ArticleMaterials (Basel, Switzerland)2026
The DD11 Material Components and Properties Impact and Relationship on Cutting Force in Progressive Stamping.
Article in Materials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Progressive stamping is a high-efficiency sheet metal forming method in the automotive and mass production industries, where material characteristics significantly influence process stability, cutting force, tool life, and final part quality. Herein, we report the effects of the chemical composition and mechanical properties of DD11 low-carbon steel on punching force during progressive stamping. Ten DD11 material batches with varying chemical compositions and mechanical properties were subjected to experimental investigation. Material characterization involved spectroscopic chemical analysis, tensile testing in accordance with ISO 6892-1, and hardness measurement. Punching tests were performed with a Zwick BZ2-MMAG100.SH01 universal testing machine that incorporates a punch-die assembly to study force-displacement behavior under controlled conditions. The cutting curves of these materials were analyzed to determine the maximum cutting and fracture loads, which were then statistically correlated with the materials' chemical and mechanical parameters. The results indicated that tensile strength and yield strength are the strongest statistically significant contributors to the maximum cutting load and the fracture point, and that the correlation coefficients for these measurements were +0.866 and +0.869, respectively. Carbon, chromium, and silicon showed the most positive effect on cutting resistance; whereas, titanium was negatively associated with each of the tested responses among chemical composition measures. But none of the chemical factors were statistically significant. The analysis also showed that material hardness yields the highest predictive performance for cutting force behavior (Pearson correlation coefficients up to 0.935 and a regression coefficient of R
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