Quality Control Improvement Using Statistical Process Control in Manufacturing Industry

Joan Michael Soeryono; Rina Kartikasari Putri; Onur Doğan

doi:10.70716/reswara.v3i1.406

Authors

Joan Michael Soeryono Department of Industrial Engineering, Institut Teknologi Bandung, Bandung, Indonesia Author
Rina Kartikasari Putri Department of Industrial Engineering, Institut Teknologi Bandung, Bandung, Indonesia Author
Onur Doğan Department of Industrial Engineering, Middle East Technical University, Ankara, Türkiye Author

DOI:

https://doi.org/10.70716/reswara.v3i1.406

Keywords:

statistical process control, quality improvement, manufacturing industry, process capability, quality management

Abstract

Quality improvement remains a critical challenge in manufacturing industries due to increasing product complexity, strict customer requirements, and competitive market conditions. Statistical Process Control (SPC) has been widely recognized as an effective approach for monitoring process stability, reducing variability, and improving product quality. This study aims to analyze the application of SPC as a systematic method to enhance quality control performance in manufacturing operations. A quantitative case-study-based research design was adopted, focusing on production processes where quality deviations frequently occurred. Data were collected through direct observation, historical production records, and defect inspection reports. SPC tools, including control charts, process capability analysis, and Pareto analysis, were employed to identify process variations and root causes of defects. The results demonstrate that SPC implementation significantly improves process stability, reduces defect rates, and enhances process capability indices. Comparative analysis with previous studies confirms that SPC contributes to continuous improvement when supported by structured data analysis and corrective actions. This study concludes that SPC is a practical and reliable quality control approach that supports decision-making and operational excellence in manufacturing industries. The findings provide practical insights for quality engineers and managers seeking to strengthen quality assurance systems.

References

Ab Rahman, M. N., Mohd Zain, R., Mohd Alias, A., & Abdullah, A. (2015). Statistical process control: Best practices in small and medium enterprises. Maejo International Journal of Science and Technology, 9(2), 192–205. https://doi.org/10.1007/S40032-017-0395-5

Abu Taher, G., & Alam, M. J. (2014). Improving quality and productivity in manufacturing process by using quality control chart and statistical process control including sampling and six sigma. Global Journal of Research in Engineering, 14(2), 1–7.

Buduneli, Z., Erdinç, P., Erton, C., et al. (2024). Applications of statistical process control, quality improvement tools and techniques, and a simulation model in a garment manufacturing company. In Advances in manufacturing and industrial engineering (pp. 1–15). Springer. https://doi.org/10.1007/978-3-031-53991-6_31

Date, K., & Yukako, T. (2020). Quality-oriented statistical process control utilizing Bayesian modeling. In Proceedings of the IEEE International Symposium on Semiconductor Manufacturing (pp. 1–6). IEEE. https://doi.org/10.1109/ISSM51728.2020.9377496

Doğan, O., & Hızıroğlu, O. A. (2024). Empowering manufacturing environments with process mining-based statistical process control. Machines, 12(6), 411. https://doi.org/10.3390/machines12060411

Erdinç, P., Buduneli, Z., & Erton, C. (2024). Applications of statistical process control and quality improvement tools in garment manufacturing. In Springer Proceedings in Manufacturing. Springer. https://doi.org/10.1007/978-3-031-53991-6_31

Fadhilah, N., & Arifin, J. (2024). Analisis pengendalian kualitas produk part housing SUV menggunakan metode statistical process control di PT Y. Industrika, 8(2), 45–54. https://doi.org/10.37090/indstrk.v8i2.1206

Fuller, S. P. (2015). Leveraging statistical process control for continuous improvement of the manufacturing process (Doctoral dissertation).

Gaikwad, L., Sunnapwar, V. K., & Teli, S. N. (2019). Application of DMAIC and SPC to improve operational performance of manufacturing industry: A case study. Journal of the Institution of Engineers: Series C, 100(1), 47–56. https://doi.org/10.1007/S40032-017-0395-5

Godina, R., Matias, J. C. O., & Azevedo, S. (2016). Quality improvement with statistical process control in the automotive industry. International Journal of Industrial Engineering and Management, 7(2), 55–64. https://doi.org/10.24867/ijiem-2016-1-101

Görmen, M. (2022). Statistical process control (SPC) under the quality approach of just in time (JIT) manufacturing philosophy and an application. ISARDER Journal, 14(1), 23–34. https://doi.org/10.20491/isarder.2022.1402

Jamadar, S. (2020). Statistical process control. International Journal of Engineering Research and Technology, 9(9), 112–118.

Jha, A. (2024). Application of statistical process control in automotive manufacturing. International Journal for Science Technology and Engineering, 10(9), 55–61. https://doi.org/10.22214/ijraset.2024.64176

Khasanov, I. R. (2024). SPC method of statistical control of processes. EJCBLT, 1(3), 15–22. https://doi.org/10.61796/ejcblt.v1i3.433

Meran, İ., & Güner Gören, H. (2024). İstatistiksel süreç kontrolü ile iletken endüstrisinde kalite iyileştirme uygulaması. Deleted Journal. https://doi.org/10.17482/uumfd.1299193

Mihalcin, M. J., Mazzuchi, T. A., & Sarkani, S. (2014). Quality control: An approach applying multivariate control charts during the operation of systems involving human processes. Systems Engineering, 17(3), 293–305. https://doi.org/10.1002/sys.21263

Milić, Z., Jovanović, Z., & Nikolić, S. S. (2024). Application of statistical process control in tire manufacturing: Tread extruder line case study. In Proceedings of the IEEE International Conference on Electronics and Electrical Engineering (pp. 1–6). https://doi.org/10.1109/icetran62308.2024.10735428

Novaliansyah, P. P., Silalahi, J. M. P., & Sukreni, T. (2024). Pengendalian kualitas dengan metode statistical process control pada line produksi semi solid. Jurnal Kajian Ilmiah, 24(1), 1–10. https://doi.org/10.31599/q7taxw33

Ogrean, S. A., & Moldovan, L. (2024). A statistical method for improving the quality of electronic products in the automotive industry. In Automotive manufacturing systems (pp. 1–12). Springer. https://doi.org/10.1007/978-3-031-54664-8_41

Parmar, P. S., & Desai, T. N. (2018). Reduction of rework cost in manufacturing industry using statistical process control techniques: A case study. Industrial Engineering Journal, 10(6), 45–52. https://doi.org/10.26488/IEJ.10.6.46

Pérez-Vicente, H. A., Ruiz Morales, M., & Torres Bermúdez, E. G. (2024). Statistical process control and PDCA for quality improvement in the Mexican automotive industry. Ingeniería Investigación y Tecnología, 25(1), 1–12. https://doi.org/10.22201/fi.25940732e.2024.25.1.002

Solihudin, M. (2017). Pengendalian kualitas produksi dengan statistical process control (SPC). Industrial Engineering and Management Systems, 16(2), 75–83. https://doi.org/10.30813/jiems.v10i1.33

Swetha, S., & Gayatri, S. (2024). Statistical process control tools and applications. In Industrial quality systems (pp. 1–18). https://doi.org/10.58532/v3bgpn19p2ch7

Ural, Ö., & Elmali, C. (2023). Statistical process control as a tool for quality improvement: A case study in denim pant production. Muğla Journal of Science and Technology, 9(2), 112–120. https://doi.org/10.22531/muglajsci.1316596

Yang, B., He, Y., & Yin, H. (2021). Data analysis and production process control. In Advanced manufacturing analytics (pp. 1–14). Springer. https://doi.org/10.1007/978-3-030-85874-2_59

Zhao, N., He, Y., & Zhang, M. (2021). Product quality improvement based on process capability analysis. In Quality engineering applications (pp. 1–12). Springer. https://doi.org/10.1007/978-3-030-85874-2_63