ArticleScientific reports2026
A novel taguchi-ocra optimization framework for incremental sheet metal forming of miniature conical cups with multi-response validation and cross-geometry applicability.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Hybrid RSM-SF-AHP-fuzzy MARCOS approach for multi-response optimization of WAAM-fabricated Ni-SS bimetallics in face milling.Scientific reports · 2026Article
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Abstract
This study aims to optimize the incremental sheet metal forming (ISMF) process for conical miniature cups by simultaneously improving formability, dimensional accuracy, energy efficiency, and sustainability. An L9 Taguchi experimental design was employed to investigate four key process parameters: feed rate, forming depth, step size, and sheet material. Multiple performance responses, including wall angle, thickness reduction, surface roughness, forming time, springback, and power consumption, were evaluated. Operational Competitiveness Rating Analysis (OCRA) was integrated with the Taguchi approach to rank alternatives and identify the optimal parameter combination. The proposed framework was further validated through confirmation experiments, ANOVA, repeatability and reproducibility tests, sensitivity analysis with multiple MCDA methods, dimensional and surface quality assessment, cross-validation using different geometries, and a simplified use-phase life cycle assessment. The optimized condition (90 mm/min feed rate, 0.10 mm depth, 0.25 mm step size, and copper sheet) reduced forming time by 18.75%, power consumption by 56.25%, and per-part energy use and CO₂ emissions by about 64.5% compared with the non-optimized condition. Surface roughness and springback were also reduced, while dimensional accuracy and repeatability remained within acceptable limits. Cross-validation confirmed good transferability to cylindrical geometries, although moderate deviations were observed for prismatic parts. Overall, the study presents a robust Taguchi-OCRA-based decision framework for sustainable ISMF optimization.
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