EFFECT OF WIRE-EDM CUTTING ON FATIGUE STRENGTH OF AZ61 MAGNESIUM ALLOY
Effect of wire electrical discharge machining (wire-EDM) cutting on fatigue strength of an extruded AZ61 magnesium alloy at room temperature was investigated. The surface condition of the samples after the wire-EDM cutting process is compared to the samples which have undergone careful polishing on their surfaces. A series of high cycle fatigue tests are performed on both the wireEDM as-cut and polished samples with constant amplitude stress at the frequency of 10 Hz. Fractographic analyses were conducted on the tested samples to identify the mechanism of fatigue fracture. The finding show that the fatigue limit of wireEDM as-cut specimen is 20 MPa lower as compared to smoothly polished specimens. Fatigue cracks are found to initiate and propagate to final failure from a cutting pit on the wire-EDM as-cut specimens.
The Influences of Fibre Parameters on the Tensile and Flexural Response of Lightweight Thermoplastic Kenaf Fibre Reinforced Metal Composites
ABSTRACT The increasing demand for high performance and lightweight materials has stimulated the development of alternative materials, namely fiber metal laminates (FMLs). FML is a sandwich structure which is formed by bonding the metallic layers with composite as core constituent using an adhesive agent. In this study, the mechanical behavior of FMLs with the core constituents of environmental friendly kenaf bast fiber reinforced polypropylene composites bonded with aluminum skin layers was investigated. The effects of fiber compositions (50, 60, and 70 wt.%), fiber lengths (30, 60, 90 mm), and alkali treatment on the mechanical responses of FML were investigated. The overall results revealed that the increase of fiber composition and fiber length reduces the mechanical strength of FML owing to the agglomeration of natural fibers when the fiber length exceeds the critical limit. However, the chemical treated kenaf bast fiber reinforced FML showed a significant enhancement of the mechanical properties in comparison to the non-treated fiber reinforced FML owing to the improved fiber-matrix adhesion level.
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.