The manufacturing industry is increasingly adopting non-traditional machining
(NTM) processes to meet the challenges posed by advanced engineering materials,
intricate geometries, and tight dimensional tolerances. Despite their advantages,
selecting and optimizing NTM processes is complex due to the presence of multiple,
often conflicting, performance criteria such as material removal rate, surface
integrity, tool wear, cost, and environmental impact, as well as numerous controllable
process parameters. Multi-criteria decision-making (MCDM) techniques offer
systematic and quantitative frameworks to evaluate, compare, and optimize such
processes under competing objectives. This review provides a comprehensive
examination of recent developments in the application of MCDM approaches to
NTM, outlining the major evaluation criteria, widely used decision-making methods,
and their applications across various industrial domains. Additionally, it highlights
how MCDM contributes to process selection and parametric optimization when
combined with mathematical modeling, statistical methods, or artificial intelligence
tools. The paper concludes by identifying research gaps and suggesting promising
future directions for sustainable and intelligent NTM process optimization.