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Submitted
September 19, 2025
Accepted
November 11, 2025
Published
January 2, 2026
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Abstract

PT X faced quality challenges in its spot-welding process, resulting in a high product defect rate and reduced competitiveness. Reliance on manual processes led to inconsistencies, which impacted customer satisfaction and the company's reputation. To address this issue, researchers initiated an Industry 4.0 based transformation with a Six Sigma approach. Improvements were made by implementing servo robots to automate the spot-welding process. This step was accompanied by modifications to the jig, the use of Jundate pallets, and the adoption of Zirconium cup tips to overcome downtime due to sticking. As a result, the company succeeded in significantly reducing the DPMO from 255 to 12, increasing productivity by 16%, and generating significant annual cost savings. In addition to tangible benefits, these improvements also resulted in increased customer trust, the acquisition of new projects, and an improved corporate image.

Keywords

automation industry 4.0 process efficiency production quality spot welding

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Copyright (c) 2025 Adidya Rangga Pratama, Bulan Prabawani

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How to Cite
Pratama, A. R., & Prabawani, B. . (2026). Implementasi Perbaikan Proses Spot Welding melalui Integrasi Teknologi Industri 4.0 dan Pokayoke untuk Meningkatkan Kualitas dan Stabilitas Produksi. AJIE (Asian Journal of Innovation and Entrepreneurship), 10(1), 16–29. https://doi.org/10.20885/ajie.vol10.iss1.art2
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References

  1. Antony, J., Sony, M., & McDermott, O. (2019). Reducing defects in manufacturing through Six Sigma DMAIC: A case study. The TQM Journal, 31(5), 705–720. https://doi.org/10.1108/TQM-12-2018-0194
  2. Aliyari, M., Rezaei, A., & Karimi, H. (2025). Advances in resistance spot welding for automotive applications. Journal of Materials Processing Technology, 309, 117726. https://doi.org/10.1016/j.jmatprotec.2022.117726
  3. Chuenmee, S., Phithakkitnukoon, S., & Kato, H. (2025). Quality improvement in automotive welding: A data-driven approach. Journal of Manufacturing Processes, 89, 45–58. https://doi.org/10.1016/j.jmapro.2024.12.005
  4. Costa, A. A., Ferraz, F., & Martins, R. A. (2019). Six Sigma in manufacturing: Evidence from case studies. Journal of Manufacturing Technology Management, 30(4), 648–666. https://doi.org/10.1108/JMTM-11-2017-0246
  5. Hemalatha, K., & Anusha, S. (2025). Comparative analysis of quality improvement methods: Lean, Six Sigma, and Taguchi. Quality Engineering, 37(2), 211–223. https://doi.org/10.1080/08982112.2024.1789903
  6. Jimenez, R., Molina, A., & Rodriguez, M. (2019). DMAIC methodology as a framework for continuous improvement in manufacturing. Total Quality Management & Business Excellence, 30(5–6), 567–584. https://doi.org/10.1080/14783363.2017.1400376
  7. Kementerian Perindustrian Republik Indonesia. (2018). Making Indonesia 4.0: Roadmap menuju Indonesia top 10 ekonomi dunia. Kementerian Perindustrian Republik Indonesia.
  8. Mittal, V., Gupta, P., & Sharma, A. (2023). Six Sigma implementation in automotive sector: Current trends and future prospects. International Journal of Lean Six Sigma, 14(1), 55–73. https://doi.org/10.1108/IJLSS-04-2021-0087
  9. Padmarajan, R., & Selvaraj, T. (2021). Six Sigma applications in manufacturing industries: A review. Materials Today: Proceedings, 46, 4236–4242. https://doi.org/10.1016/j.matpr.2020.10.550
  10. Papulova, Z., Gazova, A., & Papula, J. (2022). Industry 4.0 in automotive sector: Opportunities and challenges. Procedia Computer Science, 200, 1234–1242. https://doi.org/10.1016/j.procs.2022.01.314
  11. Silva, L. A., Gomes, R., & Costa, M. (2020). Pokayoke as a mistake-proofing approach in manufacturing systems. Journal of Manufacturing Processes, 49, 246–258. https://doi.org/10.1016/j.jmapro.2019.11.027
  12. Snee, R. D. (2017). Why Six Sigma will continue to thrive. Quality Progress, 50(5), 22–28.
  13. Sugiyono. (2013). Metode penelitian kuantitatif, kualitatif, dan R&D. Bandung: Alfabeta.
  14. Widiyanto, J. (2013). Statistik terapan: Konsep dan aplikasi SPSS/LISREL dalam penelitian pendidikan, psikologi & ilmu sosial lainnya. Jakarta: Elex Media Komputindo.
  15. Wang, Y., Li, X., & Zhou, D. (2024). The impact of Six Sigma on operational performance: Evidence from automotive firms. Operations Management Research, 17(2), 178–190. https://doi.org/10.1007/s12063-023-00291-5
  16. Xu, Y., Li, W., & Zhang, J. (2018). 4M1E-based quality control analysis in automotive manufacturing. International Journal of Production Research, 56(14), 4901–4914. https://doi.org/10.1080/00207543.2017.1391418