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Numerical Investigation of Thermal Behavior of CNC Machine Tool and Its Effects on Dimensional Accuracy of Machined Parts

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Journal of Software Engineering and Applications 2024年第8期17卷 617-637页

作者： Erick Matezo-Ngoma Abderrazak El Ouafi ahmed chebak Computer Science and Engineering Department University of Quebec Rimouski Canada GTI Mohammed VI Polytechnic University Ben Guerir Morocco

The dimensional accuracy of machined parts is strongly influenced by the thermal behavior of machine tools (MT). Minimizing this influence represents a key objective for any modern manufacturing industry. Thermally induced positioning error compensation remains the most effective and practical method in this context. However, the efficiency of the compensation process depends on the quality of the model used to predict the thermal errors. The model should consistently reflect the relationships between temperature distribution in the MT structure and thermally induced positioning errors. A judicious choice of the number and location of temperature sensitive points to represent heat distribution is a key factor for robust thermal error modeling. Therefore, in this paper, the temperature sensitive points are selected following a structured thermomechanical analysis carried out to evaluate the effects of various temperature gradients on MT structure deformation intensity. The MT thermal behavior is first modeled using finite element method and validated by various experimentally measured temperature fields using temperature sensors and thermal imaging. MT Thermal behavior validation shows a maximum error of less than 10% when comparing the numerical estimations with the experimental results even under changing operation conditions. The numerical model is used through several series of simulations carried out using varied working condition to explore possible relationships between temperature distribution and thermal deformation characteristics to select the most appropriate temperature sensitive points that will be considered for building an empirical prediction model for thermal errors as function of MT thermal state. Validation tests achieved using an artificial neural network based simplified model confirmed the efficiency of the proposed temperature sensitive points allowing the prediction of the thermally induced errors with an accuracy greater than 90%.

关键词： CNC Machine Tool Dimensional Accuracy Thermal Errors Error Modelling Numerical Simulation Finite Element Method Artificial Neural Network Error Compensation

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Numerical Investigation of Laser Surface Hardening of AISI 4340 Using 3D FEM Model for Thermal Analysis of Different Laser Scanning Patterns

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Modeling and Numerical Simulation of Material Science 2020年第3期10卷 31-54页

作者： Baha Tarchoun Abderrazak El Ouafi ahmed chebak Department of Engineering University of Quebec at Rimouski Rimouski QC Canada

Laser surface hardening is becoming one of the most successful heat treatment processes for improving wear and fatigue properties of steel parts. In this process, the heating system parameters and the material properties have important effects on the achieved hardened surface characteristics. The control of these variables using predictive modeling strategies leads to the desired surface properties without following the fastidious trial and error method. However, when the dimensions of the surface to be treated are larger than the cross section of the laser beam, various laser scanning patterns can be used. Due to their effects on the hardened surface properties, the attributes of the selected scanning patterns become significant variables in the process. This paper presents numerical and experimental investigations of four scanning patterns for laser surface hardening of AISI 4340 steel. The investigations are based on exhaustive modelling and simulation efforts carried out using a 3D finite element thermal analysis and structured experimental study according to Taguchi method. The temperature distribution and the hardness profile attributes are used to evaluate the effects of heating parameters and patterns design parameters on the hardened surface characteristics. This is very useful for integrating the scanning patterns’ features in an efficient predictive modeling approach. A structured experimental design combined to improved statistical analysis tools is

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Experimental Investigation of Laser Surface Hardening of AISI 4340 Steel Using Different Laser Scanning Patterns

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Journal of Minerals and Materials Characterization and Engineering 2020年第2期8卷 9-26页

作者： Baha Tarchoun Abderrazak El Ouafi ahmed chebak Department of Engineering University of Quebec at Rimouski Rimouski Canada Innovation Lab for Operations Mohammed VI Polytechnic University Benguerir Morocco

Laser surface transformation hardening becomes one of the most modern processes used to improve fatigue and wear properties of steel surfaces. In this process, the material properties and the heating parameters are the factors that present the most significant effects on the hardened surface attributes. The control of these factors using predictive modeling approaches to achieve desired surface properties leads to conclusive results. However, when the dimensions of the surface to be treated are larger than the cross-section of the laser beam, various laser-scanning patterns are involved. This paper presents an experimental investigation of laser surface hardening of AISI 4340 steel using different laser scanning patterns. This investigation is based on a structured experimental design using the Taguchi method and improved statistical analysis tools. Experiments are carried out using a 3 kW Nd: YAG laser source in order to evaluate the effects of the heating parameters and patterns design parameters on the physical and geometrical characteristics of the hardened surface. Laser power, scanning speed and scanning patterns (linear, sinusoidal, triangular and trochoid) are the factors used to evaluate the hardened depth and the hardened width variations and to identify the possible relationship between these factors and the hardened zone attributes. Various statistical tools such as ANOVA, correlations analysis and response surfaces are applied in order to examine the effects of the experimental factors on the hardened surface characteristics. The results reveal that the scanning patterns do not modify the nature of the laser parameters’ effects on the hardened depth and the hardened width. But they can accentuate or reduce these effects depending on the type of the considered pattern. The results show also that the sinusoidal and the triangular patterns are relevant when a maximum hardened width with an acceptable hardened depth is desired.

关键词： Laser Surface Hardening Process Experimental Investigation Laser Scanning Patterns AISI 4340 Steel Hardness Profile Hardened Depth Hardened Width Design of Experiment Analysis of Variance

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Experimental Investigation of Laser Welding Process in Overlap Joint Configuration

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Journal of Materials Science and Chemical Engineering 2019年第3期7卷 16-31页

作者： Kamel Oussaid Abderrazak El Ouafi ahmed chebak Engineering Department University of Quebec at Rimouski Rimouski Canada

This paper presents an experimental investigation of laser overlap welding of low carbon galvanized steel. Based on a structured experimental design using the Taguchi method, the investigation is focused on the evaluation of various laser welding parameters effects on the welds quality. Welding experiments are conducted using a 3 kW Nd:YAG laser source. The selected laser welding parameters (laser power, welding speed, laser fiber diameter, gap between sheets and sheets thickness) are combined and used to evaluate the variation of three geometrical characteristics of the weld (penetration depth, bead width at the surface and bead width at the interface). Various improved statistical tools are used to analyze the effects of welding parameters on the variation of the weld quality and to identify the possible relationship between these parameters and the geometrical characteristics of the weld. The results reveal that the reached hardness values are similar for all the experimental tests and all welding parameters are relevant to the weld quality with a relative predominance of laser power and welding speed. The effect of the gap is relatively limited. The investigation results reveal also that there are many options to consider for building an efficient welds quality prediction model. Results achieved using an artificial neural network based simplified model provide an indication of the prediction model performances.

关键词： Laser Welding Nd:YAG Laser Source Low Carbon Galvanized Steel Taguchi Method Overlap Welding

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Scanning Based Induction Heating for AISI 4340 Steel Spline Shafts-3D Simulation and Experimental Validation

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Advances in Materials Physics and Chemistry 2017年第6期7卷 263-276页

作者： Habib Hammi Abderrazak El Ouafi Noureddine Barka ahmed chebak Mathematics Computer Science and Engineering Department University of Quebec at Rimouski Rimouski Canada

This paper presents an investigation of non-stationary induction heating process applied to AISI 4340 steel spline shafts based on 3D simulation and experimental validation. The study is based on the knowledge, concerning the form of correlations between various induction heating parameters and the final hardness profile, developed in the case of stationary induction heating. The proposed approach focuses on analyzing the effects of variation of frequency, power and especially scanning speed through an extensive 3D finite element method simulation, comprehensive sensitivity study and structured experimental efforts. Based on coupled electromagnetic and thermal fields analysis, the developed 3D model is used to estimate the temperature distribution and the hardness profile. Experimentations conducted on a commercial dual-frequency induction machine for AISI 4340 steel splines confirm the feasibility and the validity of the proposed modelling procedure. The 3D model validation reveals a great concordance between simulated and measured results, confirms that the model can effectively be used as framework for understanding the process and for assessing the effects of various parameters on the hardening process quality and performance and consequently leads to the most relevant variables to use in an eventual hardness profile prediction model.

关键词： Induction Heating Non-Stationary Induction Heating Spline Shafts Hardness Profile Temperature Distribution Finite Element Method Induction Heating Parameters Sensitivity Study Prediction Model

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