Quality improvement of molding machine through statistical process control in plastic industry

Document Type: Research Paper

Authors

1 Master of Industrial Engineering Program, Mercu Buana University, Indonesia.

2 Faculty of Economic Social Science, Bakrie University, Indonesia.

Abstract

Enhancing the process capability is a must in quality improvement of process manufacturing in the industry. Usually, Statistical Process Control (SPC) is applied in measure the activity of quality improvement. In this case, the statistical process control used to measure the process capability of molding machine regarding of force result of inner contact rubber button in plastic industry. The forces of inner contact rubber button which produce by molding machine already become the critical point as a judgment of malfunctions or not. Meanwhile, the forces problem still found in molding machine that affected to the inner contact rubber button as defect product. Furthermore, as shown of SPC, the process capability of molding machine was 0.63. This mean the process capability is still need the improvement. As the result of quality improvement was made by applied of Poka-Yoke, the process capability of molding machine was improved to 1.65.

Keywords

Main Subjects


[1]     2017 plastics manufacturing survey results: U.S. manufacturing at all-time high, growth predicted, shifts in process popularity (n.d.). Retrieved May 15, 2019 from https://www.rayplastics.com/plastics-manufacturing-survey-results/

[2]     Das, S., & Nanda, A. K. (2013). Some stochastic orders of dynamic additive mean residual life model. Journal of statistical planning and inference143(2), 400-407.

[3]     Motorcu, A. R., & Güllü, A. (2006). Statistical process control in machining, a case study for machine tool capability and process capability. Materials & design27(5), 364-372.

[4]     Baldassarre, T., Boffoli, N., Caivano, D., & Visaggio, G. (2004, April). Managing software process improvement (SPI) through statistical process control (SPC). International conference on product focused software process improvement (pp. 30-46). Springer, Berlin, Heidelberg.

[5]     Woodall, W. H. (2000). Controversies and contradictions in statistical process control. Journal of quality technology32(4), 341-350.

[6]     John, B., & Areshankar, A. (2018). Reduction of rework in bearing end plate using six sigma methodology: a case study. Journal of applied research on industrial engineering5(1), 10-26.

[7]     Jabnoun, N. (2002). Control processes for total quality management and quality assurance. Work study51(4), 182-190.

[8]     Xie, M., & Goh, T. N. (1999). Statistical techniques for quality. The TQM magazine11(4), 238-242.

[9]     Sanches Jr, L., & Batalha, G. F. (2008). Automotive body-in-white dimensional stability through pre-control application in the subassembly process. Journal of achievements in materials and manufacturing engineering31(2), 705-711.

[10]  Škulj, G., Butala, P., & Sluga, A. (2013). Statistical process control as a service: an industrial case study. Procedia CIRP7, 401-406.

[11]  Montgomery, D. C. (2007). Introduction to statistical quality control. John Wiley & Sons.

[12]  Fournier, B., Rupin, N., Bigerelle, M., Najjar, D., & Iost, A. (2006). Application of the generalized lambda distributions in a statistical process control methodology. Journal of process control16(10), 1087-1098.

[13]  Srikaeo, K., Furst, J. E., & Ashton, J. (2005). Characterization of wheat-based biscuit cooking process by statistical process control techniques. Food control16(4), 309-317.

[14]  Cook, D. F., Zobel, C. W., & Wolfe, M. L. (2006). Environmental statistical process control using an augmented neural network classification approach. European journal of operational research174(3), 1631-1642.

[15]  Rungtusanatham, M. (2001). Beyond improved quality: the motivational effects of statistical process control. Journal of operations management19(6), 653-673.

[16]  Pearn, W. L., & Chen, K. S. (2002). One-sided capability indices C PU and C PL: decision making with sample information. International journal of quality & reliability management19(3), 221-245.

[17]  Opit, P. F., Samadhi, T. A., & Singal, Y. M. (2008). Penerapan Six Sigma Untuk Peningkatan Kualitas Produk Bimoli Classic (Studi Kasus: PT. Salim Ivomas Pratama–Bitung). J@ TI UNDIP: JURNAL TEKNIK INDUSTRI, 3(1), 17-

[18]  C─▒nar A. Study of process capability: An example and difficulties. Engineer and Machine 1987;28(329):31–2.

[19]  Kapuria, T. K., Rahman, M., & Haldar, S. (2017). Root Cause Analysis and Productivity Improvement of An Apparel Industry In Bangladesh Through Kaizen Implementation. Journal of applied research on industrial engineering4(4), 227-239.

[20]  Shingo, S., & Dillon, A. P. (1989). A study of the Toyota production system: from an industrial engineering viewpoint. CRC Press.