Subsidence, when implant penetration induces failure of the vertebral body, occurs commonly after spinal reconstruction. Anterior lumbar interbody fusion (ALIF) cages may subside into the vertebral body and lead to kyphotic deformity. No previous studies have utilized an artificial neural network (ANN) for the design of a spinal interbody fusion cage. In this study, the neural network was applied after initiation from a Taguchi
Advanced manufacturing technology (AMT) provides advantages to manufacturing managers in terms of flexibility, quality, reduced delivery times, and global competitiveness. Although a large number of publications had presented the importance of this technology, only a few had delved into related literature review. Considering the importance of this technology and the recent contributions by various authors, the present paper conducts a more comprehensive review. Literature was reviewed in a way that will help researchers, academicians, and practitioners to take a closer look at the implementation, evaluation, and justification of the AMT. The authors reviewed various papers, proposed a different classification scheme, and identified certain gaps that will provide hints for further research in AMT management.
This paper deals with the contact stress, power loss, and pitting of spur gear tooth in altered tooth-sum gearing for a tooth-sum of 100 teeth when altered by±4% tooth-sum. Analytical and experimental methods were performed to investigate and compare the altered tooth-sum gearing against the standard tooth-sum gearing. The experiments were performed using a power recirculating type test rig. The tooth loads for the experimental investigations were determined considering the surface durability of gears. A clear picture of the surface damage was obtained using a scanning electron microphotograph. The negative alteration in the tooth-sum performed better than the positive alteration in a tooth-sum operating between specified center distances.
Through a pin-on-disc type wear setup, the dry sliding wear behavior of SiC-reinforced aluminum composites produced using the molten metal mixing method was investigated in this paper. Dry sliding wear tests were carried on SiC-reinforced metal matrix composites (MMCs) and its matrix alloy sliding against a steel counter face. Different contact stresses, reinforcement percentages, sliding distances, and sliding velocities were selected as the control variables, and the responses were selected as the wear volume loss (WVL) and coefficient of friction (COF) to evaluate the dry sliding performance. An L25 orthogonal array was employed for the experimental design. Initially, the optimization of the dry sliding performance of the SiC-reinforced MMCs was performed using grey relational analysis (GRA). Based on the GRA, the optimum level parameters for overall grey relational grade in terms of WVL and COF were identified. Analysis of variance was performed to determine the effect of individual factors on the overall grey relational grade. The results indicated that the sliding velocity was the most effective factor among the control parameters on dry sliding wear, followed by the reinforcement percentage, sliding distance, and contact stress. Finally, the wear surface morphology and wear mechanism of the composites were investigated through scanning electron microscopy.
Wire electrical discharge machining (WEDM) is a well known process for generating intricate and complex geometries in hard metal alloys and metal matrix composites with high precision. In present work, intricate machining of WC-5.3%Co composite on WEDM has been reported. Taguchi’s design of experiment has been utilised to investigate the process parameters for four machining characteristics namely material removal rate, surface roughness, angular error and radial overcut. In order to optimize the four machining characteristics simultaneously, grey relational analysis (GRA) coupled with entropy measurement method has been employed. Through GRA, grey relational grade has been computed as a performance index for predicting the optimal parameters setting for multi machining characteristics. Using Analysis of Variance (ANOVA) on grey relational grade, significant parameters affecting the multi-machining characteristics has been determined. Confirmatory results prove the potential of present approach.
This paper presents a crack identification method for start-up rotor based on the Hilbert-Huang transform (HHT). With this method, the instantaneous frequency (IF) of each intrinsic mode function is obtained through the Hilbert transform, and the spectrum of IF is calculated accordingly. The influence of acceleration and crack depth on the rotor is analyzed through experiments. HHT is employed to detect the shallower crack, and is then tested during the start-up process of the rotor. The results of the experiment show that HHT is a better tool for crack detection than fast Fourier transform.
In this paper, loxodromic-type normal circular-arc spiral bevel gear is proposed as a novel application of the circular-arc tooth profile at the gear transmission with intersecting axes. Based on the principle of molding-surface conjugation, the study develops a mathematical model for the tooth alignment curve and the computational flow at the design stage to enable the generation of the tooth surface. Machining of the tooth surface is then carried out to determine the interference-free tool path of the numerical control (NC). Moreover, a pair of loxodromic-type normal circular-arc spiral bevel gears is manufactured on computer numerical control (CNC) machine tools. The proposed theory and method are experimentally investigated, and the obtained results primarily reflect the superior performance of the proposed novel gear.
The dynamic mechanical characteristics of excessively heavy-duty cutting were analyzed based on the cutting experiments with 2.25Cr-1Mo-0.25V steel used in hydrogenated cylindrical shells. By investigating the influence of dynamic mechanical characteristics on the tools’ failure in limited heavy-duty cutting processes, the model of dynamic shearing force in the cutting area was established. However, the experimental results showed that the dynamic shear flow stress in the cutting area greatly influenced the tools’ fatigue. The heavy-duty cutting tool was damaged in the form of a shearing fracture. Through a comprehensive analysis of the theory, the critical condition of the tools’ fracture under extreme loading was established.