The IoT applications in the agriculture industry are intertwined in many ways, creating a hybrid construct of traditional businesses with digital connectivity implementations. Strategic issues and principles on the assimilation of IoT solutions are prevail through time: investment costs, data interconnectivity, management and analysis, as well as data security. The agriculture industry is expected to be always alerted for the changes that may apply, with all the contemporary challenges and future directions responding to the situations, so it can reap the optimum use of the IoT connectivity.
The current work presents the development of cost model for tooling during high speed hard turning of AISI 4340 hardened steel using regression analysis. A set of experimental data using ceramic cutting tools, composed approximately of Al2O3 (70%) and TiC (30%) on AISI 4340 heat treated to a hardness of 60 HRC was obtained in the following design boundary: cutting speeds (175-325 m/min), feed rate (0.075-0.125 m/rev), negative rake angle (0 to -12) and depth of cut of (0.1-0.15) mm. The output data is used to develop a new model in predicting the tooling cost using in terms of cutting speed, feed rate, depth of cut and rake angle. Box Behnken Design was used in developing the model. Predictive regression model was found to be capable of good predictions the tooling cost within the boundary design.
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