Indian Journal of Science and Technology

Open Access Open Access  Restricted Access Subscription Access

Risk Analysis and Mitigation using SCOR-Fuzzy ANP


Affiliations
1 Agro-industrial Technology Department, Brawijaya University, Malang, Indonesia
 

Objective: To identify the supply risk and determine the mitigation strategies that can be applied. Methods: The first method used to analyze risk is SCOR, then risk assessment with fuzzy-FMEA method. The method which can be used is to analyze the risk weight by using Fuzzy method, then selected 80% of the risk that has the highest weight. Furthermore, the data is used to formulate risk mitigation strategy using Fuzzy ANP method. Results: The results of the study showed 80% risk with the highest weight. The results of this research found that the highest risk in the cultivation department is the risk of procedural errors in the process of manufacturing, maintenance or cultivation. While the highest risk for the manufacturing department is the risk of experiencing delays in the supply of mushrooms. Alternative strategies for supply risk mitigation on the part of the cultivation department such as consistent Standard operate procedure OP implementation strategies, timely pickup, and optimization of transportation availability, improvement and improvement of nursery planning. Alternative strategies for supply risk mitigation on the part of manufacturing such as increased communications and inter-division coordination, improved raw material fulfillment, increasing SOP tuning frequency, improvements and optimization of machine. Application: It is concluded that fuzzy FMEA can be used to analysis risk supply accurately and fuzzy ANP can formulate the risk mitigation strategy to support supply performance of high quality and high value selling canned mushroom products.
User

  • Jirawttinunt S, Imsuwan T. The Effect of export marketing adaptation strategy and competitiveness of food product business in Thailand, International Journal of Strategic Management. 2014; 14(2):37−48. Crossref.

  • Coulter M. Strategic Management in Action, 2nd edition. Prentice Hall. New Jersey; 2002.

  • Supply Chain Council Team. Supply Chain Operation Reference Model Version 8.0. Supply Chain Council, inc. USA; 2006. p. 1-976.

  • Wang Y, Chin P, Yang J. Risk Evaluation in failure mode and effect analysis using fuzzy weighted geometric mean, Expert System with Application. 2009; 36(2):1195−207. Crossref.

  • Kutlu A, Mehmet E. Fuzzy failure modes and effects analysis by using fuzzy tops is based fuzzy AHP, International Journal of Expert Systems with Applications. 2012; 39(1):61−67. Crossref.

  • Saaty TL. Decision Making with Dependence and Feedback the Analytic Network Process. RWS Publication. Pittsburgh;1996. p. 1−2.

  • Zhou X. Risk evaluation of dynamic alliance based on fuzzy analytic network process and fuzzy TOPSIS, Journal of Service Science and Management. 2012; 5(1):230−40. Crossref.

  • Taslicali AK, Ercan S. The analytic hierarchy and the analytic network processes in multi-criteria decision making: A comparative study, Journal of Aeronautics and Space Technologies. 2006; 2(4):55−65.

  • Sidarto. Konsep pengukuran kinerja supply chain management pada sistem manufacture dengan model Performance of Activity (POA) dan Supply Chain Operations Reference (SCOR), Jurnal Teknologi. 2008; 1(1):68−77.

  • Besterfield C, Besterfield GH, Besterfield BM. Total Quality Management. Pearson Education, Inc Indian National Congress. New Jersey; 2003. p. 1−115.

  • Chanamool T, Naenna. Fuzzy FMEA application to improve decision making process in an emergency departemen, Applied Soft Computing. 2016; 43:441−53. Crossref.

  • Hayati M, Abroshan MR. Risk Assessment Using Fuzzy FMEA (Case Study: Tehran Subway Tunneling Operations), Indian Journal of Science and Technology. 2017; 10(9):1−9. Crossref 1, 2.

  • Pillay A, Wang J. Modified failure mode and effects analysis using approximate reasoning, Reliability and System Safety. 2003; 79:69–85. Crossref.

  • Rachieru N, Belu AD. Constantin improvement of process mode and effect analysis using fuzzy logic, Applied Mechanism and Material. 2013; 37:822−26.

  • Saaty TL. The Analytical Hierarchy Process. McGraw-Hill. New York; 1980. p. 1−6.

  • Chang D. Extent Analysis and Synthetic Decision, Optimization Techniques and Application, World Scientific, Singapore. 1992; 1:352−55.

  • Chang DY. Applications of the extent analysis method on fuzzy AHP, European Journal of Operational Research. 1996; 95:649−55. Crossref.

  • Buyukozkan G. Cifci G. A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers, Expert Systems with Applications. 2012; 39(3):3000–11. Crossref.

  • Sadeghi A. The Application of Fuzzy group analytic network process to selection of best maintenance strategy - A case study in Mobarakeh Steel Company, Iran, Informatics. 2012; 62(1):1378−83.

  • Mascarenhas de FAV, Leite QE, Soares LGR, Moreira FV, Fontes dos SV. Standard operating procedure: Implementation, critical analysis, and validation in the Audiology Department at CESTEH/Fiocruz, CODAS Child of Deaf Adults. 2016 Dec; 28(6):739−44.

  • Wang Y, Hall IR. Edible ectomycorrhizal mushroom:challenges and achievements, Canadian Journal of Botany. 2004; 82(8):1063−73. Crossref.

  • Reinhold T, Kearney G. More passengers and reduced costs-The optimization of the Berlin public transport network, Journal of Public Transportation. 2008; 11(3):57−76. Crossref.

  • Straatsma G, Anyer F, Egli S. Species richness, abundance, and phenology of fungal fruit bodies over 21 years in a Swiss forest plot, Mycological Research. 2001; 105(5):515−23. Crossref.

  • Gammayani DA, Irham HN, Muhammad IR. Utilization of information and communication technology in coordination between the National Libraries with the provincial library, Record and Library Journal. 2015; 1(2):120−28. Crossref 1, 2.

  • Akter M, Haris U. Supply chain operation model in terms of raw material in Bangladesh apparel industry, International Journal of Textile Science. 2017; 6(2):43−48.

  • Moghaddam KS. Multi-objective preventive maintenance and replacement scheduling in a manufacturing system using goal programming, International Journal Production Economics. 2013; 146(2):704–16. Crossref.


Abstract Views: 189

PDF Views: 0




  • Risk Analysis and Mitigation using SCOR-Fuzzy ANP

Abstract Views: 189  |  PDF Views: 0

Authors

Yunika Nisa Afifa
Agro-industrial Technology Department, Brawijaya University, Malang, Indonesia
Imam Santoso
Agro-industrial Technology Department, Brawijaya University, Malang, Indonesia

Abstract


Objective: To identify the supply risk and determine the mitigation strategies that can be applied. Methods: The first method used to analyze risk is SCOR, then risk assessment with fuzzy-FMEA method. The method which can be used is to analyze the risk weight by using Fuzzy method, then selected 80% of the risk that has the highest weight. Furthermore, the data is used to formulate risk mitigation strategy using Fuzzy ANP method. Results: The results of the study showed 80% risk with the highest weight. The results of this research found that the highest risk in the cultivation department is the risk of procedural errors in the process of manufacturing, maintenance or cultivation. While the highest risk for the manufacturing department is the risk of experiencing delays in the supply of mushrooms. Alternative strategies for supply risk mitigation on the part of the cultivation department such as consistent Standard operate procedure OP implementation strategies, timely pickup, and optimization of transportation availability, improvement and improvement of nursery planning. Alternative strategies for supply risk mitigation on the part of manufacturing such as increased communications and inter-division coordination, improved raw material fulfillment, increasing SOP tuning frequency, improvements and optimization of machine. Application: It is concluded that fuzzy FMEA can be used to analysis risk supply accurately and fuzzy ANP can formulate the risk mitigation strategy to support supply performance of high quality and high value selling canned mushroom products.

References





DOI: https://doi.org/10.17485/ijst%2F2018%2Fv11i24%2F117978