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This paper aims to conduct an economic and environmental machining procedure (dry condition) during face milling of the Polyoxymethylene Co-polymer. In this context, an experimental study based on Taguchi’s design was conducted to develop empirical models using Response Surface Methodology (RSM) on one hand and Support Vector Machine (SVM) for regression on the other hand. The ANalysis of VAriance (ANOVA) is conducted to determine the contribution and the significance of each cutting parameter on the surface quality and productivity (MRR). The obtained models are being compared to determine the most efficient approach. The last part is to find the optimum cutting combination by using Genetic Algorithm (GA) optimization based on SVM models, whether to minimize surface roughness Ra, or for composite objective to improve the quality and to increase the productivity. The results show that feed per tooth (fz) is the most affecting parameter on Ra followed by depth of cut (ap) and then the cutting velocity (Vc). SVM was more robust than RSM with less deviation error.

Computer simulation of industrial processes is an important alternative that may be used either to complement or to replace expensive experimental procedures associated with developing new parts or modifying existing process. For a metal cutting process, numerical simulations provide vital information about cutting forces, cutting temperatures, tooling and part distortion, etc. Since the early 1970s, FEA has been applied to simulate machining process. The development of this approach, its assumptions and techniques has been widely accepted. Nowadays, the manufacturing productivity even drives the community to the next level innovation through computer utilizations. A kinematic simulation of machining processes is one of many innovative CAE applications, especially beneficial to high volume production of automotive powertrain parts. In this paper, a generic force calculation method is introduced with a modified horsepower correction factor. An example of sizing milling force, milling paths and proper milling parameters is provided by utilizing the methodology. This paper will also discuss and propose how the manufacturing industry uses this resourceful tool. Applications of the methodology would empower product and manufacturing engineers to make intelligent and cost effective decisions.

In the automotive industry, sealing quality between two flat joint surfaces is directly affected by the surface flatness. To know how much flatness is caused by machining operations, a traditional trial-and-error method has been used. The prediction for machined surface error/distortion can help to assess the integrity of the structural design as well as develop fixturing scheme to optimize machining quality. In this paper, a finite element method is applied to extract the compliance matrix of milling surface of a workpiece, such as the cylinder deck face, and an encoding MatLab program is used to compute the flatness due to milling forces. The paper focuses on deriving analytical models for evaluating the flatness of the cylinder deck face and optimizing the manufacturing process. Some special considerations have been taken to manufacturing cutting force evaluations according to analysis results of the deck face flatness. Emphasis is also placed on the optimization of machining parameters by iterations of flatness results so that minimization of surface deformations under machining loads can be achieved. The methodology introduced in the paper is the closed-loop iteration by combining structural finite element analysis (FEA) simulation, tooling kinematic simulation, and MatLab data modeling.

Considering the production requirement of workpiece optimization in order to reduce mass, the dynamic behavior of a workpiece can be affected. This factor can influence the performance of the milling process due to the occurrence of chatter vibrations. On the other hand, when the recommended cutting speed is relatively low, the tool rubs against the workpiece surface causing process damping. Consequently, the process becomes more stable and hence the depth of cut can be increased. In this paper, the stability of face milling of a cantilever plate at low cutting speed is investigated. The stability lobes diagram is determined numerically considering process damping. Cutting tests are conducted in order to verify the simulated results. An accelerometer is attached to the workpiece and its signal is measured and analyzed. Both workpiece surface and roughness are also investigated. The experimental results show a good agreement with the stability lobes diagram to predict the stable region under process damping. Hence, the depth of cut can be considerably increased, keeping the process stable at low cutting speeds.