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By Sumit Chakraborty

The elemental target is to increase an schooling process re-engineering roadmap via clever analytics.

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M; j ¼ 1; 2; . ; n; ð3:11Þ k¼1 l   X kk wkj wj ¼ IFWA w1j ; w2j ; . ; wlj ¼ k¼1 " ¼ 1À l  Y # l  k kk Y k k k 1 À lj ; vj ; k¼1 j ¼ 1; 2; . ; n; ð3:12Þ k¼1 À Á where aij ¼ lij ; vij is the group assessment of the l team members for FMi with À Á respect to RFj and wj ¼ lj ; vj is the group subjective weight of RFj of the l team members. Step 2. Determine the subjective weights of risk À factors Á Based on the group subjective weights wj ¼ lj ; vj ; determined by Eq. 12), the subjective weight of risk factor RFj can be normalized using Eq.

Expert Syst Appl 38(1):206–214 Chapter 4 FMEA Using Interval 2-Tuple Hybrid Weighted Distance Measure The interval 2-tuple linguistic representation method (Zhang 2012) is a useful computational model for computing with words, which has the capability of expressing different types of decision makers’ assessment information and has been widely used in many real-world engineering and management problems. Moreover, via this method, decision makers can express their preferences by the use of linguistic term sets with different granularity of uncertainty.

7, we can see that the ranking orders of FM2 and FM7, FM6, and FM8 are the same and FM5 is ranked behind FM1 when the fuzzy FMEA is applied. However, in the proposed method, FM2 and FM6 are successfully distinguished from FM7 and FM8, respectively. In addition, the results of the proposed method show that FM5 has a high priority compared to FM1. The main reasons for these differences may be as follows (Wang et al. 2009; Liu et al. 2013, 2014): (1) The fuzzy if–then rules with the same consequence but different antecedents are unable to be distinguished from one another by using fuzzy FMEA.

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