PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2023 | 14 | nr 3 | 134--147
Tytuł artykułu

Green Supply Chain Management: A Comprehensive Review of Research, Applications and Future Directions

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study uses statistical quality control (SQC) and overall equipment effectiveness (OEE) to examine quality at a porcelain production firm. The study is motivated by the most frequently broken machines in 2019, is the Jigger 01 machine. This paper aims to evaluate the machine's effectiveness using the OEE method. The OEE determines the scope of the problem to be solved using the SQC method. The average OEE value in 2019 was 70%. Based on the SQC method, the product defect produced is still under control. However, the average defect is still above the company's tolerance limit of 10%. Consequently, this study offers enhancements utilizing the Failure Mode Effect Analysis (FMEA) technique. The results indicate that human resources and machines caused defective products. This paper contributes to providing several improvements that the company can apply to maximize its quality control analysis. After implementing the improvement, the OEE value increases to 74%. (original abstract)
Rocznik
Tom
14
Numer
Strony
134--147
Opis fizyczny
Twórcy
  • Sampoerna University, Indonesia
  • Universitas Bunda Mulia, Indonesia
  • Universitas Bunda Mulia, Indonesia
  • Universitas Bunda Mulia, Indonesia
  • Universitas Bunda Mulia, Indonesia
Bibliografia
  • Ahire, C.P., Relkar, A.S. (2012). Correlating failure mode effect analysis (FMEA) & overall equipment effectiveness (OEE). Procedia Engineering, 38, 3482-3486. DOI: 10.1016/j.proeng.2012.06.402.
  • Andrade, M.G. de, Boas, M.A.V., Siqueira, J.A.C., Dieter, J., Sato, M., Hermes, E., Mercante, E., Tokura, L.K. (2017). Statistical quality control for the evaluation of the uniformity of microsprinkler irrigation with photovoltaic solar energy. Renewable and Sustainable Energy Reviews, 78, 743-753. DOI: 10.1016/j.rser.2017.05.012.
  • Andry, J.F., Nurprihatin, F., Liliana, L. (2022). 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.
  • Antony, J., Snee, R., Hoerl, R. (2017). Lean six sigma: yesterday, today and tomorrow. International Journal of Quality & Reliability Management, 34(7), 1073-1093. DOI: 10.1108/IJQRM-03-2016-0035.
  • Anusha, C., Umasankar, V. (2020). Performance prediction through OEE-Model. International Journal of Industrial Engineering and Management, 11(2), 93-103. DOI: 10.24867/IJIEM-2020-2-256.
  • Appollis, L.-L.M., Dyk, W.A. Van, Matope, S. (2020). Using failure modes and effects analysis as a problem-solving guideline when implementing SPC in a South African chemical manufacturing company. South African Journal of Industrial Engineering, 31(1), 157-169. DOI: 10.7166/31-1-2294.
  • Bergs, T., Stauder, L., Beckers, A., Grünebaum, T., Barth, S. (2021). Adaptive design of manufacturing process sequences in case of short-term disruptions in the production process. Manufacturing Letters, 27, 92-95. DOI: 10.1016/j.mfglet.2021.01.004.
  • Chukhrova, N., Johannssen, A. (2023). Employing fuzzy hypothesis testing to improve modified p charts for monitoring the process fraction nonconforming. Information Sciences, 633, 141-157. DOI: 10.1016/j.ins.2023.03.036.
  • Coccia, M. (2017). The fishbone diagram to identify, systematize and analyze the sources of general purpose technologies. Journal of Social and Administrative Sciences, 4(4), 291-303. DOI: 10.1453/jsas.v4i4.1518.
  • Dejene, N.D., Gopal, M. (2021). The hybrid pareto chart and FMEA methodology to reduce various defects in injection molding process. Solid State Technology, 64(2), 3541-3555.
  • Dwiartono, A.I., Nugraha, M.D., Kara, M.A.J., Dora, Y.M. (2020). Application of statistical quality control (SQC) for product 04G22 on PT. Maruichi Indonesia. Solid State Technology, 63(4), 4966-4976.
  • Ginting, R., Supriadi, S. (2021). Defect analysis on PVC pipe using statistical quality control (SQC) approach to reduce defects (Case Study: PT. XYZ). IOP Conference Series: Materials Science and Engineering, 1041(1). DOI: 10.1088/1757-899X/1041/1/012040.
  • Jaqin, C., Rozak, A., Purba, H.H. (2020). Case study in increasing overall equipment effectiveness on progressive press machine using plan-do-check-act cycle. International Journal of Engineering, 33(11), 2245-2251. DOI: 10.5829/ije.2020.33.11b.16.
  • Jimenez, G., Santos, G., Sá, J.C., Ricardo, S., Pulido, J., Pizarro, A., Hernández, H. (2019). Improvement of productivity and quality in the value chain through lean manufacturing - a case study. Procedia Manufacturing, 41, 882-889. DOI: 10.1016/ j.promfg.2019.10.011.
  • Karthik, D. (2020). Evolution of performance of work by check sheet in constructional activities. International Journal of Progressive Research in Science and Engineering, 1(8), 69-78.
  • Kulkarni, T., Toksha, B., Shirsath, S., Pankade, S., Autee, A.T. (2023). Construction and praxis of six sigma DMAIC for bearing manufacturing Process. Materials Today: Proceedings, 72, 1426-1433. DOI: 10.1016/j.matpr.2022.09.342.
  • Li, F., Zhang, L., Dong, S., Xu, L., Zhang, H., Chen, L. (2023). Risk assessment of bolt-gasket-flange connection (BGFC) failures at hydrogen transfer stations based on improved FMEA. International Journal of Hydrogen Energy. DOI: 10.1016/j.ijhydene.2023.06.191.
  • Mascia, A., Cirafici, A. M., Bongiovanni, A., Colotti, G., Lacerra, G., Di Carlo, M., Digilio, F.A., Liguori, G.L., Lanati, A., Kisslinger, A. (2020). A failure mode and effect analysis (FMEA)-based approach for risk assessment of scientific processes in non-regulated research laboratories. Accreditation and Quality Assurance, 25(5-6), 311-321. DOI: 10.1007/s00769-020-01441-9.
  • Mislan, Purba, H.H. (2020). Quality control of steel deformed bar product using Statistical Quality Control (SQC) and Failure Mode and Effect Analysis (FMEA). IOP Conference Series: Materials Science and Engineering, 1007(1). DOI: 10.1088/1757-899X/1007/1/012119.
  • Mittal, A., Gupta, P., Kumar, V., Al Owad, A., Mahlawat, S., Singh, S. (2023). The performance improvement analysis using Six Sigma DMAIC methodology: A case study on Indian manufacturing company. Heliyon, 9(3). DOI: 10.1016/j.heliyon.2023.e14625.
  • Nurcahyo, R., Faisal, Dachyar, M. (2018). Overall equipment effectiveness (OEE) at the laboratory of structure testing. Proceedings of the International Conference on Industrial Engineering and Operations Management, IEOM 2018, 1080-1090.
  • Nurprihatin, F., Angely, M., Tannady, H. (2019). Total productive maintenance policy to increase effectiveness and maintenance performance using overall equipment effectiveness. Journal of Applied Research on Industrial Engineering, 6(3), 184-199. DOI: 10.22105/jarie.2019.199037.1104.
  • Nurprihatin, F., Jayadi, E.L., Tannady, H. (2020). Comparing heuristic methods' performance for pure flow shop scheduling under certain and uncertain demand. Management and Production Engineering Review, 11(2), 50-61. DOI: 10.24425/mper.2020.133728.
  • Nurprihatin, F., Rembulan, F.D., Pratama, Y.D. (2022). Comparing probabilistic economic order quantity and periodic order quantity model performance under lumpy demand environment. Management and Production Engineering Review, 13(4), 16-25. DOI: 10.24425/mper.2022.142391.
  • Qin, J., Xi, Y., Pedrycz, W. (2020). Failure mode and effects analysis (FMEA) for risk assessment based on interval type-2 fuzzy evidential reasoning method. Applied Soft Computing, 89, 1-14. DOI: 10.1016/j.asoc.2020.106134.
  • Reynolds, M. S., Spencer, S.P., Dunaway, A., Buckingham, D., Bartman, T. (2021). Scientific approach to assess if change led to improvement - methods for statistical process control analysis in quality improvement. Journal of Emergency Nursing, 47(1), 198-205. DOI: 10.1016/j.jen.2020.09.002.
  • Sari, M. F., Darestani, S. A. (2019). Fuzzy overall equipment effectiveness and line performance measurement using artificial neural network. Journal of Quality in Maintenance Engineering, 25(2), 340-354. DOI: 10.1108/JQME-12-2017-0085.
  • Solikhah, P., Nusraningrum, D. (2022). Increasing production capacity of oil country tubular goods pipe using OEE methods. European Journal of Business and Management Research, 7(5), 9-14. DOI: 10.24018/ejbmr.2022.7.5.1612.
  • Stamatis, D.H. (2019). Risk management using failure mode and effect analysis. ASQ Quality Press.
  • Subin, Sudheer, S. (2019). Application of statistical quality control techniques in condom manufacturing industry. International Journal of Science and Research, 8(8), 1154-1162. DOI: 10.21275/ART2020375.
  • Subriadi, A.P., Najwa, N.F. (2020). The consistency analysis of failure mode and effect analysis (FMEA) in information technology risk assessment. Heliyon, 6(1). DOI: 10.1016/j.heliyon.2020.e03161.
  • Sutrisno, W., Fathiah, U., Sulistio, J. (2019). Six sigma application on cement packing quality control and analysis to reduce defect. IOP Conference Series: Materials Science and Engineering, 505(1). DOI: 10.1088/1757-899X/505/1/012064.
  • Syamsul, N.I., Amar, K., Bahri, S., Mansur, M.A. (2022). Proposed improvement of fajar daily newspaper products with a six sigma approach. Journal of Industrial Engineering Management, 7(2), 127-133. DOI: 10.33536/jiem.v7i2.1139.
  • Thakur, V., Akerele, O.A., Brake, N., Wiscombe, M., Broderick, S., Campbell, E., Randell, E. (2023). Use of a lean six sigma approach to investigate excessive quality control (QC) material use and resulting costs. Clinical Biochemistry, 112, 53-60. DOI: 10.1016/j.clinbiochem.2022.12.001.
  • Thiede, S. (2023). Advanced energy data analytics to predict machine overall equipment effectiveness (OEE): a synergetic approach to foster sustainable manufacturing. CIRP Life Cycle Engineering Conference, 116, 438-443. DOI: 10.1016/j.procir.2023.02.074.
  • Viharos, Z.J., Jakab, R. (2021). Reinforcement learning for statistical process control in manufacturing. Measurement, 182, 109616. DOI: 10.1016/j.measurement.2021.109616.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171673271

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.