Identification and strategy for the risk mitigation of supply chain with Fuzzy House of Risk: A case study in pallet products
Abstract
X Corp. is a manufacturing company that produces various wood packaging products, including pallets, which are in high demand, particularly for export commodities. However, the company's supply chain activities are often affected by various risks. If these risks are not addressed in a timely manner, they could disrupt the supply chain and lead to negative consequences for the company. Therefore, the company management needs to implement supply chain risk management to identify and mitigate these risks. This study aims to identify the risks that have occurred or are likely to occur in the supply chain of X Corp. and determine which risks should be prioritized for mitigation. The fuzzy house of risk method was used to analyze the data. The results of the study identified 38 risk events and 22 risk agents. Additionally, 17 proactive actions were proposed to the company to address the priority risk agents and mitigate their potential impact.
Keywords
Full Text:
PDFReferences
I. N. Pujawan and M. Mahendrawathi, Supply Chain Management Edisi 3. Yogyakarta: Penerbit ANDI, 2017.
A. Gurtu and J. Johny, “Supply Chain Risk Management: Literature Review,” Risks, vol. 9, no. 1, p. 16, Jan. 2021, doi: 10.3390/risks9010016.
A. Wieland and C. M. Wallenburg, “Dealing with supply chain risks: Linking risk management practices and strategies to performance,” International Journal of Physical Distribution & Logistics Management, vol. 42, no. 10, pp. 887–905, 2012, doi: 10.1108/09600031211281411.
K. P. Scheibe and J. Blackhurst, “Supply chain disruption propagation: a systemic risk and normal accident theory perspective,” International Journal of Production Research, vol. 56, no. 1-2, pp. 43-59, 2018, doi: 10.1080/00207543.2017.1355123.
A. Ridwan, M. I. Santoso, P. F. Ferdinant, and R. Ankarini, “Design of strategic risk mitigation with supply chain risk management and cold chain system approach,” IOP Conference Series: Materials Science and Engineering, vol. 673, no. 1, p. 012088, Dec. 2019, doi: 10.1088/1757-899x/673/1/012088.
G. C. Dias, C. T. Hernandez, and U. R. de Oliveira, “Supply chain risk management and risk ranking in the automotive industry,” Gestão & Produção, vol. 27, no. 1, 2020, doi: 10.1590/0104-530x3800-20.
G. Baryannis, S. Validi, S. Dani, and G. Antoniou “Supply chain risk management and artificial intelligence: state of the art and future research directions,” International Journal of Production Research, vol. 57, no. 7, pp. 2179-2202, 2019, doi: 10.1080/00207543.2018.1530476.
F. Cagnin, M. C. Oliveira, A. T. Simon, A. L. Helleno, and M. P. Vendramini, “Proposal of a method for selecting suppliers considering risk management: An application at the automotive industry,” International Journal of Quality & Reliability Management, vol. 33, no. 4, pp. 488–498, 2014, doi: 10.1108/IJQRM-11-2014-0172.
T. C. E. Cheng, F. K. Yip, and A. C. L. Yeung, “Supply risk management via guanxi in the Chinese business context: The buyer’s perspective,” International Journal of Production Economics, vol. 139, no. 1, pp. 3–13, Sep. 2012, doi: 10.1016/j.ijpe.2011.03.017.
M. Asrol, M. Marimin, and M. Machfud, “Supply chain performance measurement and improvement for sugarcane agro-industry,” International Journal of Supply Chain Management, vol. 6, no. 3, pp. 8-21, 2017.
D. Yuliana, “Fuzzy Inference System Metode Mamdani Untuk Mengidentifikasi Jenis Alergi Pernafasan Secara Dini Pada Anak Usia 3-6 Tahun,” Jurnal Lentera ICT, vol. 5, no. 2, 2019.
W. A. Teniwut, “Challenges in reducing seaweed supply chain risks arising within and outside remote Islands in Indonesia: an integrated MCDM approach,” in Sustainability Modeling in Engineering, pp. 271-291, 2020, doi: 10.1142/9789813276338_0012.
R. Zhong, X. Xu, and L. Wang, "Food supply chain management: systems, implementations, and future research," Industrial Management & Data Systems, vol. 117, no. 9, pp. 2085-2114, 2017, doi: 10.1108/IMDS-09-2016-0391.
T. Immawan and D. K. Putri, ”House of risk approach for assessing supply chain risk management strategies: a case study in crumb rubber company Ltd.,” MATEC Web Conf, vol. 154, pp. 1–4, 2018, doi: 10.1051/matecconf/201815401097.
R. Astuti, R. L. R. Silalahi, and R. A. Rosyadi, “Risk mitigation strategy for mangosteen business using House of Risk (HOR) methods: (A case study in “Wijaya Buah”, Blitar District, Indonesia),” KnE Life Sciences, vol. 4, no. 2, pp. 17–27, 2017, doi: 10.18502/kls.v4i2.1653.
R. D. Lufika, P. D. Sentia, I. Ilyas, F. Erwan, A. Andriansyah, and A. Muthmainnah, “Risk Mitigation Design in the Production Process of Packaged Fruit Juice Drinks Using a Fuzzy Based House of Risk (HOR) Approach,” Jurnal Sistem Teknik Industri, vol. 24, no. 2, pp. 245-253, 2022.
C. Wan, X. Yan, D. Zhang, Z. Qu, and Z. Yang, “An advanced fuzzy Bayesian-based FMEA approach for assessing maritime supply chain risks”, Transportation Research Part E: Logistics and Transportation Review, vol. 125, pp. 222-240, 2019, doi: 10.1016/j.tre.2019.03.011.
A. Räsänen, H. Lein, D. Bird, and G. Setten, “Conceptualizing community in disaster risk management,” International Journal of Disaster Risk Reduction, vol. 45, p. 101485, May 2020, doi: 10.1016/j.ijdrr.2020.101485.
D. Kern, R. Moser, E. Hartmann, and M. Moder, "Supply risk management: model development and empirical analysis," International Journal of Physical Distribution & Logistics Management, vol. 42, no. 1, pp. 60-82, 2012, doi: 10.1108/09600031211202472.
H. L. Ma and W. H. C. Wong, “A-Fuzzy Based House of Risk Assessment Method For Manufacturers In Global Supply Chain,” Industrial Management & Data System, vol. 118, no. 7, pp. 1463-1476, 2018, doi: 10.1108/IMDS-10-2017-0467.
M. Ulfah, P. F. Ferdinant, D. L. Trenggonowati, and M. Salsabila, “Supply-chain risk mitigation with integration House of Risk and fuzzy logic: A case study in bakery industry,” Journal Industrial Servicess, vol. 8, no. 2, pp. 151-157, October 2022, doi: 10.36055/jiss.v8i2.17393.
D. L. Trenggonowati, M. Ulfah, F. Arina, and C. Lutifiah, “Analysis and strategy of supply chain risk mitigation using fuzzy failure mode and effect analysis (fuzzy FMEA) and fuzzy analytical hierarchy process (fuzzy AHP)”, IOP Conf. Series: Materials Science and Engineering, p. 909, 2020, doi: 10.1088/1757-899X/909/1/012085.
N. Pujawan and L. H. Geraldin, "House of risk: a model for proactive supply chain risk management," Business Process Management Journal, vol. 15, no. 6, pp. 953-967, 2009, doi: 10.1108/14637150911003801.
M. Cahya and E. Wulandari, “Risiko rantai pasok paprika pada anggota kelompok tani dewa family, Kabupaten Bandung Barat,” Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis, vol. 5, no. 2, pp. 252-275, Juli 2019, doi: 10.25157/ma.v5i2.2230.g2089.
A. Ridwan, K. Kulsum, and E. Sinurat, ” Integrasi lean six sigma, balanced scorecard, dan simulasi sistem dinamis dalam peningkatan kinerja supply chain. Journal Industrial Servicess, vol. 4, no. 2, 2019, doi: 10.36055/jiss.v4i2.5150.
M. Ulfah, D. L. Trenggonowati, and F. Zahra Yasmin, “Proposed supply chain risk mitigation strategy of chicken slaughterhouse PT X by house of risk method,” MATEC Web of Conferences, vol. 218, p. 04023, 2018, doi: 10.1051/matecconf/201821804023.
DOI: http://dx.doi.org/10.36055/jiss.v9i1.18953
Refbacks
- There are currently no refbacks.
is supported by