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Parameter design has been an effective technique for quality improvement. One of the goals of parameter design for a manufacturing process is to manipulate process parameters to produce an acceptable quality level for the desired quality characteristic. This research explores the concept of implementing parameter design for a turning process using fuzzy logic as an alternative approach for parameter design and quality control. A fuzzy logic controller (FLC) is proposed to manipulate process parameters to find the proper setting for the desired part quality. In this research, we focus on a turning process with surface finish as the desired quality characteristic. The proposed FLC manipulates the most influential parameter, feed rate, while holding other parameters constant to find the proper setting of the parameters necessary for the level of surface finish required by the part. The proposed FLC is found to be an effective method for implementing parameter design for a turning process. In addition, the FLC is shown to be a robust tool through its ability to handle two types of material and two different tool geometries.

In the modern world of competitive manufacturing, turning is a basic and important process that needs to be optimized for the fast-evolving industrial nature. It has its application in various fields involving numerous materials. This research study deals with modeling with optimization on the turning process parameters of turning E2-BS970 mild steel with cryogenically treated tungsten carbide tool under NFMQL having $\mathrm{\text{SiC}}+{\mathrm{\text{MoS}}}_2$ nanofluid. The parameters considered as the input factors are spindle speed and depth of cut along with feed rate and lubrication condition. The design of the experiment is done based on Box–Behnken design for 27 trials in the response surface method. The Deep Neural Network (DBN) and the Coot optimization algorithm are employed using MATLAB software for the prediction modeling. The prediction model developed by the DBN sigmoid function gave minimal error with prediction regression values of 0.99988 for MRR, 0.99516 for Cutting temperature, and 0.99545 for Tool life. The optimized result by CO shows a value of 188.89 rpm for spindle speed, 0.2318mm/rev for feed rate, Doc of 1.45mm, and 0.5015vol.% nanofluid MQL condition. The optimized values of MRR are 3.35mm³/min, $24.145^{\circ }$C cutting temperature, and 1543.12s of tool life. The DBN model combined with the Coot algorithm shows minimal deviation compared to the experimental results validation and confirmatory analysis and is deemed suitable for efficient prediction.

Nickel super alloys like Inconel 718 characterize a significant metal part in the structures of aircraft and engine components. The high reliability levels are the major conditions during the manufacturing of these essential structural components in aerospace production. Surface integrity is the most important factor considered for estimating the quality of machined surfaces in term of finishing as well as strongly effect on the corrosion behavior of the machined surface. In this study, three-dimensional (3D)-finite element (3D-FE) simulations were accomplished to determine induced residual stresses in machined Inconel 718 alloy. 3D simulations were executed in the sequential successive method using the design of experiments (DOEs) based on Taguchi L₉ technique. Subsequently, a veritable turning was implemented based on the selected Taguchi design to validate the simulation results. Also, the efficiency of independent parameters (cutting speed, feed rate, and depth of cut) on the surface integrity (surface roughness, microhardness, induced residual stresses), and corrosion rate of the machined surface were explored experimentally. Based on analysis of variance (ANOVA), it was obtained that the feed rate is the most relevant factor related to surface roughness and corrosion rate while cutting speed is the most relevant factor related to microhardness and induced residual stresses. The analyzed polarization curves confirmed that the reducing surface roughness and increasing induced compressive residual stresses are robustly related to enhancing the corrosion behavior of Inconel 718. Robust agreement was detected between the predicted and measured data. The optimal values of independent parameters that led to optimal surface integrity and minimum value of corrosion rate were found. Based on the revealed simulation results, the 3D-FE simulation of the turning process afforded consistent data as compared to experimental measurements for the wide range of induced residual stresses.

This paper explores the cutting force oscillations. Forces have been measured during the stainless steel turning. We provide the results of standard statistical analysis of the corresponding time series together with their recurrence properties. We claim that the system, which is initially in a regular vibration region for some fairly larger cutting depth, is unstable to chaotic oscillation appearance. This could have the important implication to the process control procedure.