A fuzzy enabled model for aggregative food safety risk assessment in food supply chains

The food industry is under pressure to improve food product safety, implement efficient risk management and rapid response capability, and manage quality ‘from farm to fork’. In this article, a new risk assessment approach is proposed to perform structured analysis of aggregative food safety risk in the food supply chain by using the concepts of fuzzy set theory and analytical hierarchy process. The novelty of this research lies in performing structured risk assessment and establishing an aggregative food safety risk indicator. It provides a single value representing the risk rating which can be effectively employed in incorporating the safety objectives into operations planning. It can function as a part of practical food safety management tool and help managers to understand how the risk changes and transfers in a supply chain. It will therefore improve food safety and quality through integrating the risk control with supply chain management.

[1]  Roberto Cigolini,et al.  A note on supply risk and inventory outsourcing , 2006 .

[2]  Alan Reilly,et al.  Prevention and control of hazards in seafood , 2000 .

[3]  Christopher S. Tang.  Robust strategies for mitigating supply chain disruptions , 2006 .

[4]  William H. Sperber.  Hazard identification: from a quantitative to a qualitative approach , 2001 .

[5]  Weiming Shen,et al.  Personal assistant agents for collaborative design environments , 2006, Comput. Ind..

[6]  W. Pedrycz,et al.  A fuzzy extension of Saaty's priority theory , 1983 .

[7]  H. Marks,et al.  Qualitative and quantitative risk assessment , 1999 .

[8]  S. Notermans,et al.  The use of quantitative risk assessment in HACCP , 2001 .

[9]  Huey-Ming Lee,et al.  Applying fuzzy set theory to evaluate the rate of aggregative risk in software development , 1996, Fuzzy Sets Syst..

[10]  Christopher S. Tang,et al.  The power of flexibility for mitigating supply chain risks , 2008 .

[11]  Tiaojun Xiao,et al.  Pricing, service level and lot size decisions of a supply chain with risk-averse retailers: implications to practitioners , 2009 .

[12]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[13]  D. Chang.  Applications of the extent analysis method on fuzzy AHP , 1996 .

[14]  Saadettin Erhan Kesen,et al.  A fuzzy AHP approach to personnel selection problem , 2009, Appl. Soft Comput..

[15]  John Sumner,et al.  A simple, spreadsheet-based, food safety risk assessment tool. , 2002, International journal of food microbiology.

[16]  T. Ross.  Fuzzy Logic with Engineering Applications , 1994 .

[17]  D J Parsons,et al.  A comparison of three modelling approaches for quantitative risk assessment using the case study of Salmonella spp. in poultry meat. , 2005, International journal of food microbiology.

[18]  Fritz Klocke,et al.  Evaluating alternative production cycles using the extended fuzzy AHP method , 1997, Eur. J. Oper. Res..

[19]  Isabel Walls,et al.  Role of quantitative risk assessment and food safety objectives in managing Listeria monocytogenes on ready-to-eat meats. , 2006, Meat science.

[20]  Ronald E. Giachetti,et al.  Analysis of the error in the standard approximation used for multiplication of triangular and trapezoidal fuzzy numbers and the development of a new approximation , 1997, Fuzzy Sets Syst..

[21]  Jennifer Blackhurst,et al.  A network-based decision tool to model uncertainty in supply chain operations , 2007 .

[22]  B. Ritchie,et al.  Supply chain risk management and performance: A guiding framework for future development , 2007 .

[23]  Ching-Gung Wen,et al.  River assimilative capacity analysis via fuzzy linear programming , 1996, Fuzzy Sets Syst..

[24]  Riitta Maijala,et al.  Trapping the food safety performance of a small or medium-sized food company using a risk-based model. The HYGRAM® system , 2003 .

[25]  Nicola Jones,et al.  An assessment of the value of documenting food safety in small and less developed catering businesses , 2002 .

[26]  M. R. Abdi,et al.  Fuzzy multi-criteria decision model for evaluating reconfigurable machines , 2009 .

[27]  Germaine H. Saad,et al.  Managing Disruption Risks in Supply Chains , 2005 .

[28]  D. Neiger,et al.  Supply chain risk identification with value-focused process engineering , 2009 .

[29]  Chongfu Huang.  Fuzzy risk assessment of urban natural hazards , 1996, Fuzzy Sets Syst..

[30]  Huey-Ming Lee,et al.  A new algorithm for applying fuzzy set theory to evaluate the rate of aggregative risk in software development , 2003, Inf. Sci..

[31]  Gordon H. Huang,et al.  An integrated fuzzy-stochastic modeling approach for risk assessment of groundwater contamination. , 2007, Journal of environmental management.

[32]  Uta Jüttner.  Supply chain risk management: Understanding the business requirements from a practitioner perspective , 2005 .

[33]  Pin-Yu Chu,et al.  A fuzzy AHP application in government-sponsored R&D project selection☆ , 2008 .

[34]  Seyed Hassan Ghodsypour,et al.  Vendor selection and order allocation using an integrated fuzzy case-based reasoning and mathematical programming model , 2009 .

[35]  Kevin McCormack,et al.  Supply Chain Risk in Turbulent Environments – A Conceptual Model for Managing Supply Chain Network Risk , 2009 .

[36]  Jennifer Blackhurst,et al.  A model for inbound supply risk analysis , 2006, Comput. Ind..

[37]  Dong Li,et al.  A Web-based tool and a heuristic method for cooperation of manufacturing supply chain decisions , 2001, J. Intell. Manuf..

[38]  Arun Kanda,et al.  Coordination in supply chains: an evaluation using fuzzy logic , 2007 .

[39]  Thomas L. Saaty,et al.  Models, Methods, Concepts & Applications of the Analytic Hierarchy Process , 2012 .

[40]  F. Chan,et al.  Global supplier development considering risk factors using fuzzy extended AHP-based approach , 2007 .

[41]  C. Kahraman,et al.  Multi‐criteria supplier selection using fuzzy AHP , 2003 .

[42]  Michio Sugeno,et al.  An introductory survey of fuzzy control , 1985, Inf. Sci..

[43]  Stephen J. Forsythe,et al.  Hazard analysis critical control point and prerequisite programme implementation in small and medium size food businesses , 2003 .

[44]  J. Buckley,et al.  Fuzzy hierarchical analysis , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

[45]  W. Zinn,et al.  Proactive planning for catastrophic events in supply chains , 2009 .

[46]  Prasanta Kumar Dey,et al.  Decision support system for inspection and maintenance: a case study of oil pipelines , 2004, IEEE Transactions on Engineering Management.

[47]  Tahir Husain,et al.  A fuzzy-based methodology for an aggregative environmental risk assessment: a case study of drilling waste , 2005, Environ. Model. Softw..

[48]  H M Marks,et al.  Topics in Microbial Risk Assessment: Dynamic Flow Tree Process , 1998, Risk analysis : an official publication of the Society for Risk Analysis.

[49]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[50]  Anna Nagurney,et al.  Supply chain networks, electronic commerce, and supply side and demand side risk , 2005, Eur. J. Oper. Res..

[51]  Xiaojun Wang,et al.  Optimisation of traceability and operations planning: an integrated model for perishable food production , 2009 .

[52]  Valerie J. Davidson,et al.  Fuzzy risk assessment tool for microbial hazards in food systems , 2006, Fuzzy Sets Syst..

[53]  Sebastian Martorell,et al.  Quantification of risks to consumers’ health and to company’s incomes due to failures in food safety , 2007 .

[54]  Xiao-Jun Zeng,et al.  Approximation theory of fuzzy systems-SISO case , 1994, IEEE Trans. Fuzzy Syst..

[55]  J A Serra,et al.  Risk assessment and critical control points from the production perspective. , 1999, International journal of food microbiology.