Humanzentriertes Zero Defect Manufacturing der Zukunft/Human-centered zero-defect manufacturing of the future

Table of contents

Bibliographic information


Cover of Volume: wt Werkstattstechnik online Volume 115 (2025), Issue 09
Open Access Full access

wt Werkstattstechnik online

Volume 115 (2025), Issue 09


Authors:
Publisher
VDI fachmedien, Düsseldorf
Copyright Year
2025
ISSN-Online
1436-4980
ISSN-Print
1436-4980

Chapter information


Open Access Full access

Volume 115 (2025), Issue 09

Humanzentriertes Zero Defect Manufacturing der Zukunft/Human-centered zero-defect manufacturing of the future


Authors:
ISSN-Print
1436-4980
ISSN-Online
1436-4980


Preview:

Sustainable industrial manufacturing can be significantly enhanced using data-driven, AI-supported systems. This paper presents a platform based on the three Zero³ dimensions: Zero Human Potential Loss, Zero Resource Loss, and Zero Data Loss. Using a recommender system designed with the retrieval-augmented generation principle, production bottlenecks are identified, suitable base technologies suggested, and recommendations for action derived. The platform supports companies in systematically evaluating and improving their production processes with a sustainability focus.

Bibliography


  1. [1] Intergovernmental Panel on Climate Change (IPCC): Climate Change 2021 – The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press 2021 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  2. [2] Umweltbundesamt: Klimaschutz in Zahlen. Fakten, Trends und Impulse deutscher Klimapolitik. Stand: 2020. Internet: media.frag-den-staat.de/files/foi/699554/klimaschutz-in-zahlen-2020.pdf. Zugriff am 25.08.2025 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  3. [3] Europäische Kommission: Deal für eine saubere Industrie. Stand: 2025. Internet: commission.europa.eu/topics/eu-competitiveness/clean-industrial-deal_de. Zugriff am 14.08.2025 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  4. [4] Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie (BMK): Österreich auf dem Weg zu einer nachhaltigen und zirkulären Gesellschaft Die österreichische Kreislaufwirtschaftsstrategie. Stand: 2022. Internet: www.bmluk.gv.at/dam/jcr:baacfdef-c63e-49f5-ab8f-e4be8c0d7504/ Kreislaufwirtschaftsstrategie_2022_230215.pdf. Zugriff am 25.08.2025 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  5. [5] Fragapane, G.; Eleftheriadis, R.; Powell, D. et al.: A global survey on the current state of practice in Zero Defect Manufacturing and its impact on production performance. Computers in Industry 148 (2023), #103879 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  6. [6] Powell, D.; Magnanini, M. C.; Colledani, M. et al.: Advancing Zero Defect Manufacturing: A State-of-the-Art Perspective and Future Research Direction“. Computers in Industry 136 (2022), #103596, doi.org/10.1016/j.compind.2021.103596 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  7. [7] vom Brocke, J.; Simons, A.; Niehaves, B. et al.: Reconstructing the Giant: On the Importance of Rigour in Documenting the Literature Search Process. ECIS 2009 Proceedings, 2009, paper #161 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  8. [8] Cooper, H. M.: Organizing knowledge syntheses: A taxonomy of literature reviews. Knowledge in Society 1 (1988) 1, pp. 104–126, doi.org/10.1007/BF03177550 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  9. [9] Caiazzo, B.; Di Nardo, M.; Murino, T. et al.: Towards Zero Defect Manufacturing paradigm: A review of the state-of-the-art methods and open challenges. Computers in Industry 134 (2022), #103548 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  10. [10] Nazarenko, A. A.; Sarraipa, J.; Camarinha-Matos, L. M. et al.: Analysis of Manufacturing Platforms in the Context of Zero-Defect Process Establishment. IFIP Advances in Information and Communication Technology (2020), pp. 583–596, doi.org/10.1007/978–3–030–62412–5_48 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  11. [11] Psarommatis F.; Kiritsis D.: Identification of the Inspection Specifications for Achieving Zero Defect Manufacturing. IFIP Advances in Information and Communication Technology 566 (2019), pp. 267–273 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  12. [12] Panagiotopoulou V. C.; Papacharalampopoulos A.; Stavropoulos P.: Developing a Manufacturing Process Level Framework for Green Strategies KPIs Handling. Lecture Notes in Mechanical Engineering (2023), pp. 1008–1015, doi.org/10.1007/978–3–031–28839–5_112 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  13. [13] Psarommatis, F.; Fraile, F.; Ameri, F.: Zero Defect Manufacturing ontology: A preliminary version based on standardized terms. Computers in Industry 145 (2023), #103832 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  14. [14] Tanane B. Dafflon B. Bentaha M.L. Moalla N. Ferreiro V.: Toward a Collaborative Sensor Network Integration for SMEs’ Zero-Defect Manufacturing. IFIP Advances in Information and Communication Technology 662 (2022), pp. 31–43, doi.org/10.1007/978–3–031–14844–6_3 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  15. [15] Adamson, G.; Gordon, D.: Industrial Strength Design: How Brooks Stevens Shaped Your World. Cambridge: MIT Press 2003 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  16. [16] Brondoni, S. M.: Planned Obsolescence, Total Quality, Zero Defects and Global Competition. Symphonya. Emerging Issues in Management (2018) 2, pp. 8–20, doi.org/10.4468/2018.2.02brondoni Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  17. [17] Psarommatis, F.; May, G.; Azamfirei, V.: Envisioning maintenance 5.0: Insights from a systematic literature review of Industry 4.0 and a proposed framework. Journal of Manufacturing Systems 68 (2023), pp. 376–399 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  18. [18] Schmidbauer, C.; Zafari, S.; Hader, B. et al.: An Empirical Study on Workers’ Preferences in Human–Robot Task Assignment in Industrial Assembly Systems. IEEE Transactions on Human-Machine Systems 53 (2023) 2, pp. 293–302, doi.org/ 10.1109/THMS.2022.3230667 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  19. [19] Silva, B.; Marques, R.; Faustino, D. et al.: Enhance the Injection Molding Quality Prediction with Artificial Intelligence to Reach Zero-Defect Manufacturing. Processes 11 (2023) 1, p. 62, doi.org/10.3390/pr11010062 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  20. [20] Wan, P. K. L.; Leirmo T. L.: .: Human-centric zero-defect manufacturing: State-of-the-art review, perspectives, and challenges. Computers in Industry 144 (2023), #103792 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  21. [21] Serrano-Ruiz, J. C.; Mula, J.; Poler, R.: Smart manufacturing scheduling: A literature review. Journal of Manufacturing Systems 61 (2021), pp. 265–287 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  22. [22] Konstantinidis, F. K.; Mouroutsos, S. G.; Gasteratos, A.: The Role of Machine Vision in Industry 4.0: an automotive manufacturing perspective. 2021 IEEE International Conference on Imaging Systems and Techniques (IST), Kaohsiung/Taiwan, IEEE 2021, pp. 1–6 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  23. [23] Psarommatis, F.; Danishvar, M.; Mousavi, A. et al.: Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing. IEEE Transactions on Engineering Management 71 (2024), pp. 702–714, doi.org/10.1109/TEM.2021.3133619 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  24. [24] Lughofer, E.; Zavoianu, A. C.; Pollak, R. et al.: On-line anomaly detection with advanced independent component analysis of multi-variate residual signals from causal relation networks. Information Sciences 537 (2020), pp. 425–451 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  25. [25] Lughofer, E.; Eitzinger, C.; Guardiola, C.: Online Quality Control with Flexible Evolving Fuzzy Systems. In: Sayed-Mouchaweh, M.; Lughofer, E. (eds.): Learning in Non-Stationary Environments. New York/USA: Springer 2012, pp. 375–406 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  26. [26] Lughofer, E.; Pollak, R.; Zavoianu, A. C. et al.: Self-Adaptive Time-Series Based Forecast Models for Predicting Quality Criteria in Microfluidics Chip Production. 2017 3rd IEEE International Conference on Cybernetics (CYBCONF), pp. 1–8 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  27. [27] Zambal, S.; Eitzinger, C.; Clarke, M. et al.: A digital twin for composite parts manufacturing: Effects of defects analysis based on manufacturing data. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN), pp. 803–808 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  28. [28] Zörrer, H.; Steringer, R.; Zambal, S. et al.: Using Business Analytics for Decision Support in Zero Defect Manufacturing of Composite Parts in the Aerospace Industry. IFAC-PapersOnLine 52 (2019) 13, pp. 1461–1466 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  29. [29] Zambal, S.; Heindl, C.; Eitzinger, C et al.: End-to-end defect detection in automated fiber placement based on artificially generated data. Fourteenth International Conference on Quality Control by Artificial Vision, SPIE 11172 (2019), pp. 371–378 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  30. [30] Isaja, M.; Nguyen, P.; Goknil, A. et al..: A blockchain-based framework for trusted quality data sharing towards zero-defect manufacturing. Computers in Industry 146 (2023), #103853 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  31. [31] Lindström, J.; Lejon, E.; Kyösti, P. et al.: Towards intelligent and sustainable production systems with a zero-defect manufacturing approach in an Industry 4.0 context. Procedia CIRP 81 (2019), pp. 880–885 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6
  32. [32] Psarommatis, F.; May, G.: Optimization of zero defect manufacturing strategies: A comparative study on simplified modeling approaches for enhanced efficiency and accuracy. Computers & Industrial Engineering 187 (2024), #109783, doi.org/10.1016/j.cie.2023.109783 Open Google Scholar DOI: 10.37544/1436-4980-2025-09-6

Citation


Download RIS Download BibTex