Research Article

Kaizen Selection for Continuous Improvement through VSM-Fuzzy-TOPSIS in Small-Scale Enterprises: An Indian Case Study

Table 5

Calculations for average fuzzy rating, normalized fuzzy rating, and weighted normalized fuzzy rating.

CriteriaKaizen eventsM1M2M3Aggregate fuzzy ratingNormalized fuzzy ratingWeighted normalized fuzzy rating

C1KE1G (5,7,9)VG(7,9,9)F(3,5,7)(3,7,9)(0.333,0.778,1.000)(1.000,5.446,9.000)

KE2G (5,7,9)F(3,5,7)VG(7,7,9)(3,6.33,9)(0.333,0.703,1.000)(1.000,4.449,9.000)

KE3F (3,5,7)P(1,3,5)G(5,7,9)(1,5,9)(0.111,0.556,1.000)(0.111,2.780,9.000)

C2KE1G (5,7,9)VG(7,9,9)F(3,5,7)(3,7,9)(0.333,0.778,1.000)(1.000,5.446,9.000)

KE2F(3,5,7)VG(7,9,9)VG(7,7,9)(3,7,9)(0.333,0.778,1.000)(1.000,5.446,9.000)

KE3F(3,5,7)F(3,5,7)G(5,7,9)(3,5.66,7)(0.333,0.628,0.778)(1.000,3.554,5.446)

C3KE1VG(7,9,9)VP(1,1,3)F(3,5,7)(1,5,9)(0.111,0.778,1.000)(0.111,3.890,9.000)

KE2F(3,5,7)F(3,5,7)VG(7,7,9)(3,5.66,9)(0.333,0.628,1.000)(1.000,3.554,9.000)

KE3F (3,5,7)F(3,5,7)F(3,5,7)(3,4.33,9)(0.333,0.481,1.000)(1.000,2.082,9.000)

C4KE1P (1,3,5)VG(7,9,9)F(3,5,7)(1,5.66,9)(0.111,0.628,1.000)(0.111,3.554,9.000)

KE2G (5,7,9)VP (1,3,5)G(3,5,7)(1,5,9)(0.111,0.556,1.000)(0.111,2.780,9.000)

KE3F (3,5,7)F (3,5,7)G(5,7,9)(3,5.66,9)(0.333,0.628,1.000)(1.000,3.554,9.000)

C5KE1G (5,7,9)G (5,7,9)F(3,5,7)(3,6.33,9)(0.333,0.703,1.000)(1.000,4.449,9.000)

KE2VG (7,9,9)G (5,7,9)F(3,5,7)(3,7,9)(0.333,0.778,1.000)(1.000,5.446,9.000)

KE3G (5,7,9)P(1,3,5)VG(7,7,9)(1,5.66,9)(0.111,0.628,1.000)(0.111,3.554,9.000)