Open Access
E3S Web Conf.
Volume 328, 2021
International Conference on Science and Technology (ICST 2021)
Article Number 05005
Number of page(s) 5
Section Material Theory, Modeling & Characterisation, System Manufacture, Dynamic System
Published online 06 December 2021
  1. Z. D. Cahyani, S. R. W. Pribadi, and I. Baihaqi, “Study the implementation of a Model House of Risk (HOR) for risk mitigation of delays in materials and Components Imported in the construction of new ships,” J. Tek. ITS, vol. 5, no. 2, pp. G52–G59, (2016). [Google Scholar]
  2. S. Nasution, Y. Arkeman, K. Soewardi, and T. Djatna, “Identification and Risk Evaluation Using Fuzzy Fmea On Shrimp Industrial Agriculture Supply Chain,” J. Ris. Ind., vol. 8, no. 2, pp. 135–146, (2014). [Google Scholar]
  3. G. Acharyulu, “Supply Chain Management Practices in Printing Industry,” Oper. Supply Chain Manag., vol. 7, no. 2, pp. 39–45, (2014). [Google Scholar]
  4. I. N. Pujawan and L. H. Geraldin, “House of risk: A model for proactive supply chain risk management,” Bus. Process Manag. J., vol. 15, no. 6, pp. 953–967, (2009). [CrossRef] [Google Scholar]
  5. B. R. Kristanto and N. L. P. Hariastuti, “Application of the Model House of Risk (Hor) for risk mitigation on Leather raw materials Supply Chain,” J. Ilm. Tek. Ind., vol. 13, no. 2, pp. 1–10, (2014). [Google Scholar]
  6. D. Anggrahini, P. D. Karningsih, and M. Sulistiyono, “Managing Quality Risk in a Frozen Shrimp Supply Chain: A Case Study,” Procedia Manuf., vol. 4, no. January, pp. 252–260, (2015). [CrossRef] [Google Scholar]
  7. A. Lokobal, “Managing Construction Risk Management In The Province Of Papua (Case Study: Sarmi Regency),” J. Media Eng., vol. 4, no. 2, pp. 109–118, (2014). [Google Scholar]
  8. R. S. Nugraheni, R. Yuniarti, and R. A. Sari, “The Analysis Of Supply Chain Risk On Ready To Drink (RTD) Product Using House Of Risk Method,” J. Eng. Manag. Ind. Syst., vol. 5, no. 1, pp. 1–17, (2017). [Google Scholar]
  9. M. Ulfah, M. maarif Syamsul, Sukardi, and S. Raharja, “Analysis and Improvement of Supply Chain Risk Management of Refined Sugar Using House of Risk Approach,” vol. 26, no. 1, pp. 87–103, (2016). [Google Scholar]
  10. Standard, Australian New Zealand AS/NZS 4360:2004, “Risk management,” (2004). [Google Scholar]
  11. M. N. Masri, D. Satiti, and A. Rusdiansyah, “Identifying research advancements in supply chain risk management for Agri-food Industries: Literature review,” in Materials Science and Engineering, (2017), pp. 1–8. [Google Scholar]
  12. 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,” (2018), vol. 1097, pp. 1–4. [Google Scholar]
  13. I. D. Handayani, “A Review: The Potential Risk In Supply Chain Risk Management,” Spektrum Ind., vol. 14, no. 1, pp. 1–18, (2016). [CrossRef] [Google Scholar]
  14. P. Ceryno and L. Scavarda, “Supply Chain Risk Management: A Fishbone Analysis Approach,” Int. J. Ind. Eng. Manag., vol. 4, no. 3, pp. 141–149, (2013). [Google Scholar]
  15. D. L. Trenggonowati, “Analysis Of Causes Of Risks And Risk Mitigation By Using Methods Of Risk In The Procurement Division,” Ind. Serv., vol. 3, no. 1, pp. 1–7, (2017). [Google Scholar]
  16. T. S. Parsana and M. T. Patel, “A Case Study: A Process FMEA Tool to Enhance Quality and Efficiency of Manufacturing Industry,” Bonfring Int. J. Ind. Eng. Manag. Sci., vol. 4, no. 3, pp. 145–152, (2014). [Google Scholar]
  17. S. M. Muzakkir, K. P. Lijesh, and H. Hirani, “Failure mode and effect analysis of Bearing,” Int. J. Appl. Eng. Res., vol. 10, no. 16, pp. 37752–37759, (2015). [Google Scholar]
  18. J. Doshi and D. Desai, “Application of failure mode & effect analysis (FMEA) for continuous quality improvement -multiple case studies in automobile SMEs,” Int. J. Qual. Res., vol. 11, no. 2, pp. 345–360, (2017). [Google Scholar]
  19. D. Premkumar and M. Balamurugan, “Implementation of Quality Function Deployment in Pump Industry,” Int. J. Innov. Res. Sci. Eng. Technol., vol. 3, no. 3, pp. 1258–1262, (2014). [Google Scholar]
  20. N. Muda and R. S. N. Mat, “A Quality Function Deployment (QFD) Approach in Determining the Employer’ s Selection Criteria,” Ind. Eng., vol. 2015, no. 1, pp. 1–10, (2015). [Google Scholar]

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