Abdellatif Khamlichi

Multiple Regression Prediction Model for Cutting Forces in Turning Carbon-Reinforced PEEK CF30

Among the thermoplastic polymers available, the reinforced polyetheretherketone with 30% of carbon fibres (PEEK CF 30) demonstrates a particularly good combination of strength, rigidity, and hardness, which prove ideal for industrial applications. Considering these properties and potential areas of application, it is necessary to investigate the machining of PEEK CF30. In this study, response surface methodology was applied to predict the cutting forces in turning operations using TiN-coated cutting tools under dry conditions where the machining parameters are cutting speed ranges, feed rate, and depth of cut. For this study, the experiments have been conducted using full factorial design in the design of experiments (DOEs) on CNC turning machine. Based on statistical analysis, multiple quadratic regression model for cutting forces was derived with satisfactory 𝑅2-squared correlation. This model proved to be highly preferment for predicting cutting forces.

Optimizing the thermal properties of clutch facings

Abstract The tribological contact under sliding situation taking place in the friction surfaces during dry clutch engagement process is strongly affected by heat transfer occurring in the clutch system. Heat is produced due to dissipation mechanisms of mechanical work which is developed by the frictional forces acting in the contact paths yielding the interfacial temperature to increase. The magnitude of temperature rise depends to a large extent on the thermal properties of clutch facings fitting the friction disk. This paper gives a modeling of the thermal properties of general organic clutch facings which are manufactured according to the scatter wound procedure. Starting from the material formulation, the rule of mixtures approach is used to determine the local thermal properties for an elementary yarn segment embedded in a matrix shell taken to be a representative volume element. Then, estimates for the thermal properties of the whole facing are obtained through a homogenization technique where global averaging over the facing surface of the directional contributions set by these individual segments are performed. Optimization of the facing thermal properties is conducted after that with regard to material formulation of the clutch facings and key parameters of the fabrication process.

Multi-criteria Optimization Using Taguchi and Grey Relational Analysis in CNC Turning of PEEK CF30

The robust design of turning parameters is dealing with the optimization of surface roughness and cutting force in turning of reinforced polyetheretherketone (PEEK) with 30% of carbon fibers (PEEK CF30) using TiN-coated cutting tools. The selected turning parameters include the cutting speed, feed rate and depth of cut. Grey–Taguchi method is combining orthogonal array design of experiments with relational analysis, which enables the determination of the optimal combination of turning parameters with the multiple criteria. The basic aim of grey relational analysis is to find the grey relational grade, which can be used for the optimization conversion from a multi-criteria problem to a single objective problem. This study not only proposes a novel optimization technique, but also contributes the satisfactory solution for multiple CNC turning objectives with profound insight.

Fuzzy Logic-Based Modeling of Surface Roughness Parameters for CNC Turning of PEEK CF30 by TiN-Coated Cutting Tools

An important range of existing engineered industrial parts consists of plastic materials that are reinforced with carbon fibers. Due to their excellent mechanical and thermal properties, machined mechanical parts made from reinforced polyetheretherketone (PEEK) composite materials have become standard in many high-technology engineering fields such as aerospace, automotive, and electronics. There is however a crucial need to predict the machining criteria for reinforced PEEK composite materials in order to optimize their fabrication process. In this article, the process parameters including cutting speed, feed rate, and depth of cut are investigated. A fuzzy rule-based model was derived to predict the surface roughness parameters Ra and Rt, in dry turning of reinforced PEEK with 30% of carbon fibers using TiN-coated cutting tools. The model was identified using results of experiments carried out according to Taguchi method. Predictions of the fuzzy-based model were found to fit, very well, experimental data with a correlation coefficient as high as 99%.

Prediction of surface roughness in turning of PEEK cf30 by using an artificial neural network

Surface roughness parameters Ra and Rt are mostly used as an index to determine the surface finish quality in the process of machining. Because of the strong nonlinear character of relationships between the process inputs and outputs, it is difficult to accurately estimate roughness characteristics by using traditional modeling techniques. In this work, accurate prediction of the Ra and Rt values during machining of reinforced poly ether ether ketone (PEEK) CF30 with TiN coated tools is achieved. The modeling is performed by using artificial neural network approach to represent the complex relationships between cutting conditions and surface roughness parameters. The input cutting parameters include cutting speed, depth of cut and feed rate. The network was trained with pairs of inputs and outputs datasets generated by machining experimental results that were obtained according to a full factorial design of experiment table. Predictions of the ANN based model were found to fit experimental data very well with a correlation coefficient as high as 99%. Complementary results that were not used during derivation of the ANN model have enabled one to assess the validity of the obtained predictions.

Identification of crack characteristics in beams by using modal frequencies and inverse problem

Detection of cracks in mechanical components as early as possible enables monitoring structural health and scheduling efficiently the maintenance tasks such as replacing the critical parts just in time. Vibration analysis based techniques for crack detection have been largely considered in the framework of beam-like structures. This methodology relies essentially on the observed changes of beam frequencies and mode shapes induced by the presence of damage. In the present work, using an explicit analytical model assessing the effect of a crack on beam strain energy, the beam first resonance frequencies as they depend on a single crack defect characteristics were evaluated. The crack equations were obtained by means of fracture mechanics approach. Variations of the first beam frequencies and modes shapes were then related explicitly to the location and depth of the crack. Measuring the beam frequency changes and monitoring their variations can be used to perform identification of the crack defect parameters...

Buckling strength of axially compressed thin axisymmetric shells as affected by localized initial geometric imperfections

Abstract Buckling analysis of axially compressed cylindrical shells having one or two localized initial geometric imperfections was performed by using the finite element method. The imperfections of entering triangular form were assumed to be positioned symmetrically at the mid shell length. The buckling load was assessed in terms of shell aspect ratios, imperfection amplitude and wavelength, and the distance separating the imperfections. The obtained results have shown that amplitude and wavelength have major effects, particularly for short and thin shells. Two interacting imperfections were found to be more severe than a single imperfection, but the distance separating them has small influence.

Modelling of machining force components during turning of PEEK CF30 by TiN coated cutting tools using artificial intelligence

Machined mechanical parts made from reinforced polyetheretherketone (PEEK) composite materials have become standard in many high-technology engineering fields. Considering their properties and potential areas of application it is necessary to investigate the machining of reinforced PEEK composite with 30% of carbon fibre (PEEK CF30). In this study, dry turning tests were carried out on PEEK CF 30 specimens using TiN coated cutting tool. An L27 orthogonal array was used for tests. A fuzzy rule-based model is developed to predict the machining force components in turning of carbon fibre-reinforced polymer (CFRP) composites. Good agreement is observed between the predictive model results and the experimental values. The fuzzy rule-based model can be used effectively for predicting the machining force components in turning CFRP composites.

Grey-fuzzy optimisation model for multi performance in CNC turning processes

The reinforced polyetheretherketone with 30% of carbon fibres (PEEK-CF30) reveals a particularly good combination of strength, rigidity, and hardness, which prove ideal for industrial applications. Considering these properties and potential areas of application, it is necessary to investigate and optimise the machining of PEEK-CF30. The Grey-fuzzy logic based on orthogonal array for optimising the machining process with multi-response has been reported. An orthogonal array and Grey-fuzzy reasoning grade are applied to study the multi performance characteristics of the machining process. The machining parameters (cutting speed, feed rate and depth of cut) with considerations of multiple responses (roughness surface and cutting force) are effective. The experimental results using the optimal setting easily clarified that the abovementioned optimum procedure greatly improved the manufacturing process in this study.

Optimization of cutting parameters in CNC turning operation using Taguchi design of experiments

Abstract Non-reinforced and reinforced Poly-Ether-Ether-Ketone (PEEK) plastics have excellent mechanical and thermal properties. Machining is an efficient process that can be used to manufacture specific mechanical parts made from PEEK composites. Researchers have focused on improving the performance of machining operations with the aim of minimizing costs and improving quality of manufactured products, in order to get the best surface roughness and the minimum cutting force. The parameters evaluated are the cutting speed, the depth of cut and the feed rate. In this paper, the effect of the mentioned parameters on surface roughness and cutting force, in dry turning of reinforced PEEK with 30% of carbon fibers (PEEK CF30) using TiN coated cutting tools, is analyzed through using robust design techniques such as Taguchis design method, signal-to-noise (S/N) ratio and statistical analysis tools such as Pareto-ANOVA. The obtained results have shown that Taguchi method and Pareto ANOVA are suitable for optimi...