In this work, initially the chemical composition of Inconel 718 alloy sheet was obtained using X-ray fluorescence technique (XRF). The material properties such as yield strength, ultimate tensile strength, percentage of elongation, normal anisotropy, planar anisotropy, strain hardening exponent, and the strength coefficient were determined in longitudinal, diagonal, and transverse rolling direction using a uniaxial tensile test. The Limiting Dome Height (LDH) values are obtained by simulation and experimentation based on the hemispherical punch method. In simulation work, Barlat-89 yield criterion was used to obtain the Limiting Dome Height (LDH) values and strain distribution along with the specimen in Abaqus 6.1 software. The experimental LDH values of Inconel 718 alloy sheet and simulated results obtained from Abaqus 6.1 software were in close agreement. The approach presented in this work can be applied to obtain the LDH test values of interesting material focused by researchers. With the help of experiments, a limit curve was established which ensures the safe working region of Inconel 718 sheet. Scanning Electron Microscope (SEM) analysis of 100 &120 mm width specimens indicated smooth surface and ductile fracture. The examination of 140 &160 mm width specimens showed rough surface and shear-ductile failure. Energy Dispersive Spectrum (EDS) analysis of a fractured surface confirms the constituents of the sheet present before failure.
The deep drawing technique is an important metal forming processes, and it is rarely used in the Inconel 718 sheet. The main purpose of this study is to perform a deep drawing process using the Inconel 718 alloy. In this research article, the Inconel 718 alloy sheet of 1 mm thickness is drawn into sheet metal cups, and defects such as thinning, and earing are controlled using selected input parameters such as Blank Holding Force (BHF) Blank Diameter (BD), and Punch Nose Radius (Rpn). A Box Behnken design (BBD) is used to evaluate the effects of output parameters. The hybrid Deep Neural Network (DNN) is used to predict the experimental outcomes obtained from the deep drawing process. For deep drawing process blank holding force is favorable for both thinning and earing. The minimum thinning value obtained during experimentation is 0.033 mm. During experimentation less earing value is 2.47 mm. Hybrid Deep Neural Network based Sparrow Search Optimization (DNN-SSO) gives the prediction model, where the values are much closer to the experimented model than RSM and non-Hybrid DNN. The minimum thinning obtained in the prediction model such as RSM, SSO-DNN, and DNN are 0.030, 0.0304, and 0.023 mm. Likewise, the minimum earing obtained from the predictive model is 2.65, 2.49, and 2.51 mm respectively. The minimum error is found in the hybrid DNN and the average RMSE for thinning is 0.002 and earing is 0.0024. The regression coefficient of thinning and earing is 99% which proves the experimental outcomes matches with RSM validation.
Critical level of Fe in 15 different soils of Coimbatore was established through a green house experiment with Sorghum CSH.5 as test crop and six levels of Fe Viz. 0, 5, 10, 20, 40 and 80 ppm Fe through ferrous sulphate. The dry matter production of sorghum was significantly increased by the application of Fe at 5 and 10 ppm to the Fe deficient soils. D.T.P.A.-extractable Fe at 6.1 ppm was found to be critical level of Fe in calcareous soils of Coimbatore District in Tamil Nadu State with regard to sorghum crop
Automatic seed sowing machine are expensive and not affordable by small farmers in India. Traditional method of seed sowing practice causes muscular fatigue. It also leads to severe back ache. This paper focuses on the prototype development of manual cum automatic seed sowing machine at a minimum cost and to reduce the muscular fatigue associated with traditional method of seed sowing practice. The activities of this work include ideation, detail design, analysis and finally prototype development. In the ideation stage, solutions were sketched and finally best solution was selected using weighted matrix method. The detail design emphasis on the overall dimension and bill of materials for the proposed final model. The ergonomic analysis was performed in Catia V5 using Manikin and results indicated moderate risk. The cost estimation of the final product was presented. A minor variation of the developed prototype is recommended for commercialization.
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