A generalised approach on kerf geometry prediction during CO2 laser cut of PMMA thin plates using neural networks

This study presents an application of feedforward and backpropagation neural network (FFBP-NN) for predicting the kerf characteristics, i.e. the kerf width in three different distances from the surface (upper, middle and down) and kerf angle during laser cutting of 4 mm PMMA (polymethyl methacrylate) thin plates. Stand-off distance (SoD: 7, 8 and 9 mm), cutting speed (CS: 8, 13 and 18 mm/sec) and laser power (LP: 82.5, 90 and 97.5 W) are the studied parameters for low power CO2 laser cutting. A three-parameter three-level full factorial array has been used, and twenty-seven (33) cuts are performed. Subsequently, the upper, middle and down kerf widths (Wu, Wm and Wd) and the kerf angle (KA) were measured and analysed through ANOM (analysis of means), ANOVA (analysis of variances) and interaction plots. The statistical analysis highlighted that linear modelling is insufficient for the precise prediction of kerf characteristics. An FFBP-NN was developed, trained, validated and generalised for the accurate prediction of the kerf geometry. The FFBP-NN achieved an R-all value of 0.98, in contrast to the ANOVA linear models, which achieved Rsq values of about 0.86. According to the ANOM plots, the parameter values which optimize the KA resulting in positive values close to zero degrees were the 7 mm SoD, 8 mm/s CS and 97.5 W LP.

A generalised approach on kerf geometry prediction during CO2 laser cut of PMMA thin plates using neural networks

This study presents an application of feedforward and backpropagation neural network (FFBP-NN) for predicting the kerf characteristics, i.e. the kerf width in three different distances from the surface (upper, middle and down) and kerf angle during laser cutting of PMMA thin plates. Stand-off distance, cutting speed and beam power are the studied parameters for the case of low power CO2 laser cutting. A three-parameter three-level full factorial array has been used and twenty-seven (33) cuts were performed. Subsequently, the kerf width and angle were measured and analysed through ANOM, ANOVA and interaction plots. The statistical analysis highlighted that linear modeling is insufficient for the precise prediction of kerf characteristics. A FFBP-NN was developed, trained, validated and generalised for the accurate prediction of the kerf geometry. The FFBP-NN achieved an R-sq value of 0.98, in contrast to the ANOVA linear models which achieved a value of about 0.90.

Machinability of hybrid natural fiber reinforced composites with cellulose micro filler incorporation

In the current scenario, the applications of natural fibers are increasing enormously due to their biodegradability, low-density and better mechanical properties. This research explains the machining nature of pineapple (P) and flax (F) fibers by the incorporation of cellulose micro filler (CMF). These epoxy-based composites were manufactured using compression moulding. In the machining process using abrasive water jet machining (AWJM), lower kerf angle of 1.31° and surface roughness of 5.1 µm were observed in 30% PF/2% cellulose micro filler hybrid epoxy combination. Agglomeration at higher filler incorporation causes decrease in machinability of hybrid 30% PF. Pineapple and flax hybrid fibers with 30 and 35 wt % showed better machinability at 2 and 3% cellulose micro filler addition. Scanning electron microscopy analysis after machining process showed reduction in flush off and pullouts of fiber by improved compaction with the epoxy matrix due to filler addition.

Abrasive Jet Machining Performance of Vegetable Fiber Polyester Composite and its Modelling

In this research, exploration of Abrasive Water Jet Machining (AWJM) on polyester based Curaua/basalt hybrid composite was carried out. The composites were fabricated through resin transfer molding (RTM) at a ratio of 60-40 weight percentage of matrix and fiber respectively. Experimental runs were carried out based on L27 orthogonal array considering three parameters and three levels. Further, the effect of input parameter viz., water pressure, standoff distance and feed rate on the output responses viz., kerf angle (Ta) and surface roughness (Ra) were studied. From the investigation, it is observed that stand off distance contributes a maximum in determining the results of surface roughness and kerf angle

The Machinability of Steels by Abrasive Water Jet

Abrasive Water jet machining (AWJM) is a Non-Traditional manufacturing process, were the material is expelled from the workpiece by effect erosion of pressurized high-speed water stream mixed with high-speed abrasives. There are such a significant number of procedure parameters influence with nature of the machined surface can be done by AWJM. The process variables are, the cross speed, water driven weight, remain off separation, rough stream rate and kind of grating are significant. This measures in AWJM are Surface Roughness (SR, Rate of Material Removal (RMR), Kerf angle, cutting depth. At the past, the survive completed from different kinds of steel was inproved and investigated on AWJM research by identifying with execution estimates checking and procedure control and process factor advancement. In this paper, a study undergoes on AWJM about feature pattern regarding various types of steels.

Influence of AWJM Parameter on GFRP Reinforced Nylon-6 Composite

This research article is aiming to comprehend the cause of Abrasive Water Jet Machining (AWJM) parameter on kerf angle of the polymer based composites. Direct extrusion method is adopted to fabricate the Nylon 6 – GFRP composites. L27 OA design is followed to carry out to study the behaviour of AWJM parameter Kerf Angle (Ka). Three parameters with three levels are formulated; the selected parameters are pressure of the jet, standoff distance and feed rate and output is Ka. Taguchi optimization tool is used to locate the optimal combination of the AWJM parameter. The maximum pressure, low feed rate and standoff distance are the beneficial for reducing the kerf angle. ANOVA is also employed to determine the contribution of each process parameter on kerf angle and it is found that pressure combined with standoff distance plays important role in reducing the Ka followed by standoff distance and feed rate.

Performance Studies on Flax Fiber Reinforced Polymer Composites – An Effect on Fiber Orientation

The plant based nature fiber added as a reinforced material for so many structural applications. From this awareness of earlier research in this paper by changing orientation of fiber and the mechanical properties and machining performance of flax fiber evaluated. The preparation of composite polyester resin was used with varying layers of flax fibers. The hand layup technique was adopted to fabricate the composites. The main aim of this research is to find out the effect of the fiber orientation. Different fiber orientations were used like 0º, 30º, 45˚, 60˚, and 90˚. Mechanical properties, tensile and flexural strength and abrasive water jet machining also performed to study the kerf angle. It was found that 00 and 900 orientation exhibited the better performance.