Show source-provided references
14. Garcia, N., Puente, J., Fernandez, I., and Priore, P. (2018). Suitability of a consensual fuzzy inference system to evaluate suppliers of strategic products. Symmetry, 10.
10.3390/sym10010022 ↗17. Developing a supplier selection system through integrating fuzzy AHP and fuzzy DEA: a case study on an auto lighting system company in Taiwan
10.1080/09537280903458348 ↗27. Resilient supplier selection using AHP-TOPSIS-QFD under a fuzzy environment
28. A customer based supplier selection process that combines quality function deployment, the analytic network process and a Markov chain
10.1016/j.ejor.2017.06.006 ↗30. A multi-objective mathematical model integrating environmental concerns for supplier selection and order allocation based on fuzzy QFD in beverages industry
10.1016/j.eswa.2017.09.041 ↗32. A group decision model based on quality function deployment and hesitant fuzzy for selecting supply chain sustainability metrics
10.1016/j.jclepro.2018.02.197 ↗38. Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry
10.1016/j.cor.2016.02.015 ↗40. Feng, Y., Zhang, Z., Tian, G., Fathollahi-Fard, A.M., Hao, N., Li, Z., Wang, W., and Tan, J. (2019). A novel hybrid fuzzy grey TOPSIS method: Supplier evaluation of a collaborative manufacturing enterprise. Appl. Sci., 9.
10.3390/app9183770 ↗41. Green supplier selection using multi-criterion decision making under fuzzy environment: A case study in automotive industry
10.1016/j.cie.2019.07.038 ↗44. Assessment of supplier quality performance of computer manufacturing industry by using ANP and DEMATEL
10.1108/TQM-11-2012-0091 ↗45. A new extension to PROMETHEE under intuitionistic fuzzy environment for solving supplier selection problem with linguistic preferences
10.1016/j.asoc.2017.07.028 ↗48. The application of control chart for defects and defect clustering in IC manufacturing based on fuzzy theory
10.1016/j.eswa.2006.01.050 ↗50. Yang, C.M., Lin, K.P., and Chen, K.S. (2019). Confidence interval based fuzzy evaluation model for an integrated-circuit packaging molding process. Appl. Sci., 9.
10.3390/app9132623 ↗52. Using a QCAC–Entropy–TOPSIS approach to measure quality characteristics and rank improvement priorities for all substandard quality characteristics
10.1080/00207543.2013.865092 ↗53. Construction of closed interval for process capability indices Cpu, Cpl, and Spk based on Boole’s inequality and de Morgan’s laws
10.1080/00949655.2016.1182168 ↗55. Developing a performance index with a Poisson process and an exponential distribution for operations management and continuous improvement
10.1016/j.cam.2018.03.034 ↗57. Performance assessment of processing and delivery times for very large scale integration using process capability indices
10.1007/s001700200186 ↗