi.org/10.1080/00207543.2019.1572932

    Article  Google Scholar 

  31. Fox, W. M. (1995). Sociotechnical system principles and guidelines: Past and present. The Journal of Applied Behavioral Science., 31, 91–105. https://doi.org/10.1177/0021886395311009

    Article  Google Scholar 

  32. Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the Longwall method of coal-getting. Human Relations, 4, 3–38. https://doi.org/10.1177/001872675100400101

    Article  Google Scholar 

  33. Liebenberg, M., & Jarke, M. (2020). Information systems engineering with digital shadows: Concept and case studies. In International Conference on Advanced Information Systems Engineering (pp. 70–84). Springer. https://doi.org/10.1007/978-3-030-49435-3_5

    Chapter  Google Scholar 

  34. Jarke, M., Schuh, G., Brecher, C., Brockmann, M., & Porte, J.-P. (2018). Digital shadows in the internet of production. ERCIM News, 115, 26–28.

    Google Scholar 

  35. Schuh, G., Prote, J.-P., Gützlaff, A., Thomas, K., Sauermann, F., & Rodemann, N. (2019). Internet of production: Rethinking production management. In Production at the leading edge of technology (pp. 533–542). Springer. https://doi.org/10.1007/978-3-662-60417-5_53

    Chapter  Google Scholar 

  36. Brauner, P., Brillowski, F., Dammers, H., Königs, P., Kordtomeikel, F., Petruck, H., Schaar, A. K., Schmitz, S., Steuer-Dankert, L., Mertens, A., Gries, T., Leicht-Scholten, C., Nagel, S., Nitsch, V., Schuh, G., & Ziefle, M. (2020). A research framework for human aspects in the internet of production – An intra-company perspective. In Advances in intellifgent systems and computing (pp. 3–17). Springer. https://doi.org/10.1007/978-3-030-51981-0_1

    Chapter  Google Scholar 

  37. Villani, V., Pini, F., Leali, F., & Secchi, C. (2018). Survey on human–robot collaboration in industrial settings: Safety, intuitive interfaces and applications. Mechatronics, 55, 248–266. https://doi.org/10.1016/j.mechatronics.2018.02.009

    Article  Google Scholar 

  38. Brauner, P., Bremen, L., Ziefle, M., Altorf, L., Rast, M., & Rossmann, J. (2014). Impact of different feedback conditions on worker’s performance in carbon-fiber reinforced plastic manufacturing. In T. Ahram, W. Karwowski, & T. Marek (Eds.), Proceedings of the 15th International Conference on The Human Aspects of Advanced Manufacturing (HAAMAHA): Manufacturing enterprises in a digital world (pp. 5087–5097). CRC Press.

    Google Scholar 

  39. Chandrasekaran, B., & Conrad, J. M. (2015). Human-robot collaboration: A survey. Conference Proceedings - IEEE SOUTHEASTCON. https://doi.org/10.1109/SECON.2015.7132964

  40. Heinz, M., Martin, P., Margrett, J. A., Yearns, M., Franke, W., Yang, H.-I., Wong, J., & Chang, C. K. (2013). Perceptions of technology among older adults. Journal of Gerontological Nursing., 39, 42–51. https://doi.org/10.3928/00989134-20121204-04

    Article  Google Scholar 

  41. Onnasch, L., & Roesler, E. (2020). A taxonomy to structure and analyze human–robot interaction. International Journal of Social Robotics. https://doi.org/10.1007/s12369-020-00666-5

  42. Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38, 475–487. https://doi.org/10.1006/imms.1993.1022

    Article  Google Scholar 

  43. Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., Bonnefon, J.-F., & Rahwan, I. (2018). The moral machine experiment. Nature, 1. https://doi.org/10.1038/s41586-018-0637-6

  44. Liehner, G. L., Brauner, P., Schaar, A. K., & Ziefle, M. (2021). Delegation of moral tasks to automated agents: The impact of risk and context on trusting a machine to perform a task. IEEE Transactions on Technology and Society., 1–14. https://doi.org/10.1109/TTS.2021.3118355

  45. Brauner, P., Calero Valdez, A., Philipsen, R., & Ziefle, M. (2016). Defective still deflective – How correctness of decision support systems influences user’s performance in production environments. In F. F.-H. Nah & C.-H. Tan (Eds.), HCI in Business, Government, and Organizations (HCIGO), held as part of HCI international 2016 (pp. 16–27). Springer. https://doi.org/10.1007/978-3-319-39399-5_2

    Chapter  Google Scholar 

  46. Goddard, K., Roudsari, A., & Wyatt, J. C. (2012). Automation bias: A systematic review of frequency, effect mediators, and mitigators. Journal of the American Medical Informatics Association, 19, 121–127. https://doi.org/10.1136/amiajnl-2011-000089

    Article  Google Scholar 

  47. Forrester, J. W. (1961). Industrial dynamics. Wiley.

    Google Scholar 

  48. Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science, 43, 546–558.

    Article  MATH  Google Scholar 

  49. Brauner, P., Runge, S., Groten, M., Schuh, G., & Ziefle, M. (2013). Human factors in supply chain management – Decision making in complex logistic scenarios. In S. Yamamoto (Ed.), Proceedings of the 15th HCI International 2013, Part III, LNCS 8018 (pp. 423–432). Springer.

    Google Scholar 

  50. Brauner, P., Philipsen, R., Fels, A., Fuhrmann, M., Ngo, H., Stiller, S., Schmitt, R., & Ziefle, M. (2016). A game-based approach to meet the challenges of decision processes in ramp-up management. Quality Management Journal, 23, 55–69. https://doi.org/10.1080/10686967.2016.11918462

    Article  Google Scholar 

  51. Philipsen, R., Brauner, P., Stiller, S., Ziefle, M., & Schmitt, R. (2014). The role of human factors in production networks and quality management. In First International Conference, HCIB 2014, held as part of HCI International 2014, Heraklion, Crete, Greece, June 22–27, 2014 (Proceedings, LNCS 8527) (pp. 80–91). Springer. https://doi.org/10.1007/978-3-319-07293-7_8

    Chapter  Google Scholar 

  52. Teniwut, W. A., & Hasyim, C. L. (2020). Decision support system in supply chain: A systematic literature review. Uncertain Supply Chain Management, 8, 131–148. https://doi.org/10.5267/j.uscm.2019.7.009

    Article  Google Scholar 

  53. Philipsen, R., Brauner, P., Stiller, S., Ziefle, M., & Schmitt, R. (2014). Understanding and supporting decision makers in quality management of production networks. In Advances in the ergonomics in manufacturing. Managing the enterprise of the future 2014: Proceedings of the 5th International Conference on Applied Human Factors and Ergonomics, AHFE 2014 (pp. 94–105). CRC Press.

    Google Scholar 

  54. Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8, 293–332. https://doi.org/10.1207/s1532690xci0804_2

    Article  Google Scholar 

  55. Brauner, P., Valdez, A. C., Philipsen, R., & Ziefle, M. (2016). On studying human factors in complex cyber-physical systems. In Workshop human factors in information visualization and decision support systems part of the mensch und computer 2016. Gesellschaft für Informatik. https://doi.org/10.18420/muc2016-ws11-0002

    Chapter  Google Scholar 

  56. Calero Valdez, A., Brauner, P., Schaar, A. K., Holzinger, A., & Ziefle, M. (2015). Reducing complexity with simplicity - Usability methods for Industry 4.0. In 19th Triennial Congress of the International Ergonomics Association (IEA 2015). IEA. https://doi.org/10.13140/RG.2.1.4253.6809

    Chapter  Google Scholar 

  57. Bennett, N., & Lemoine, G. J. (2014). What a difference a word makes: Understanding threats to performance in a VUCA world. Business Horizons, 57, 311–317. https://doi.org/10.1016/j.bushor.2014.01.001

    Article  Google Scholar 

  58. McAfee, A., & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review., 90, 61–68. https://doi.org/10.1007/s12599-013-0249-5

    Article  Google Scholar 

  59. Mertens, A., Putz, S., Brauner, P., Brillowski, F., Buczak, N., Dammers, H., Van Dyck, M., Kong, I., Konigs, P., Kordtomeikel, F., Rodemann, N., Schaar, A. K., Steuer-Dankert, L., Wlecke, S., Gries, T., Leicht-Scholten, C., Nagel, S. K., Piller, F. T., Schuh, G., et al. (2021). Human digital shadow: Data-based modeling of users and usage in the Internet of production. In 14th International Conference on Human System Interaction (HSI) (pp. 1–8). IEEE. https://doi.org/10.1109/HSI52170.2021.9538729

    Chapter  Google Scholar 

  60. Miraz, M. H., Ali, M., & Excell, P. S. (2021). Adaptive user interfaces and universal usability through plasticity of user interface design. Computer Science Review., 40, 100363. https://doi.org/10.1016/j.cosrev.2021.100363

    Article  Google Scholar 

  61. Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46, 50–80. https://doi.org/10.1518/hfes.46.1.50.30392

    Article  Google Scholar 

  62. Masalonis, A. J., & Parasuraman, R. (1999). Trust as a construct for evaluation of automated aids: Past and future theory and research. Proceedings of the Human Factors and Ergonomics Society Annual Meeting., 43, 184–187. https://doi.org/10.1177/154193129904300312

    Article  Google Scholar 

  63. Parasuraman, R., & Riley, V. (1997). Humans and automation: Use, misuse, disuse, abuse. Human Factors: The Journal of the Human Factors and Ergonomics Society, 39, 230–253. https://doi.org/10.1518/001872097778543886

    Article  Google Scholar 

  64. Endsley, M. R. (2017). From here to autonomy: Lessons learned from human-automation research. Human Factors, 59, 5–27. https://doi.org/10.1177/0018720816681350

    Article  Google Scholar 

  65. Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227–268.

    Article  Google Scholar 

  66. Molino, M., Cortese, C. G., & Ghislieri, C. (2020). The promotion of technology acceptance and work engagement in industry 4.0: From personal resources to information and training. International Journal of Environmental Research and Public Health, 17, 2438. https://doi.org/10.3390/ijerph17072438

    Article  Google Scholar 

  67. Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., Chatila, R., & Herrera, F. (2020). Explainable explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82–115. https://doi.org/10.1016/j.inffus.2019.12.012

    Article  Google Scholar 

Download references

Acknowledgments

Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2023 Internet of Production – 390621612. With thank the anonymous reviewers for their valuable feedback and Nina Braun for editing the manuscript.

Author information

Authors and Affiliations

  1. Human-Computer Interaction Center, RWTH Aachen University, Aachen, Germany

    Philipp Brauner, Anne Kathrin Schaar & Martina Ziefle

Authors
  1. Philipp Brauner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anne Kathrin Schaar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Martina Ziefle
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Philipp Brauner .

Editor information

Editors and Affiliations

  1. Institute Industrial IT, OWL University of Applied Sciences and Arts, Lemgo, Germany

    Carsten Röcker

  2. Institute Industrial IT, OWL University of Applied Sciences and Arts, Lemgo, Germany, Human-Centered Information Systems, Clausthal University of Technology, Clausthal-Zellerfeld, Germany

    Sebastian Büttner

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Brauner, P., Schaar, A.K., Ziefle, M. (2023). Interfaces, Interactions, and Industry 4.0: A Framework for the User-Centered Design of Industrial User Interfaces in the Internet of Production. In: Röcker, C., Büttner, S. (eds) Human-Technology Interaction. Springer, Cham. https://doi.org/10.1007/978-3-030-99235-4_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-99235-4_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-99234-7

  • Online ISBN: 978-3-030-99235-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation