MULTIPLE REGRESSION AND COMMITTEE NEURAL NETWORK FORCE PREDICTION MODELS IN MILLING FRP

This work utilizes the mechanistic modeling approach for predicting cutting forces and simulating the milling process of fiber-reinforced polymers (FRP) with a straight cutting edge. Specific energy functions were developed by multiple regression analysis (MR) and committee neural network approximation (CN) of milling force data and a cutting model was developed based on these energies and the cutting geometry. It is shown that both MR and CN models are capable of predicting the cutting forces in milling of unidirectional and multidirectional composites. Model predictions were compared with experimental data and were found to be in good agreement over the entire range of fiber orientations from 0 to 180°. Furthermore, CN model predictions were found to greatly outperform MR model predictions.     

Hole Quality and Damage in Drilling Carbon/Epoxy Composites by Electrical Discharge Machining

This study investigates the material removal mechanisms and machining damage in drilling of carbon fiber epoxy composite by electrical discharge machining (EDM). Detailed investigation of the morphology of the machined surfaces and elemental analysis were conducted inside a scanning electron microscope. Machining damage was characterized by the extent of delamination, hole taper, and the average width of the heat-affected zone (HAZ). The effect of pulse-on time and gap current on machining damage was also investigated. It was found that material removal occurred mainly in the form of decomposition of the polymer matrix and thermally induced fracture of the carbon fibers. Vaporization of the carbon fibers due to spark and Joule heating is also a possible mechanism. The width of HAZ was found to be influenced the most by pulse-on time where the minimum HAZ occurred for intermediate pulse-on time. Furthermore, the width of HAZ and hole taper in EDM were found to be comparable to or less than those obtained by laser cutting.     

CO2 laser cut quality of 4130 steel

Samples of 4130 steel were cut on a CO₂ laser cutting system and the combined effects of power and feed rate on kerf width, surface roughness, striation frequency and the size of heat affected zone (HAZ) have been studied. Regression analysis was used to develop models that describe the effect of the independent process parameters on laser cut quality. For the range of operation conditions tested, it was observed that power had a major effect on kerf width and size of HAZ, while feed rate affects were secondary. On the other hand, surface roughness and striation frequency were affected most by feed rate. At low power levels, the smallest kerf width and HAZ are obtained and the effect of feed rate is moderate. Low feed rates gave good surface roughness and low striation frequency. For optimum cut quality, kerf width, HAZ and surface roughness are kept at a minimum. However, operating conditions that satisfy these requirements while maintaining high productivity could not be identified.     

MULTIPLE REGRESSION AND COMMITTEE NEURAL NETWORK FORCE PREDICTION MODELS IN MILLING FRP

This work utilizes the mechanistic modeling approach for predicting cutting forces and simulating the milling process of fiber-reinforced polymers (FRP) with a straight cutting edge. Specific energy functions were developed by multiple regression analysis (MR) and committee neural network approximation (CN) of milling force data and a cutting model was developed based on these energies and the cutting geometry. It is shown that both MR and CN models are capable of predicting the cutting forces in milling of unidirectional and multidirectional composites. Model predictions were compared with experimental data and were found to be in good agreement over the entire range of fiber orientations from 0 to 180°. Furthermore, CN model predictions were found to greatly outperform MR model predictions.     

Prediction of cutting forces in helical end milling fiber reinforced polymers

Machining of fiber reinforced composites is an important activity in the integration of these advanced materials into engineering applications. Machining damage due to excessive cutting forces may result in rejecting the composite components at the last stages of their production cycle. Therefore, the ability to predict the cutting forces is essential for selecting process parameters that would result in minimum machining damage. This work utilizes mechanistic modeling techniques for simulating the cutting of carbon fiber-reinforced polymers (CFRP) with a helical end mill. A methodology is developed for predicting the cutting forces by transforming specific cutting energies from orthogonal cutting to oblique cutting. It is shown that the method developed is capable of predicting the cutting forces in helical end milling of unidirectional and multidirectional composites and over the entire range of fiber orientations from 0° to 180°. This is a significant improvement over previous models that were only capable of addressing orthogonal cutting and/or a limited range of fiber orientations. Model predictions were compared with experimental data and were found to be in good agreement in cutting unidirectional laminate, but with lesser agreement in the case of a multidirectional laminate.     

Recent Advancements in Design Optimization of Lattice-Structured Materials

Metamaterials, also known as lattice-structured materials, imitate the multifunctionality of natural architects as tailoring their physical properties is associated with manipulating their microstructure. As the recent evolution of additive manufacturing enables the creation of intricate geometries with minimal material wastage, improving the design to manufacturing cycle of lattice structured materials has become one of the trending research areas. Triply periodic minimal surface (TPMS) and plate lattice materials are renowned for their exceptional mechanical behavior in lightweight applications. Apparently, several types of design optimization strategies are explored to maximize their performance for better biocompatibility and mechanical loading resistance. Some of these strategies include functional gradation and multimorphology hybridization that are comprehensively described in this review. Their benefits and drawbacks are highlighted with a focus on TPMS and plate lattice materials. The review anticipates the utilization of automated design exploration methods (i.e., topology optimization and data-driven methods) to further enhance the design optimization procedure of lattice structured materials.     

A study on tool wear of tungsten carbide cutters in edge trimming of CFRP

Journal of Mechanical Science and Technology - Carbon fiber reinforced polymer (CFRP) composites are widely used in the aerospace field because of their outstanding lightweight material...     

Evaluation of heat partition in machining CFRP using inverse method

An inverse heat conduction method was used to determine the energy balance at the cutting zone in edge trimming of carbon fiber-reinforced polymer composites. Three-dimensional transient heat conduction problem was modeled and solved independently in Abaqus for both the workpiece and cutting tool. Temperatures at specific locations were also measured during cutting using thermocouples and infrared thermography. Minimizing the difference between measured and calculated temperatures allowed the estimation of the heat flux applied in each problem. The total electric power consumed in machining was also measured. The heat partition was determined from the measured and calculated energies to be 0.07, 0.56 and 0.37 for the workpiece, tool and chips, respectively. The temperature distribution in the workpiece indicated that heat penetration is shallow due to poor thermal conductivity. It was also found that the extent of estimated machining thermal damage in the workpiece is within 0.35?mm below the machined surface.