PRIORITIZATION OF FAILURE MODES IN FOOD LOGISTIC PROCESS WITH A FUZZY APPROACH

Year 2017, , 186 - 201, 30.06.2017

Yelda Ayrim Gulin Feryal Can

https://doi.org/10.17261/Pressacademia.2017.463

Abstract

Purpose- Food
logistics include food transfer activities that transport dry food, beverage
and canned products etc. at any time, to anywhere and without any damage by
transport companies using special equipment and expert staff support. Unless
the required sensitivity for food logistics interacting with human health is
not shown, it may result in situations that can damage human health and even
cause death. Accordingly, it is very important to determine the failures that
may arise from the beginning and to determine the risk levels related to these
failures and take precautions related to these failures. In this way, failure
costs and customer complaints that may occur after delivery can be reduced.

Methodology-
In this study, Failure Modes and Effects Analysis (FMEA) were used to
determine the failures that may be encountered in food logistics and the risk
levels associated with these failures. In this context considering
disadvantages of traditional FMEA, weights of the risk factors related to the
failure modes are determined by using Fuzzy DEMATEL (Decision Making Trial and
Evaluation Laboratory) and these failure modes are prioritized by implementing
Fuzzy WASPAS (Weighted Aggregated Sum Product Assessment). In addition, for
identifying the consistency of failure modes ranking, comparison study is
realized.

Findings- As a result
of the study, it is determined that to perform regular maintenance and
calibration of vehicle coolers failure mode has the first priority. Also, as a
result of the comparison analysis, it is proved by the Sperman Rank Correlation
Coefficient values that the proposed approach can produce consistent results.

Conclusion- In real
life, the transportation of foods in the condition that will not threaten human
health and provide required environmental conditions has a great importance in
the food logistics. Among these conditions the fact that, the unsuitable
environment temperature for the transported food is one of the most important
problems in terms of deterioration of sensitive foods. Degraded food during
transport will bring health problems when they are consumed by people and will
cause high cost of products and loss of customers for the logistics firm.

Keywords

Multi criteria decision making, FMEA, food logistics, fuzzy DEMATEL, fuzzy WASPAS

References

• Abdelgawad M, Fayek AR (2010) Risk management in the construction industry using combined fuzzy FMEA and fuzzy AHP. J Constr Eng Manage 136(9):1028–1036.
• Aksakal E. ve Dağdeviren M. (2010), Anp Ve Dematel Yöntemleri İle Personel Seçimi Problemine Bütünleşik Bir Yaklaşım, Gazi Üniv. Müh. Mim. Fak. Der. Cilt 25, No 4, 905-913.
• Akyuz E., Celik E. (2015), A fuzzy DEMATEL method to evaluate critical operational hazards during gas freeing process in crude oil tankers, Journal of Loss Prevention in the Process Industries 38243e253.
• Allahverdi N. (2002). Uzman Sistemler Bir Yapay Zeka Uygulaması, Atlas Yayın Dağıtım, İstanbul
• Bitarafan, M., Zolfani, S. H., Arefi, S. L., Zavadskas, E. K., Mahmoudzadeh, A. (2014), Evaluatıon of real-tıme ıntellıgent sensors for structural health monıtorıng of brıdges based on swara-waspas; a case ın IRAN. Baltic Journal of Road & Bridge Engineering, 9(4),333-340.
• Chakraborty, S., Zavadskas, E. K. (2014), Applications of WASPAS method in manufacturing decision making. Informatica, 25(1), 1-20.
• Chakraborty, S., Zavadskas, E. K., Antucheviciene, J. (2015), Applications of WASPAS method as a multi-criteria decisionmaking tool. Economic Computation and Economic Cybernetics Studies and Research, 49(1) 5-22.
• Chang KH (2009) Evaluate the orderings of risk for failure problems using a more general RPN methodology. Microelectron Reliab 49(12):1586–1596.
• Chang, B.,Chang, C.W., Wu, C.H. (2011), “Fuzzy DEMATEL Method For Developing Supplier Selection Criteria”, Expert Systems With Applications, Volume 38, Issue 3, March 2011, 1850-1858.
• Emovon I, Norman RA, MA J, Pazouki K (2015) An integrated multicriteria decision making methodology using compromise solution methods for prioritising risk of marine machinery systems. Ocean Eng 105:92–103.
• Fontela, E., Gabus, A. (1974), “DEMATEL, innovative methods. Report no. 2 structural analysis of the world problematique”, Battelle Geneva Research Institute, 67-69.
• Li, C.W., Tzeng, G.H. (2009), “Identification of a threshold value for the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by a semiconductor intellectual property mall” Expert Systems with Applications, 36: 9891–9898.
• Li, D. F., Yang, J. B. (2004). Fuzzy Linear Programming Technique for Multiattribute Group Decision Making in Fuzzy Environments, Information Sciences, 158, p. 263-264.
• Rituparna C., Supahi M., D. Datta (2011), Arithmetic of Triangular Fuzzy Variable from Credibility Theory, International Journal of Energy, Information and Communications Vol. 2, Issue 3.
• Šaparauskas, J., Zavadskas, E. K., Turskis, Z. (2011), Selection of facade's alternatives of commercial and public buildings based on multiple criteria. International Journal of Strategic Property Management, 15(2), 189-203
• Tsai S., Chien M., Xue Y., Li L., Jiang X., Chen Q., Zhou J.,. Wang L. (2015), Using the Fuzzy DEMATEL to Determine Environmental Performance: A Case of Printed Circuit Board Industry in Taiwan. PLoS ONE 10(6): e0129153. doi:10.1371/journal.pone.0129153.
• Tseng M.L., Lin Y. H. (2008), “Application of fuzzy DEMATEL to develop a cause and effect model of municipal solid waste”, Environ Monit Assess, DOI 10.1007/s10661-008-0601-2.
• Turskis, Z., Zavadskas, E. K., Antucheviciene, J., Kosareva, N. (2015), A hybrid model based on fuzzy AHP and fuzzy WASPAS for construction site selection. International Journal of Computers Communications & Control, 10(6), 113-128.
• Vafaeipour, M., Zolfani, S. H., Varzandeh, M. H. M., Derakhti, A., & Eshkalag, M. K. (2014), Assessment of regions priority for implementation of solar projects in Iran: New application of a hybrid multi-criteria decision making approach. Energy Conversion and Management, 86, 653-663.
• Wu, W.W. (2012), “Segmenting Critical Factors For Successful Knowledge Management Implementation Using The Fuzzy DEMATEL Method”, Applied Soft Computing, Volume 12, Issue 1, Pages 527-535.
• Zadeh, L. A. (1965), Fuzzy Sets, Information and Control, 8, p.338-353.
• Zadeh, L. A. (1975), The Concept of a Linguistic Variable and its Application to Approximate Reasoning-I, Information Sciences, 8, p.199-249.
• Zavadskas, E.K., Turskis, Z., Antucheviciene, J., Zakarevicius, A. (2012). Optimization of Weighted Aggregated Sum Product Assessment. Elektronika ir Elektrotechnika – Electronics and Electrical Engineering, 122(6), 3–6.
• Zavadskas, E. K., Antucheviciene, J., Šaparauskas, J., Turskis, Z. (2013a), Multi-criteria assessment of facades’ alternatives: peculiarities of ranking methodology. Procedia Engineering, 57, 107-112.
• Zavadskas, E. K., Antucheviciene, J., Saparauskas, J., & Turskis, Z. (2013b), MCDM methods WASPAS and MULTIMOORA: verification of robustness of methods when assessing alternative solutions. Economic Computation and Economic Cybernetics Studies and Research, 47(2), 5-20.
• Zavadskas, E. K., Antucheviciene, J., Hajiagha, S. H. R., & Hashemi, S. S. (2014), Extension of weighted aggregated sum product assessment with interval-valued intuitionistic fuzzy numbers (WASPAS-IVIF). Applied Soft Computing, 24, 1013-1021.
• Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2015), Selecting a Contractor by Using a Novel Method forMultiple Attribute Analysis: Weighted Aggregated SumProduct Assessment with Grey Values (WASPAS-G)–Art. 02–Volume 24• Issue 2
• Zammori F, Gabbrielli R (2011) ANP/RPN: A multi criteria evaluation of the risk priority number. Qual Reliab Eng Int 28(1):85–104.
• Zolfani, S. H., Aghdaie, M. H., Derakhti, A., Zavadskas, E. K., Varzandeh, M. H. M. (2013), Decision making on business issues with foresight perspective; an application of new hybrid MCDM model in shopping mall locating. Expert systems with applications, 40(17), 7111-7121.