Abstract
Production process control is an important issue. Production processes are affected by many factors and some processes are very complex. Statistical process control (SPC) can apply statistical methods to monitor and control production processes for quality improvement. SPC methods include control charts and process capability analysis. This paper presents a method for continuous production process improvement. The control flow of the proposed method is developed. The method identifies the production process to be improved, collects and verifies data, applies Xbar-R control chart analysis and process capability analysis, analyzes the causes, forms measures for improvement, and takes actions for the improvement. An application example is provided. The results of the study indicate the quality improvement of their production process. This research can provide a reference for companies to apply SPC methods and statistical tools and take process capability analysis and control chart analysis for production process control to improve the quality of production processes.
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Acknowledgment
The authors would like to thank the work of other people in the quality improvement group. The authors would like to thank the session chair, Professor Natalia Bakhtadze and the referees.
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© 2021 IFIP International Federation for Information Processing
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Yang, B., He, Y., Yin, H. (2021). Data Analysis and Production Process Control. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 630. Springer, Cham. https://doi.org/10.1007/978-3-030-85874-2_59
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DOI: https://doi.org/10.1007/978-3-030-85874-2_59
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