Tri Dung Dang 1*

1 College of Technology and Design, University of Economics Ho Chi Minh City, Vietnam

 

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ABSTRACT

Despite the use of Operation Work Standards (OWS) in industrial manufacturing, human processes frequently result in failures such as product functionality issues, missing components, and improper packaging. An improved Interlocking System has been designed to address these recurrent difficulties. This system successfully leads workers and assures the sequential execution of tasks, lowering the risk of failure dramatically. The Interlocking System works in tandem with the Traceability system to automate the production of QR codes. Hardware upgrades, data collecting capabilities, and compatibility with numerous production lines are also included. The Interlocking System has shown remarkable accuracy, efficiency, and success in lowering the Risk Priority Number (RPN) score and resolving early challenges via rigorous testing and trials in a case study in a Viet Nam’s manufacturer. As a result, not only has this unique approach increased consumer confidence, but it has also improved the factory's reputation. Manual operation failures have been reduced, resulting in higher product quality, faster delivery, and higher overall customer satisfaction.


Keywords: Manual process, Interlocking system, PLC, Historical data, Viet Nam’s manufacturer, QR label, Compatibility, Control failure mode, RPN score.


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REFERENCES

  1. Adewale, D., Okediran, I.K., Idris, M.O., Oyewo, A.T., Adefajo, A.A. 2025. Application in product labeling: benefits, Challenges, Key Components and Technologies: A review. Borobudur Engineering Review, 5(1), 1–33.

  2. Aized, T., Ahmad, M., Jamal, M.H., Mahmood, A., Ubaid ur Rehman, S., Srai, J.S. 2020. Automotive leaf spring design and manufacturing process improvement using failure mode and effects analysis (FMEA). International Journal of Engineering Business Management, 12, 1–13.

  3. Bachhav, P.D., Patil, S.M., Jadhav, M.S., Kene, H.D. 2025. Leveraging MES Integration for Operational Excellence in A ‎green field Automotive Stamping Plant: A Digital Transformation ‎Case Study. International Journal of Basic and Applied Sciences, 14(4), 808–817.

  4. Cao, Y., Yin, X., Zhang, J., Ge, Y. 2024, November. Parts sorting and adjustment automatic production line control system based on PLC and WinCC. In Proceedings of the 4th International Conference on Computer, Internet of Things and Control Engineering, 97–101.

  5. Chongwatpol, J., Sharda, R. 2013. Rfid-enabled track and traceability in job-shop scheduling environment. European Journal of Operational Research 227, 453–463.

  6. Febriana, T.H., Hasbullah, H. 2021. Analysis and Defect Improvement Using FTA, FMEA, and MLR Through DMAIC Phase: Case Study in Mixing Process Tire Manufacturing Industry. Journal Européen Des Systèmes Automatisés, 54(5), 721.

  7. Fortuna, G., Gaspar, P.D. 2022. Implementation of industrial traceability systems: A case study of a luxury metal pieces manufacturing company. Processes, 10(11), 2444.

  8. Ghelani, H. 2024. AI-Driven quality control in PCB manufacturing: enhancing production efficiency and precision. Valley International Journal Digital Library, 12(10), 1549–1564.

  9. Haekal, J. 2022. Quality control with failure mode and effect analysis (FMEA) and fault tree analysis (FTA) Methods: Case Study Japanese Multinational Automotive Corporation. International Journal of Scientific Advances (IJSCIA), 3(2), 227.

  10. Hakulinen, T., Valentini, F., Havart, F., Ninin, P. 2015. Building an interlock: Comparison of technologies for constructing safety interlocks. Proceedings of ICALEPCS2015, Melbourne, Australia

  11. Huang, L. 2020. The past, present and future of railway interlocking system. In 2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE) (pp. 170–174). IEEE.

  12. Institute for Healthcare Improvement, 2017. QI Essentials Toolkit: Failure Modes and Effects Analysis (FMEA). Technical Report. Available at: https://www.hchmd.org/sites/default/files/wysiwyg/Failure%20Modes%20and%20Effects%20Analysis%20%28FMEA%29.pdf (Access on Mar. 2023)

  13. IQMS, 2017. 10 ways track and trace improves production efficiency. Available at: https://blogs.solidworks.com/delmiaworks/track-and-trace-production-efficiency/ (Access on Mar. 2023)

  14. Ishiyama, R., Kudo, Y., Takahashi, T. 2016. midot: Micro identifier dot on things—a tiny, efficient alternative to barcodes, tags, or marking for industrial parts traceability, in: 2016 IEEE International Conference on Industrial Technology (ICIT), IEEE, 781–786.

  15. Kieseberg, P., Leithner, M., Mulazzani, M., Munroe, L., Schrittwieser, S., Sinha, M., Weippl, E. 2010. QR code security. In Proceedings of the 8th International Conference on Advances in Mobile Computing and Multimedia, 430–435.

  16. Kuhn, M., Franke, J. 2020, January. Smart manufacturing traceability for automotive E/E systems enabled by event-driven microservice architecture. In 2020 IEEE 11th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT), 142–148. IEEE.

  17. Le, M.T., Nhieu, N.L. 2022. A novel multi-criteria assessment approach for post-COVID-19 production strategies in Vietnam manufacturing industry: OPA–fuzzy EDAS model. Sustainability, 14(8), 4732.

  18. Li, X.S., He, W.P., Lei, L., Wang, J., Guo, G.F., Zhang, T.Y., Yue, T. 2016. Laser direct marking applied to rasterizing miniature data matrix code on aluminum alloy. Optics & Laser Technology 77, 31–39.

  19. Liu, S., Xu, S., He, G., Hu, Y., Huang, M. 2023, August. Research on trusted traceability method of large-scale manufacturing industry based on blockchain. In 2023 5th International Conference on Industrial Artificial Intelligence (IAI), 1–8. IEEE.

  20. Oborski, P., Wysocki, P. 2022. Intelligent visual quality control system based on convolutional neural networks for holonic shop floor control of industry 4.0 manufacturing systems. Advances in Science and Technology. Research Journal, 16(2), 89–98.

  21. Olsen, P., Borit, M. 2013. How to define traceability. Trends in food science & technology, 29(2), 142–150.

  22. Omisola, J.O., Shiyanbola, J.O., Osho, G.O. 2024. A predictive quality assurance model using lean six sigma: Integrating FMEA. SPC, and root cause analysis for zero-defect production systems. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 1481–1497

  23. Petrova, K., Romaniello, A., Medlin, B. D., Vannoy, S. A. 2016. QR codes advantages and dangers. In 13th International Joint Conference on e-Business and Telecommunications, Vol. 2, pp. 112–116. SCITEPRESS–Science and Technology Publications, Lda.

  24. Pinto, D. B., Castro, I., Vicente, A.A. 2005. Development of an application to improve traceability and food safety management. In 2nd Mercosur Congress on Chemical Engineering, 4th Mercosur Congress on Process Systems Engineering, Rio de Janeiro, Brasil, 1–10.

  25. Prastyabudi, W.A., Faharga, R.A., Chandra, H. 2024. Systematic risk analysis of railway component quality: Integration of failure mode & effect analysis (FMEA) and fault tree analysis (FTA). Spektrum Industri, 22(2), 77–89.

  26. Querme, M.E.T. Lima, D.A. 2024. Traceability Automation in Coffee Production: A case study on QR code integration to optimize manual steps. Archives of Advanced Engineering Science, 2(3), 170–180.

  27. Renosori, P., Oemar, H. Fauziah, S.R. 2023. Combination of FTA and FMEA methods to improve efficiency in the manufacturing company. Acta Logistica (AL), 10(3), 487-495.

  28. Schuitemaker, R., Xu, X., 2020. Product traceability in manufacturing: A technical review. Procedia CIRP, 93, 700–705.

  29. Segovia, V.R., Theorin, A. 2012. History of Control History of PLC and DCS. University of Lund.

  30. Sehr, M.A., Lohstroh, M., Weber, M., Ugalde, I., Witte, M., Neidig, J., Hoeme, S., Niknami, M., Lee, E.A. 2020. Programmable logic controllers in the context of industry 4.0. IEEE Transactions on Industrial Informatics, 17(5), 3523–3533.

  31. Shearon, C.E. 2018. IPC-1782 standard for traceability of critical itemsbased on risk, in: 2018 Pan Pacific Microelectronics Symposium (Pan Pacific), IEEE. pp. 1–3.

  32. Shirou, W.A.K.A.Y.A.M.A., Yusuke, D., Satoshi, O., Atsushi, I. 2007. Cost-effective product traceability system based on widely distributed databases. Journal of Communications, 2(2), 45–52.

  33. Tiryakioglu, B., Kayakutlu, G., Duzdar, I. 2016. Medical device tracking via QR code and efficiency analyze. In 2016 Portland International Conference on Management of Engineering and Technology (PICMET), IEEE.pp. 3115–3128.

  34. Wang, C.N., Nhieu, N.L., Liu, W.L. 2024. Unveiling the landscape of Fintech in ASEAN: assessing development, regulations, and economic implications by decision-making approach. Humanities and Social Sciences Communications, 11(1), 1–16.

  35. Wang, C.N., Pham, T.D.T., Nhieu, N.L. 2021. Multi-layer fuzzy sustainable decision approach for outsourcing manufacturer selection in apparel and textile supply chain. Axioms, 10(4), p.262.

  36. Wang, C.N., Pham, T.D.T., Nhieu, N.L. 2023. A Composited regret-theory-based spherical fuzzy prioritization approach for moving high-tech manufacturing in Southeast Asia. Applied Sciences, 13(2), 688

  37. Wu, Z., Zhang, L., Gray, J. 2013. Traceability Database and Software Application. Technical Report. Available at: https://edepot.wur.nl/455347 (Access on Mar. 2023)

  38. You, M., Lin, M., Wang, S., Wang, X., Zhang, G., Hong, Y., Dong, Y., Jin, G., Xu, F. 2016. Three-dimensional quick response code based oninkjet printing of upconversion fluorescent nanoparticles for drug anticounterfeiting. Nanoscale 8, 10096–10104.

  39. Yun, K., Lee, H., Bang, H., Jeon, N.L. 2016. Qr-on-a-chip: a computer-recognizable micro-pattern engraved microfluidic device for high-throughput image acquisition. Lab on a Chip 16, 655–659.

  40. Zhong, R.Y., Xu, X., Wang, L. 2017. IoT-enabled smart factory visibility and traceability using laser-scanners. Procedia Manufacturing 10, 1–14.


ARTICLE INFORMATION

Received: 2023-05-29
Revised: 2024-05-02
Accepted: 2025-10-23
Available Online: 2025-12-02


Cite this article:

Dang, T.D., 2025. Design and deployment of an interlocking system for enhancing manufacturing process stability. International Journal of Applied Science and Engineering, 22, 2023192. https://doi.org/10.6703/IJASE.202512_22(4).005

  Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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