Abstract
In the process of attaining high-end machines, control of machining systems via optimized machining parameters along with their transient responses is highly essential. By implementing system detection methodologies, a new methodology is proposed to introduce the best mathematical model, which subsumes the best FIT, fewer parameters, minimum MSE, and residuals amongst ARX and ARMAX models for an SBCNC-60 Machine to gratify the controller’s design requirement. From the CNC machine, the real-time measurement data samples are obtained for model detection; then, they are simulated with the aid of MATLAB. Here, for the study of Metal Removal Rate (MRR), the multiple inputs with the single-output system are utilized; similarly, for tuning operation, the Surface Roughness (SR) is measured; subsequently, the MRR is utilized for drilling operation on P8 (H-13, High-Speed-Steels) materials, which were detected by ARX and ARMAX for varying orders. To optimize the output MRR, the best-fit models were selected for control regarding the PID as well as FOPID controller; moreover, in the ‘3’ inputs’ SR, one input differs at a time whilst retaining the other 2 constants at their mid-levels. Better time-domain characteristics were obtained by the PSO tuned FOPID controlled ARX 331 model than the PSO-PID controller for MRR (tr = 6.86 s., Mp = 1.94%, ts = 8.93 s.) and SR (tr = 1.13 s., Mp = 2.47%, ts = 2.68 s.) in case of turning operation, the ARX 311 is the best-suited model for MRR (tr = 0.0818 s., Mp = 1.8%, ts = 2.78 s.) while running for drilling operation. A prominent effect of the varied cutting speed input variable was illustrated by these models; thus, affecting the output performance like MRR and SR for various operations performed during the machining process.
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27 March 2024
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s10878-024-01134-w
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Acknowledgements
Sh. Abnnesh Saxena WM (OFC)/Ministry of Defence provided technical support to the authors for turning and drilling operations at the Ordnance factory Kanpur (U.P), INDIA, and provided logistics support free of any conflicts of interest. The authors are happy to acknowledge his assistance.
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Saxena, A., Dubey, Y.M. & Kumar, M. RETRACTED ARTICLE: ARX and ARMAX modelling of SBCNC-60 machine for surface roughness and MRR with optimization of system response using PSO. J Comb Optim 45, 56 (2023). https://doi.org/10.1007/s10878-022-00983-7
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DOI: https://doi.org/10.1007/s10878-022-00983-7