Table 1 Previous articles on the selection and optimisation of the WEDM process
S/No | Author(s) | Method | Solution approach |
|---|---|---|---|
1 | Raj and Prabhu [25] | Multivariate statistical techniques and multicriteria decision-making | Principal component analysis, grey relational analysis |
2 | Thankachan et al. [30] | Mathematical modeling | Response surface methodology |
3 | Majumder and Maity [17] | Artificial intelligence, multicriteria decision-making, fuzzy logic | GRNN, MOORA-fuzzy |
4 | Roy and Mandal [27] | Mathematical modeling | Response surface methodology |
5 | Karthik et al. [11] | Mathematical modeling | Taguchi method, ANOVA and TOPSIS |
6 | Das and Chakraborty [8] | Multicriteria decision making | Grey correlation-based TOPSIS |
7 | Okponyia and Oke [22] | Multicriteria decision making, mathematical modeling | EDAS-Taguchi, EDAS-Taguchi-Pareto |
8 | Chaudhari et al. [6] | Metaheuristics | Teaching learning-based optimisation algorithm, multi-objective teaching learning-based optimisation algorithm |
9 | Vakharia et al. [31] | Artificial intelligence and machine learning | Singular generative adversarial network, dense Net deep learning |
10 | Adedeji et al. [1] | Mathematical modeling and metaheuristics | Taguchi-Pareto, grey wolf algorithm, desirability function analysis |
11 | Ikedue et al. [10] | Mathematical modeling, metaheuristics, multicriteria decision making | AHP, Taguchi method and modified Taguchi methods, genetic algorithm |
12 | Ikedue and Oke [9] | Mathematical modeling | Taguchi, Taguchi Pareto, Taguchi-ABC methods |