High performance drilling of T800 CFRP composites by combining ultrasonic vibration and optimized drill structure

Enhancing Cutting Efficiency and Minimizing Forces for Nomex Honeycomb Core Using Grey Relational Analysis and Desirability Function Analysis

Nomex Honeycomb core is the foundational building block for manufacturing aerospace composite components. Its usage requires machining honeycomb in complex aerodynamic profiles where the quality of the core is governed by accuracy and precision of cut profiles. The assessment of accuracy and precision is directly related to forces induced in the cutting tool and cutting efficiency. These two parameters form the basis of a multi-objective function that this paper aims to optimize for the milling operation. The parameter of depth of cut considered in this paper has not been analyzed in a multi-objective optimization study of the Nomex Honeycomb core previously. A Taguchi-based array of Design of Experiments followed by Analysis of Variance and correlation analysis is utilised. The results indicate that the most significant factor is the feed rate, with a percentage contribution of 72% for the cutting forces and depth of cut, with a percentage contribution of 85% in the case of cutting efficiency. The two parameters are optimized using Desirability Function Analysis and Grey Relational Analysis. The results are validated through experimental runs with an error within 5% of the statistical predictions, with the percentage improvement in cutting forces for optimum runs as compared to the worst experimental run at 47.8%. The percentage improvement in cutting efficiency likewise is 11%.

Characteristics of Carbon and Kevlar Fibres, Their Composites and Structural Applications in Civil Engineering-A Review

Kevlar and carbon fibres and fabrics have won a leading place in the structure market, although such materials are not cheap, and are increasingly used for reinforcing and strengthening structural elements in the civil engineering, automotive, aerospace and military industries, due to their superior mechanical properties, especially in terms of strength. The mechanical characteristics of such composite materials must be known in order to numerically simulate the mechanical behaviour of such structures in terms of the distribution of stresses and strains. It has also become a necessity to understand the effects of reinforcement with both types of fibres (carbon fibres and Kevlar fibres) on the mechanical properties, especially on the impact properties of such composites. This review aims to expose the main advantages and disadvantages of the hybridization of carbon and Kevlar fibres. For this reason, an overview is presented concerning the main characteristics (tensile strength, flexural strength, impact strength, coefficient of thermal expansion and so on) for carbon and Kevlar fibres and also for hybrid Kevlar-carbon composite materials to aid in the design of such hybrid composite materials. Finally, some civil construction rehabilitation and consolidation applications of the composites reinforced with carbon fibre, Kevlar fibre or with hybrid Kevlar-carbon fabrics are highlighted in the last part of the paper.

Machine Learning Models in Drilling of Different Types of Glass-Fiber-Reinforced Polymer Composites

The aim of the research presented in this paper was to simulate the relationship between selected technological drilling parameters (cutting speed, vc, and feed per tooth, fz) and cutting forces and the delamination in machining of a new glass-fiber-reinforced polymer (GFRP) composite. Four different types of new materials were manufactured with the use of a specially designed pressing device and differed in the fiber type (plain and twill woven materials) and weight fraction (wf) ratio, but they had the same number of layers and the same stacking sequence. A vertical machining center Avia VMC800HS was used for drilling holes with a two-edge carbide diamond coated drill. Measurements of the cutting force Fz in the drilling process conducted with variable technological parameters were carried out on a special test stand, 9257B, from Kistler. The new ink penetration method, involving covering the drilled hole surface with a colored liquid that spreads over the inner surface of the hole showing damage, was used to determine the delamination area. The cause-and-effect relationship between the drilling parameters was simulated with the use of five machine learning (ML) regression models (Linear Regression; Decision Tree Regressor; Decision Tree Regressor with Ada Boost; XGBRF Regressor; Gradient Boosting Regressor). Gradient Boosting Regressor results showed that the feed per tooth had the greatest impact on delamination-the higher the feed was, the greater the delamination became. Push-out delamination factors had higher values for materials that were made of plain woven fibers. The lowest amplitude of the cutting force component Fz was obtained for the lowest tested feed per tooth of 0.04 mm for all tested materials, with the lowest values obtained for the materials with twill fibers.