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As a way of enhancing the mechanical properties of photopolymer‐based parts produced by layered manufacturing (LM) techniques, the use of short glass‐fibre reinforcements has been recently explored in the literature. This paper proposes a novel methodology that utilizes a modified rule‐of‐mixtures model for the prediction of the mechanical properties of such layered composites. The prediction process employs empirical data on (i) the fibre‐matrix interface, (ii) the fibres’ geometrical arrangement within the specimens (i.e. fibre‐orientation distribution), and (iii) the fibre‐length distribution. The effects of the fibre‐orientation and fibre‐length distributions are accounted for in the prediction model by the fibre‐length‐correction and orientation‐efficiency factors. Comparison of extensive experimental results and model‐based predictions of mechanical properties of layered composites demonstrated the effectiveness of the proposed estimation methodology.

3D printing of composites has a high degree of design freedom, which allows for the manufacture of complex shapes that cannot be achieved with conventional manufacturing processes. This paper aims to assess the design variables that might affect the mechanical properties of 3D-printed fibre-reinforced composites.

Markforged Mark-Two printers were used to manufacture samples using nylon 6 and carbon fibres. The effect of fibre volume fraction, fibre layer location and fibre orientation has been studied using three-point flexural testing.

The flexural strength and stiffness of the 3D-printed composites increased with increasing the fibre volume fraction. The flexural properties were altered by the position of the fibre layers. The highest strength and stiffness were observed with the reinforcement evenly distributed about the neutral axis of the sample. Moreover, unidirectional fibres provided the best flexural performance compared to the other orientations. 3D printed composites also showed various failure modes under bending loads.

Despite multiple studies available on 3D-printed composites, there does not seem to be a clear understanding and consensus on how the location of the fibre layers can affect the mechanical properties and printing versatility. Therefore, this study covered this design parameter and evaluated different locations in terms of mechanical properties and printing characteristics. This is to draw final conclusions on how 3D printing may be used to manufacture cost-effective, high-quality parts with excellent mechanical performance.

The purpose of this paper is to develop a mathematical model for surface roughness and delamination through response surface methodology (RSM) and analyse the influences of the entire individual input machining parameters (cutting speed, fibre orientation angle, depth of cut and feed rate) on the responses in milling of glass fibre reinforced plastics (GFRP) composites with solid carbide end mill cutter coated with PCD.

Four factors, five level central composites and a rotatable design matrix in response surface methodology were employed to carry out the experimental investigation. “Design Expert 8.0” software was used for regression and graphical analysis of the data were collected. The optimum values of the selected variables were obtained by solving the regression equation and by analyzing the response surface contour plots. Analysis of variance (ANOVA) was applied to check the validity of the model and for finding the significant parameters.

The developed second order response surface model was used to calculate the surface roughness and delamination of the machined surfaces at different cutting conditions with the chosen range with 95 per cent confidence intervals. Using such a model, remarkable savings in time and cost can be obtained.

The effect of fibre orientation during milling of GFRP laminates using RSM has not been previously attempted for analysis.

Composites 3D printing has the potential to replace the conventional manufacturing processes for engineering applications because it allows for the manufacturing of complex shapes with the possibility of reducing the manufacturing cost. This paper aims to analyse the performance of 3D printed fibre reinforced polymer composites to investigate the energy absorption capabilities and the residual properties before and after impact.

Various composites composed of carbon fibres and Kevlar fibres embedded into both Onyx and nylon matrix were printed using Markforged-Two 3D printers. Specimens with different fibre orientations and fibre volume fractions (Vf) were printed. A drop-weight impact test was performed at energies of 2, 5, 8 and 10 J. Flexural testing was performed to evaluate the flexural strength, flexural modulus and absorbed energy under bending (AEUB) before and after impact. Additionally, 3D printed carbon fibre composites were tested at two different temperatures to study their behaviour under room and sub-ambient temperatures. Failure modes were investigated using optical and high depth of field microscopes for all 3D printed composite samples.

Kevlar/nylon composites with a unidirectional lay-up and 50% Vf exhibited the most prominent results for AEUB at room temperature. The high-Vf carbon fibre composite showed the highest ultimate strength and modulus and performed best at both temperature regimes.

The work, findings and testing produced in this paper are entirely original with the objective to provide further understanding of 3D printed composites and its potential for use in many applications.

The purpose of this paper is to optimise the process parameters, namely, fibre orientation angle, helix angle, spindle speed, and feed rate in milling of glass fibre-reinforced plastic (GFRP) composites using grey relational analysis (GRA) and desirability function analysis (DFA).

In this work, experiments were carried out as per the Taguchi experimental design and an L27 orthogonal array was used to study the influence of various combinations of process parameters on surface roughness and delamination factor. As a dynamic approach, the multiple response optimisation was carried out using GRA and DFA for simultaneous evaluation. These two methods are best suited for multiple criteria evaluation and are also not much complicated.

The process parameters were found optimum at a fibre orientation angle of 15°, helix angle of 25°, spindle speed of 6,000 rpm, and a feed rate of 0.04 mm/rev. Analysis of variance was employed to classify the significant parameters affecting the responses. The results indicate that the fibre orientation angle is the most significant parameter preceded by helix angle, feed rate, and spindle speed for GFRP composites.

An attempt to optimise surface roughness and delamination factor together by combined approach of GRA and DFA has not been previously done.

This paper aims to study the comparison between a response surface methodology (RSM) and artificial neural network (ANN) in the modelling and prediction of surface roughness during endmilling of glass-fibre-reinforced polymer composites.

Aiming to achieve this goal, several milling experiments were performed with polycrystalline diamond inserts at different machining parameters, namely, feed rate, cutting speed, depth of cut and fibre orientation angle. Mathematical model is created using central composite face-centred second-order in RSM and the adequacy of the model was verified using analysis of variance. ANN model is created using the back propagation algorithm.

With regard to the machining test, it was observed that feed rate is the dominant parameter that affects the surface roughness, followed by the fibre orientation. The comparison results show that models provide accurate prediction of surface roughness in which ANN performs better than RSM.

The data predicted from ANN are very nearer to experimental results compared to RSM; therefore, this ANN model can be used to determine the surface roughness for various fibre-reinforced polymer composites and also for various machining parameters.

This contribution is focused on the relations between the fibre orientation and the air filtration properties. The fiber orientation is intended as the orientation of fibre to main stream or as the alignment of fibres each other. There are two reasons to study this problem. The relation between theoretical model and real filter and the possibility how to increase the filter quality due to fiber orientation.

The definitions of the filter characteristics, filter properties and the filtration mechanisms are noted and short view to velocity field is outlined.

The first examined model is the "cube" model where the same aligned fibrous object is oriented in different directions to the main stream. This model provides interesting information but some discrepancies too.

The second examined model compare the flat filters with different alignment of fibres each other. It seems that this parameter affect the filter properties markedly.

Both models are examined in relation to the drop in pressure and the filter efficiency.

In milling process the surface roughness and delamination are the most important performance characteristics, which are influenced by many factors like fibre orientation angle, helix angle, feed rate and spindle speed. The selection of these parameters at optimum level plays a vital role in getting minimum surface roughness and delamination factor. The purpose of this paper is to present multi-objective optimisation of Computer Numerical Control milling parameters using Grey-Taguchi method to get minimum surface roughness and delamination factor in machining of glass fibre reinforced plastics (GFRP) composites used in automotive, aircraft and manufacture of space ships.

The experiments are designed and conducted based on Taguchi's L₂₇ orthogonal array by taking fibre orientation angle, helix angle, feed rate and spindle speed at three levels and responses are surface roughness and delamination factor. Taguchi's signal-to-noise (S/N) ratio are determined based on their performance characteristics. A Grey relation grade is obtained by using S/N ratio. Based on Grey relational grade value, optimum levels of parameters have been identified by using response table and response graph.

Optimum levels of parameters for GFRP composites have been identified by using response table and response graph and the significant contributions of controlling parameters are estimated using analysis of variance.

The combined effect of fibre orientation angle and helix angle during milling of GFRP composites using Grey relational analysis has not been previously attempted for analysis.

Tribology of the carbon‐fibre‐reinforced plastics has been investigated. The wear‐resistance of carbon‐fibre‐reinforced plastics was found to be much better than those of other plastics reinforced with fibres of glass and stainless steel and was affected by the fibre‐orientation relative to sliding. Law of mixture in the frictional coefficient of composite materials was deduced; a comparison of calculated values with experimental data showed good agreements. Wear‐resistance of the carbon‐fibre‐reinforced plastics against fretting was also examined; good wear‐resistance was obtained when sliding within a region about 30° from the carbon‐fibre axis.

Fibre-reinforced additive manufacturing (FRAM) with short and continuous fibres yields light and stiff parts and thus increasing industry acceptance. High material anisotropy and specific manufacturing constraints shift the focus towards design for AM (DfAM), particularly on toolpath strategies. Assessing the design-property-processing relations of infill patterns is fundamental to establishing design guidelines for FRAM.

Subject to the DfAM factors performance, economy and manufacturability, the efficacy of two conventional infill patterns (grid and concentric) was compared with two custom strategies derived from the medial axis transformation (MAT) and guided by the principal stresses (MPS). The recorded stiffness and strength, the required CPU and print time, and the degree of path undulation and effective fibre utilisation (minimum printable fibre length) associated with each pattern, served as assessment indices for different case studies. Moreover, the influence of material anisotropy was examined, and a stiffness-alignment index was introduced to predict a pattern’s performance.

The highest stiffnesses and strengths were recorded for the MPS infill, emphasising the need for tailoring print paths rather than using fixed patterns. In contrast to the grid infill, the concentric infill offered short print times and reasonable utilisation of continuous fibres. The MAT-based infill yielded an excellent compromise between the three DfAM factors and experimentally resulted in the best performance.

This constitutes the first comprehensive investigation into infill patterns under DfAM consideration for FRAM, facilitating design and processing choices.