Abstract
Product standardization has gained importance with the increase of customer demands and developments of technology. Products must be tested with measurement equipment to ensure quality standards. In quality management, the variability between products is targeted to be minimum. Products are produced at a target value with specific tolerance levels. Measurement equipment are used to confirm that the dimensions be in accordance with the required tolerance levels. The calibration of measurement equipment is crucial for acquiring certain measurements. The calibration process aims to minimize the measurement error by providing the accuracy of measurement equipment. The companies can carry out their calibration processes in the company structure for certain equipment. However, companies may need outsourcing for the calibration of complex equipment. This study includes a model to select the most appropriate calibration supplier by using the interval type-2 fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method. The proposed approach is presented with a case study for torque-limiting wrench calibration in an automotive company. In the case study, ten different evaluation criteria were determined from the decision-makers and the literature for the calibration suppliers’ evaluation and selection. Within the scope of these criteria, three alternative suppliers (A, B, and C) were evaluated and supplier C was selected as the most suitable calibration supplier.
Similar content being viewed by others
References
Amid A, Ghodsypour SH, O’Brien C (2006) Fuzzy multiobjective linear model for supplier selection in a supply chain. Int J Prod Econ 104:394–407. https://doi.org/10.1016/j.ijpe.2005.04.012
Awasthi A, Chauhan SS, Goyal SK (2010) A fuzzy multicriteria approach for evaluating environmental performance of suppliers. Int J Prod Econ 126:370–378. https://doi.org/10.1016/j.ijpe.2010.04.029
Banaeian N, Mobli H, Fahimnia B, Nielsen IE, Omid M (2018) Green supplier selection using fuzzy group decision making methods: a case study from the agri-food industry. Comput Oper Res 89:337–347. https://doi.org/10.1016/j.cor.2016.02.015
Behzadian M, Khanmohammadi Otaghsara S, Yazdani M, Ignatius J (2012) A state-of the-art survey of TOPSIS applications. Expert Syst Appl 39:13051–13069. https://doi.org/10.1016/j.eswa.2012.05.056
Boran FE, Genç S, Kurt M, Akay D (2009) A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Syst Appl 36:11363–11368. https://doi.org/10.1016/j.eswa.2009.03.039
Büyüközkan G, Çifçi G (2012) A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Syst Appl 39:3000–3011. https://doi.org/10.1016/j.eswa.2011.08.162
Chan FTS, Kumar N (2007) Global supplier development considering risk factors using fuzzy extended AHP-based approach. Omega 35:417–431. https://doi.org/10.1016/j.omega.2005.08.004
Chen C-T (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114:1–9. https://doi.org/10.1016/S0165-0114(97)00377-1
Chen S-M, Lee L-W (2010) Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Expert Syst Appl 37:2790–2798. https://doi.org/10.1016/j.eswa.2009.09.012
Chen C-T, Lin C-T, Huang S-F (2006) A fuzzy approach for supplier evaluation and selection in supply chain management. Int J Prod Econ 102:289–301. https://doi.org/10.1016/j.ijpe.2005.03.009
Erginel N, Gecer A (2016) Fuzzy multi-objective decision model for calibration supplier selection problem. Comput Ind Eng 102:166–174. https://doi.org/10.1016/j.cie.2016.10.017
Gecer A, Erginel N (2012) Determining the criteria and their importance level of calibration supplier selection. International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering 6:322–326
Hwang CL, Yoon K (1981) Multiple attributes decision making: methods and applications. Springer, Berlin, Heidelberg
Jain V, Sangaiah AK, Sakhuja S, Thoduka N, Aggarwal R (2018) Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry. Neural Comput & Applic 29:555–564. https://doi.org/10.1007/s00521-016-2533-z
Kahraman C, Öztayşi B, Uçal Sarı İ, Turanoğlu E (2014) Fuzzy analytic hierarchy process with interval type-2 fuzzy sets. Knowl-Based Syst 59:48–57. https://doi.org/10.1016/j.knosys.2014.02.001
Lee L-W, Chen S-M (2008a) A new method for fuzzy multiple attributes group decision-making based on the arithmetic operations of interval type-2 fuzzy sets. Mach Learn Cybern 2008 Int Conf 6:3084–3089. https://doi.org/10.1109/ICMLC.2008.4620938
Lee L-W, Chen S-M (2008b) Fuzzy multiple attributes group decision-making based on the extension of TOPSIS method and interval type-2 fuzzy sets. Mach Learn Cybern 2008 Int Conf 6:3260–3265. https://doi.org/10.1016/j.eswa.2009.09.012
Mendel JM, John RI, Liu F (2006) Interval type-2 fuzzy logic systems made simple. IEEE Trans Fuzzy Syst 14:808–821. https://doi.org/10.1109/TFUZZ.2006.879986
Nations U (2006) Role of measurement and calibration in the manufacture of products for the global market: a guide for small and medium-sized enterprises. Vienna
Parkouhi SV, Ghadikolaei AS (2017) A resilience approach for supplier selection: using fuzzy analytic network process and grey VIKOR techniques. J Clean Prod 161:431–451. https://doi.org/10.1016/j.jclepro.2017.04.175
Shaw K, Shankar R, Yadav SS, Thakur LS (2012) Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain. Expert Syst Appl 39:8182–8192. https://doi.org/10.1016/j.eswa.2012.01.149
Ucal Sari I, Kahraman C (2015) Interval type-2 fuzzy capital budgeting. Int J Fuzzy Syst 17:635–646. https://doi.org/10.1007/s40815-015-0040-5
Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning-I. Inf Sci 8:199–249. https://doi.org/10.1016/0020-0255(75)90036-5
Author information
Authors and Affiliations
Corresponding author
Additional information
This article is part of the Topical Collection on Geo-Resources-Earth-Environmental Sciences
Rights and permissions
About this article
Cite this article
Cengiz Toklu, M. Interval type-2 fuzzy TOPSIS method for calibration supplier selection problem: a case study in an automotive company. Arab J Geosci 11, 341 (2018). https://doi.org/10.1007/s12517-018-3707-z
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12517-018-3707-z