Implementation of Statistical Process Control through PDCA Cycle to Improve Potential Capability Index of Drop Impact Resistance: A Case Study at Aluminum Beverage and Beer Cans Manufacturing Industry in Indonesia

Sunadi Sunadi, Humiras Hardi Purba, Sawarni Hasibuan

Abstract

Purpose: The purposes of this study are first, to analyze why the process capability index (Cpk) for drop impact resistance (DIR) does not meet the specification or less than 1.33, and second, to find out what improvements should be made to make it meet the specification.

Methodology/Approach: The methodology used was Statistical Process Control (SPC) through the PDCA cycle, supporting with Cause and Effect Diagram (CED), Nominal Group Technique (NGT) and “why, what, where, when and how (5W1H)” method.

Findings: With the above methods, the result of the study was given a positive impact on the company. The average of DIR was increased from 20.40 cm to 25.76 cm, increased by 26.27% and the standard deviation was reduced from 1.80 to 1.48, and then the Cpk index was increased from 0.48 to 1.79 it means the process is in control and capable.

Research Limitation/implication: This research was limited only on the two-piece can aluminum cans manufacturing process, no for three-piece cans manufacturing. SPC through PDCA cycle is an interesting method for continuous improvement of process capability in the cans manufacturing industry.

Originality/Value of paper: This study highlights the area of future research SPC through the PDCA cycle to analyze and optimize process capability. Therefore, this research is considered to promote and adopt high-valued methodologies for supporting industry to achieve global competitive advantages.

References

Ani, M.N.C., Ishak, A.A. and Shahrul, K., 2016. Solving Quality Issues in Automotive Component Manufacturing Environment by utilizing Six Sigma DMAIC Approach and Quality tools. In: IEOM (Industrial Engineering and Operations Management), Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management. Kuala Lumpur, Malaysia, 08-10 March 2016. IEOM Society International. pp.1986-1997.

Bereman, M.S., Johnson, R., Bollinger, J., Boss, Y., Shulman, N., MacLean, B., Hoofnagle, A.N. and MacCoss, M.J., 2014. Implementation of Statistical Process Control for Proteomic Experiments Via LC-MS/MS. Journal of The American Society for Mass Spectrometry, [e-journal] 25(4), pp581-587. DOI: 10.1007/s13361-013-0824-5.

Chakraborty, A., 2016. Importance of the PDCA cycle for SMEs. International Journal of Mechanical Engineering, [e-journal] 3(5), pp.30-34. DOI: 10.14445/23488360/IJME-V3I5P105.

Darmawan, H., Hasibuan, S. and Hardi Purba, H., 2018. Application of Kaizen Concept with 8 Steps PDCA to Reduce in Line Defect at Pasting Process: A Case Study in Automotive Battery. International Journal of Advances in Scientific Research and Engineering, [e-journal] 4(8), pp.97-107. DOI: 10.31695/IJASRE.2018.32800.

Devani, V. and Wahyuni, F., 2017. Pengendalian Kualitas Kertas Dengan Menggunakan Statistical Process Control di Paper Machine 3. Jurnal Ilmiah Teknik Industri, [e-journal] 15(2), pp.87-93. DOI: 10.23917/jiti.v15i2.1504.

Dhounchak, D. and Biban, L.K., 2017. Total Quality Management and Its Applications. International Journal of Scientific Research in Mechanical and Materials Engineering, [e-journal] 1(1), pp.15-17.

Fazeli, A.R. and Sharifi, E., 2011. Statistical Control and Investigation of Capability of Process and Machine in Wire Cut Edm Process of Gas Turbine Blade Airfoil Tip. Engineering, [e-journal] 2011(3), pp.260-265. DOI: 10.4236/eng.2011.33030.

Godina, R., Matias, J.C.O. and Azevedo, S.G., 2016. Quality Improvement With Statistical Process Control in the Automotive Industry. International Journal of Industrial Engineering and Management, 7(1), pp.1-8.

Mohamed, N.A., 2016. Evaluation of the Functional Performance for Carbonated Beverage Packaging: A Review for Future Trends. Evaluation, 39. pp.53-61.

Magar, V.M. and Shinde, D.V.B., 2014. Application of 7 Quality Control (7 QC) Tools for Continuous Improvement of Manufacturing Processes. International Journal of Engineering Research and General Science, 2(4), pp-364-371.

Mangesha, Y., Singh, A.P. and Amedie, W.Y., 2013. Quality improvement using statistical process control tools in glass bottles manufacturing company. International Journal for Quality research, 7(1), pp.107-126.

Nabiilah, A.R., Hamedon, Z. and Faiz, M.T., 2018. Improving Quality Of Light Commercial Vehicle. Using PDCA Approach. Journal of Advanced Manufacturing Technology (JAMT), 12(1-1), 10p.

Nugroho, R.E., Marwanto, A. and Hasibuan, S., 2017. Reduce Product Defect in Stainless Steel Production Using Yield Management Method and PDCA. International Journal of New Technology and Research (IJNTR), 3(11), pp.39-46.

Ramirez, B. and Runger, G., 2006. Quantitative Techniques to Evaluate Process Stability. Quality Engineering, [e-journal] 18(1), pp.53-68. DOI: 10.1080/08982110500403581.

Rana, M., Zhang, X. and Akher, S.A., 2018. Determination of Factors and Quality Control of Car Painting Based on FMEA and SPC.V2. Modern Mechanical Engineering, [e-journal] 8(2), pp.158-177. DOI: 10.4236/mme.2018.82011.

Realyvásquez-Vargas, A., Arredondo-Soto, K., Carrillo-Gutiérrez, T. and Ravelo, G., 2018. Applying the Plan-Do-Check-Act (PDCA) Cycle to Reduce the Defects in the Manufacturing Industry. A Case Study. Applied Sciences, [e-journal] 8(11), 17p. DOI: 10.3390/app8112181.

Sagbas, A., 2009. Improving The Process Capability Of A Turning Operation By The Application Of Statistical Techniques. Materiali in Tehnologije, 43(1), pp.55-59.

Saputra, T., Hernadewita, H., Prawira Saputra, A.Y., Kusumah, L. and ST, H., 2019. Quality Improvement of Molding Machine through Statistical Process Control in Plastic Industry. Journal of Applied Research on Industrial Engineering, [e-journal] 6(2), pp.87-96. DOI: 10.22105/jarie.2019.163584.1068.

Sharma, G. and Rao, P.S., 2013. Process capability improvement of an engine connecting rod machining process. Journal of Industrial Engineering International, [e-journal] 9, 37. DOI: 10.1186/2251-712X-9-37.

Sharma, G., Rao, P.S. and Babu, B.S., 2018. Process capability improvement through DMAIC for aluminum alloy wheel machining. Journal of Industrial Engineering International, 14, pp.213-226. DOI: 10.1007/s40092-017-0220-z.

Sokovi, M., 2009. Basic Quality Tools in the Continuous Improvement Process. Strojniski Vestnik, 55(5), pp.333-341.

Solihudin, M. and Kusumah, L.H., 2017. Analisis Pengendalian Kualitas Proses Produksi Dengan Metode Statistical Process Control (SPC) Di PT. Surya Toto Indonesia, Tbk. In: ITN Malang, Seminar Nasional Inovasi Dan Aplikasi Teknologi Di Industri 2017. Malang, 4 February 2017. C31.1-8.

Supriyadi, E., 2018. Analisis Pengendalian Kualitas Produk Dengan Statistical Proses Control (SPC) Di PT. Surya Toto Indonesia, Tbk. Jurnal Ilmiah Teknik dan Manajemen Industri, [e-journal] 1(1), pp.63-73. DOI: 10.32493/jitmi.v1i1.y2018.p%25p.

Tuna, S., 2018. Keeping Track of Garment Production Process and Process Improvement using Quality Control Techniques. Periodicals of Engineering and Natural Sciences, [e-journal] 6(1), pp.11-26. DOI: 10.21533/pen.v6i1.162.

Trimarjoko, A., Saroso, D.S., Purba, H.H., Hasibuan, S., Jaqin, C. and Aisyah, S., 2019. Integration of nominal group technique, Shainin system and DMAIC methods to reduce defective products: A case study of tire manufacturing industry in Indonesia. Management Science Letters, [e-journal] 9, pp.3421-2432. DOI: 10.5267/j.msl.2019.7.013.

Authors

Sunadi Sunadi
sunadi210770@gmail.com (Primary Contact)
Humiras Hardi Purba
Sawarni Hasibuan
Sunadi, S., Purba, H. H., & Hasibuan, S. (2020). Implementation of Statistical Process Control through PDCA Cycle to Improve Potential Capability Index of Drop Impact Resistance: A Case Study at Aluminum Beverage and Beer Cans Manufacturing Industry in Indonesia. Quality Innovation Prosperity, 24(1), 104–127. https://doi.org/10.12776/qip.v24i1.1401
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