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2023 | 14 | nr 4 | 71-91
Tytuł artykułu

Integration of Overall Equipment Effectiveness and Six Sigma Approach to Minimize Product Defect and Machine Downtime

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study was conducted in a company that produces palm oil-based products such as cooking oil and margarine. The study aimed to encounter defects in packaging pouches. This study integrated the overall equipment effectiveness (OEE) with the six sigma DMAIC method. The OEE was performed to measure the efficiency of the machine. Three factors were measured in OEE: availability, performance, and quality. These factors were calculated and compared to the OEE world-class value. Then, the Multiple Linear Regression was performed using SPSS to determine the correlation between measurement variables toward the OEE value. Lastly, the six sigma method was implemented through the DMAIC approach to find the solution and improve the packaging quality. Supposing the recommendations are implemented, the OEE is expected to increase from 82% to 85%, with availability ratio, performance ratio, and quality ratio at, 99%, 86%, and 99.8%, respectively(original abstract)
Rocznik
Tom
14
Numer
Strony
71-91
Opis fizyczny
Twórcy
  • Sampoerna University, Indonesia
  • Universitas Bunda Mulia, Indonesia
  • Universitas Bunda Mulia, Indonesia
  • Sampoerna University, Indonesia
  • Universitas Bunda Mulia, Indonesia
autor
  • Goodman School of Business, Brock University, Canada
Bibliografia
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  • Allen, T.T., & Shanmugam, R. (2019). Introduction to engineering statistics and lean six sigma: statistical quality control and design of experiments and systems. Journal of Statistical Computation and Simulation, 89(15), 2980-2980. DOI: 10.1080/00949655. 2019.1589122.
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  • Andry, J.F., Nurprihatin, F., & Liliana, L. (2022b). Supply chain disruptions mitigation plan using six sigma method for sustainable technology infrastructure. Management and Production Engineering Review, 13(4), 88-97. DOI: 0.24425/mper.2022.142397.
  • Andry, J.F., Nurprihatin, F., & Liliana, L. (2023). Developing a decision support system for supply chain component. Management and Production Engineering Review, 14(2), 124-133. DOI: 0.24425/mper.2023.146029.
  • Cheah, C.K., Prakash, J., & Ong, K.S. (2020). Overall equipment effectiveness (OEE): a review and development of an integrated improvement framework. International Journal of Productivity and Quality Management, 1(1), 1-26. DOI: 10.1504/IJPQM.2019. 10020889.
  • Chiarini, A. (2015). Improvement of OEE performance using a lean six sigma approach: an Italian manufacturing case study. International Journal of Prductivity and Quality Management, 16(4), 416-433.DOI: 10.1504/IJPQM.2015.072414.
  • Chikwendu, O.C., Chima, A.S., & Edith, M.C. (2020).The optimization of overall equipment effectiveness factors in a pharmaceutical company. Heliyon, 6(4).DOI:10.1016/j.heliyon.2020.e03796.
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  • Febriana, T.H., & Hasbullah, H. (2021). Analysis anddefect improvement using FTA, FMEA, and MLR through DMAIC phase: case study in mixing process tire manufacturing industry. Journal Européen Des Systèmes Automatisés, 54(5), 721-731. DOI:10.18280/jesa.540507.
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  • Gabungan Pengusaha Kelapa Sawit Indonesia (GAPKI), (2021). Refleksi Industri Sawit 2020 dan Prospek 2021. Gabungan Pengusaha Kelapa Sawit Indonesia (GAPKI). https://gapki.id/news/18768/refleksi industri-sawit-2020-prospek-2021.
  • Gallesi-Torres, A., Velarde-Cabrera, A., León-Chavarri, C., Raymundo-Ibañez, C., & Dominguez, F. (2020). Maintenance management model under the TPM approach to reduce machine breakdownsin Peruvian giant squid processing smes. IOP Conference Series: Materials Science and Engineering, 796(1). DOI: 10.1088/1757-899x/796/1/012006.
  • Gaspersz, V., & Fontana, A. F. (2018). Lean six sigma for manufacturing and service industries waste elimination and continuous cost reduction. Bogor: Vinchristo Publication. Ginste, L. Van De, Aghezzaf, E.-H., & Cottyn, J. (2022).
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  • Girmanová, L., Šolc, M., Kliment, J., Divoková, A.,& Mikloš, V. (2017). Application of six sigma using DMAIC methodology in the process of product quality control in metallurgical operation. Acta Technologica Agriculturae, 20(4), 104-109. DOI:10.1515/ata-2017-0020.
  • Karamazova, E., Jusufi Zenku, T., & Trifunov, Z. (2017). Analysing and comparing the final grade in mathematics by Linear Regression using excel and SPSS.International Journal of Mathematics Trends and Technology, 52(5), 334-344. DOI: 10.14445/22315373/IJMTT-V52P549.
  • Khademi, F., Akbari, M., Jamal, S.M., & Nikoo, M.(2017). Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive strength of concrete. Frontiers of Structural and Civil Engineering, 11(1), 90-99. DOI: 10.1007/s11709-016-0363-9
  • Klemelä, J. (2018). Multivariate Data Analysis. In Non parametric Finance (pp. 95-120). DOI: 10.1002/9781119409137.ch4.
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  • Liu, L., Geng, Q., Zhang, Y., & Wang, Y. (2022). Investors' perspective on forecasting crude oil return volatility: where do we stand today? Journal of Management Science and Engineering, 7(3), 423-438. DOI: 10.1016/j.jmse.2021.11.001.
  • Lutfianto, M.A., & Prabowo, R. (2022). Implementation of six sigma methods with failure mode and effect analysis (FMEA) as a tool for quality im provement of newspaper products (case study: PT. ABC Manufacturing - Sidoarjo, East Java - Indone sia). Journal of Integrated System, 5(1), 87-98. DOI: 10.28932/jis.v5i1.4615.
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  • Mohammadi, M., Rai, P., & Gupta, S. (2017). Perfor mance evaluation of bucket Based Excavating, Loading and Transport (BELT) equipment - An OEE approach. Archives of Mining Sciences, 62(1), 105-120. DOI: 10.1515/amsc-2017-0008.
  • Montororing, Y.D.R., & Nurprihatin, F. (2021). Model of quality control station allocation with consider work in process, and defect probability of final product. Journal of Physics: Conference Series, 1811(1). DOI: 10.1088/1742-6596/1811/1/012013.
  • Nagi, A., & Altarazi, S. (2017). Integration of value stream map and strategic layout planning into DMAIC approach to improve carpeting process.Journal of Industrial Engineering and Management, 10(1), 74-97. DOI: 10.3926/jiem.2040.
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Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171679828
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