A Triangulation-Based Method for Complex Mold Parts Surface Wear Assessment

Song, Limei; Wang, Yulin; Wang, Hongyu; Sun, S.; Guo, Qinghua; Yang, Yangang; Zhu, Xinjun

doi:10.1109/jsen.2022.3188520

Cited by 4 publications

(1 citation statement)

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“…The surface topography after machining has a strong influence on fatigue strength and other tribological properties [ 36 , 37 , 38 ]. Depending on the type of treatment used, the properties of the surface topography may differ significantly despite similar values of the typical parameters describing surface roughness, such as Ra.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods

2022

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Precise machining of micro parts from difficult-to-cut materials requires using advanced technology such as wire electrical discharge machining (WEDM). In order to enhance the productivity of micro WEDM, the key role is understanding the influence of process parameters on the surface topography and the material’s removal rate (MRR). Furthermore, effective models which allow us to predict the influence of the parameters of micro-WEDM on the qualitative effects of the process are required. This paper influences the discharge energy, time interval, and wire speed on the surface topography’s properties, namely Sa, Sk, Spk, Svk, and MRR, after micro-WEDM of Inconel 718 were described. Developed RSM and ANN model of the micro-WEDM process, showing that the discharge energy had the main influence (over 70%) on the surface topography’s parameters. However, for MRR, the time interval was also significant. Furthermore, a reduction in wire speed can lead to a decrease in the cost process and have a positive influence on the environment and sustainability of the process. Evaluation of developed prediction models of micro-WEDM of Inconel 718 indicates that ANN had a lower value for the relative error compared with the RSM models and did not exceed 4%.

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Section: Introductionmentioning

confidence: 99%