Supply Chain Risk Analysis With MAFMA Method Approach

Fatimah Fatimah, Indah Asmara, Sri Mutia, M Sayuti

Abstract


Palm oil mill is a palm oil and palm kernel processing industry which is a semi-finished product. The palm oil industry is currently growing rapidly in line with the demand for large quantities of CPO and Kernal and their derivatives. In its operation, it is always faced with various risks, from the field to the processing plant. These risks will cause losses to the factory, especially in the form of financial. From the results of field observations obtained 13 kinds of supply chain risks, namely damaged trucks, FFB not up to standard, damaged FFB, insufficient FFB, network error, FFB damaged in the sorting field, boiling problems, problematic polisyndrom, abnormal steem, abnormal processes. /stops, viber cyclone plugs and leaks pipe. Therefore, it is necessary to identify, measure and manage risks to reduce losses caused by supply chain risks. The method used in this study is the MAFMA (Multi Attribute Failure Mode Analysis) method. The MAFMA method is a development of the FMEA method. The results showed that the risk level value contained 4 critical risks on the part of the factory, namely FFB less with a risk level value of 0.096, FFB not according to standards with a risk level value of 0.085, network error with a risk level value of 0.083 and the process running abnormally. /stop with a risk level of 0.073. These 4 critical risks are the priority to be handled. The handling carried out is planning for the right FFB procurement, providing guidance on the harvesting process, stabilizing the network by providing copper rods and planning machine scheduling.

Keywords


Risk, Supply Chain, Multi Attribute Failure Mode Analysis, Failure Mode and Effect Analysis.

Full Text:

PDF

References


O. Lavastre, A. Gunasekaran, and A. Spalanzani, “Supply chain risk management in French companies,†Decis. Support Syst., vol. 52, no. 4, pp. 828–838, Mar. 2012, doi: 10.1016/j.dss.2011.11.017.

D. G. Hoffman, Managing Operational Risk: 20 Firmwide Best Practice Strategies. Wiley, 2002.

Y. K. Tse, M. Zhang, K. H. Tan, K. Pawar, and K. Fernandes, “Managing quality risk in supply chain to drive firm’s performance: The roles of control mechanisms,†J. Bus. Res., vol. 97, pp. 291–303, Apr. 2019, doi: 10.1016/j.jbusres.2018.01.029.

J. . Vaughan, Risk Management. New Jersey: John Wiley&Sons, Inc., 1997.

A. I. Pettersson and A. Segerstedt, “Measuring supply chain cost,†Int. J. Prod. Econ., vol. 143, no. 2, pp. 357–363, Jun. 2013, doi: 10.1016/j.ijpe.2012.03.012.

D. M. Lambert and M. C. Cooper, “Issues in Supply Chain Management,†Ind. Mark. Manag., vol. 29, no. 1, pp. 65–83, Jan. 2000, doi: 10.1016/S0019-8501(99)00113-3.

S. Samad et al., “Green Supply Chain Management practices and impact on firm performance: The moderating effect of collaborative capability,†Technol. Soc., vol. 67, p. 101766, Nov. 2021, doi: 10.1016/j.techsoc.2021.101766.

G. Li, H. Fan, P. K. C. Lee, and T. C. E. Cheng, “Joint supply chain risk management: An agency and collaboration perspective,†Int. J. Prod. Econ., vol. 164, pp. 83–94, Jun. 2015, doi: 10.1016/j.ijpe.2015.02.021.

M. Munir, M. S. S. Jajja, K. A. Chatha, and S. Farooq, “Supply chain risk management and operational performance: The enabling role of supply chain integration,†Int. J. Prod. Econ., vol. 227, p. 107667, Sep. 2020, doi: 10.1016/j.ijpe.2020.107667.

J. Hong, Y. Zhang, and M. Ding, “Sustainable supply chain management practices, supply chain dynamic capabilities, and enterprise performance,†J. Clean. Prod., vol. 172, pp. 3508–3519, Jan. 2018, doi: 10.1016/j.jclepro.2017.06.093.

R. K. Aslani, H. R. Feili, and H. Javanshir, “A hybrid of fuzzy FMEA-AHP to determine factors affecting alternator failure causes,†Manag. Sci. Lett., vol. 4, no. 9, pp. 1981–1984, 2014.

G. Cassanelli, G. Mura, F. Fantini, M. Vanzi, and B. Plano, “Failure Analysis-assisted FMEA,†Microelectron. Reliab., vol. 46, no. 9–11, pp. 1795–1799, Sep. 2006, doi: 10.1016/j.microrel.2006.07.072.

N. Xiao, H.-Z. Huang, Y. Li, L. He, and T. Jin, “Multiple failure modes analysis and weighted risk priority number evaluation in FMEA,†Eng. Fail. Anal., vol. 18, no. 4, pp. 1162–1170, Jun. 2011, doi: 10.1016/j.engfailanal.2011.02.004.

A. Hassan, M. R. A. Purnomo, and A. R. Anugerah, “Fuzzy-analytical-hierarchy process in failure mode and effect analysis (FMEA) to identify process failure in the warehouse of a cement industry,†J. Eng. Des. Technol., vol. 18, no. 2, pp. 378–388, Sep. 2019, doi: 10.1108/JEDT-05-2019-0131.

K.-S. Chin, Y.-M. Wang, G. Ka Kwai Poon, and J.-B. Yang, “Failure mode and effects analysis using a group-based evidential reasoning approach,†Comput. Oper. Res., vol. 36, no. 6, pp. 1768–1779, Jun. 2009, doi: 10.1016/j.cor.2008.05.002.

R. Fattahi and M. Khalilzadeh, “Risk evaluation using a novel hybrid method based on FMEA, extended MULTIMOORA, and AHP methods under fuzzy environment,†Saf. Sci., vol. 102, pp. 290–300, Feb. 2018, doi: 10.1016/j.ssci.2017.10.018.

O. Oktamianiza, D. Maisa Putra, Y. Yulia, A. Fahira, and A. Afridon, “Analysis of Differences in Tariff for Health Service Based on Sustability of Diagnosis on Admision and Summary Discharge Form with INA-CBGs Verification,†Int. J. Eng. Sci. Inf. Technol., vol. 1, no. 3, 2021, doi: 10.52088/ijesty.v1i3.114.

N. Khalil, S. N. Kamaruzzaman, and M. R. Baharum, “Ranking the indicators of building performance and the users’ risk via Analytical Hierarchy Process (AHP): Case of Malaysia,†Ecol. Indic., vol. 71, pp. 567–576, Dec. 2016, doi: 10.1016/j.ecolind.2016.07.032.

H. Li, H. Díaz, and C. Guedes Soares, “A failure analysis of floating offshore wind turbines using AHP-FMEA methodology,†Ocean Eng., vol. 234, p. 109261, Aug. 2021, doi: 10.1016/j.oceaneng.2021.109261.

M. Braglia, “MAFMA: multiâ€attribute failure mode analysis,†Int. J. Qual. Reliab. Manag., vol. 17, no. 9, pp. 1017–1033, Dec. 2000, doi: 10.1108/02656710010353885.

K.-H. Chang, “Generalized multi-attribute failure mode analysis,†Neurocomputing, vol. 175, pp. 90–100, Jan. 2016, doi: 10.1016/j.neucom.2015.10.039.




DOI: https://doi.org/10.52088/ijesty.v1i4.196

Article Metrics

Abstract view : 142 times
PDF - 90 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Fatimah Fatimah, Indah Asmara, Sri Mutia, M Sayuti

International Journal of Engineering, Science and Information Technology (IJESTY) eISSN 2775-2674