A new approach to minimization of the surface roughness and cutting force via fuzzy TOPSIS, multi-objective grey design and RSA

Prediction of surface roughness in hard turning under high pressure coolant using Artificial Neural Network

“…Experimental investigation and mathematical analysis have been performed by the researchers to evaluate the contributions of factors on the machinability aspect, specifically on surface roughness. The prediction of surface roughness has been accomplished by using diverse techniques such as response surface method, artificial neural network, Taguchi method, fuzzy system [3][4][5].…”

Fuzzy model based surface roughness prediction of fine turning

“…The surface roughness minimization was carried out using fuzzy approach by Gok [8] for nodular cast iron. The so-called L 16 (3 4 ) Taguchi plan was used to define the experimental run, in which the three input cutting parameters were changed in four levels (v c =50-100-150-200 m/min; f=0.05-0.075-0.01-0.125 mm; a p = 0.5-1-1.5-2 mm).…”

“…For the representation the consequent sets belonging to the roughness parameters the Gauss-type membership functions were used, which can be defined by (8), the specific sets belonging to the outputs are illustrated in Figures. 9-10.…”

A Fuzzy-TOPSIS Method for Optimizing of Forging Problems

“…These problems along with their causes and effects are listed in table 1. Fuzzy-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is being adopted by many researchers for evaluating performance of different manufacturing processes like EDM (Electric discharge machining) [1,2,3], Laser drilling [4], Turning [5], Robust design [6], Milling [7], Welding [8], Product infant failure [9], Sustainable city logistic planning [10]. Organizations performance [11], Supplier evaluation and management [12,13], Group Dewangan et.al.…”