Assessment of Substrate and TBC Damage Effects on Resonance Frequencies for Blade Health Monitoring

The reliability of critical aircraft components continues to shift towards onboard monitoring to optimize maintenance scheduling, economy efficiency and safety. Therefore, the present study investigates changes in dynamic behavior of turbine blades for the detection of defects, with focus on substrate cracks and TBC spallation as they relate to vibration modes 1 to 6. Two‐dimensional and three-dimensional finite element simulation is used. The results indicate that TBC spallation reduces natural frequencies due to the ensuing hot spot and overall increase in temperature, leading to drops in blade stiffness and strength. Cracks cause even larger frequency shifts due to local plastic deformation at the crack that changes the energy dissipation behavior. Mode 1 vibration shows the largest shifts in natural frequencies that best correlate to the size of defects and their position. As such, it may be most appropriate for the early assessment of the severity and location of defects.

Optimization of DH Parameters of 6R Robotic Manipulator Using JAYA Approach

Manipulation of robots is carried out by the operators through a sequence of commands. However, the accuracy of the manipulation is still hindered due to parameter uncertainty. This results in less accurate robotic operations and hence affects the job performance. Due to measurement errors and sensor faults, the operation of robots malfunctions. Generally, errors are reduced with the use of high precision sensors and correcting hardware faults. However, corrections can also be made on a software platform to handle the correction process. Presently, the Denavit–Hartenberg (DH) parameters of a robotic manipulator are optimized for forward kinematics problems. The optimization is carried out using the JAYA approach. The 6R MTAB Aristo XT robot is selected as a case study for the experimental validation of the proposed approach. Experimental results reveal that the optimization of DH parameters improves accuracy for forward kinematic estimation problems. The proposed JAYA approach can further be extended to other robotic manipulators for parameter optimization problems.

Effect of pretreatment on mechanical properties of orange peel particulate (bio-waste) reinforced epoxy composites

Effects of chemical treatments with benzoyl chloride, acetone and alkali on the physical and mechanical properties of Orange Peel Particulate (OPP) reinforced epoxy composite materials have been studied. Hand lay-up technique was applied to manufacture the composites. The experimental results illustrate that chemical treatment with benzoyl chloride has a considerable impact. The properties of OPP reinforced composite material have been enhanced by 15% (for tensile test) and 30% (in case of flexural test) due to benzoyl chloride treatment as compared to raw OPP composites. It is evident from Fourier Transform Infrared Spectroscopy (FTIR) that non cellulosic content was removed from the surface of the fiber due to benzoyl chloride treatment. After chemical treatment there was good interfacial bonding between matrix and filler material as observed in SEM micrographs. From the experimental observations, it can be seen that among all fabricated composites, set of composites with 30% filler loading yields excellent mechanical properties.

CNC Milling of Medical-Grade PMMA

This study evaluates CNC milling parameters (spindle speed, depth of cut, and feed rate) on medical-grade PMMA. A single objective analysis conducted showed that the optimal material removal rate (MRR) occurs at a spindle speed of 1250 rpm, a depth of cut of 1.2 mm, and a feed rate of 350 mm/min. The ANOVA showed that feed rate is the most significant factor towards the MRR, and spindle speed (11.83%) is the least contributing. The optimal surface roughness (Ra) occurred at spindle speed of 500 rpm, depth of cut of 1.2 mm, and feed rate of 200 mm/min. The milling factors were insignificant. A regression analysis for prediction was also conducted. Further, a multi-objective optimization was conducted using the Grey Relational Analysis. It showed that the best trade-off between the MRR and the Ra could be obtained from a combination of 1250 rpm (spindle speed), 1.2 mm (depth of cut), and 350 mm/min (feed rate). The depth of cut was the largest contributor towards the grey relational grade (54.48%), followed by the feed rate (10.36%), and finally, the spindle speed (4.28%).

Accuracy investigation of Fused Deposition Modelling (FDM) processed ABS and ULTRAT parts.

This paper aims to assess the dimensional deviation of Fused Deposition Modeling (FDM) processed ABS and ULTRAT parts using a new geometrical model which can evaluate three types of dimensional deviation: along the z-axis, along external and internal dimensions, and through diameters. The methodology involves a step-by-step procedure wherein after establishing the experimental plan and manufacturing the specimens, the measurements taken are analyzed via Grey Relational Analysis (GRA) to find out the optimal combination of parameters leading to the minimum deviation in all dimensions of parts for both materials. Statistical techniques such as Analysis of Variance (ANOVA) and Signal to Noise (S/N) ratio were also used. Subsequently, a confirmation test was carried out to validate the results obtained. The findings of the ANOVA and the S/N ratio were in good concordance with those of GRA.

Comparison of Constitutive Models for predicting the formability of SS 304 by tubular hydroforming process

Finite Element (FE) simulation of sheet/tube forming precision depends mainly on the accuracy of the constitutive modeling. The present paper aim is to compare the constitutive models to fit the stress-strain curves. The accurate deformation behavior of the SS 304 tubes depends on the constitutive modeling of hardening behavior. Deformation data of the tensile specimens cut from tubular sample were collected by conducting Uniaxial tensile tests (UTT) at three different rolling directions. Five constitutive relationships were then recognized by fitting the true stress and strain data with the constitutive models of Hollomon, Power, Krupowsky, Voce and Ghosh, and the fitting accuracy were analyzed and compared. Effects of hardening models on Forming Limit Curves (FLC), pressure loading and bulge height of the hydroformed tube were then studied. The obtained FLC from the simulations were compared with experimental FLC to predict the accuracy of the hardening models.

Formability of Aluminum Alloys During Single Point Incremental Forming – A Review

Single point incremental sheet metal forming has passed through a period of ample improvement with developing responsiveness from research societies and industries globally. The process has expressively spared the practice of using costly dies, which makes it an appropriate process for manufacturing prototypes and small batch production. It also discovers easiness in fabricating components of timeworn equipment. Additionally, in recent years, aluminum alloys become the most commonly used materials in the automotive, aeronautics, and transportation industries for their structural and other applications. The effect of various process parameters on the formability of Single Point Incremental Forming of aluminum alloys has been critically surveyed. Ultimately, this article also debated the dares associated with the Single Point Incremental Forming process and recommended some correlated research regions which probably charm significant research considerations in the future.

Dry Machining of Inconel 825 Superalloys

The present work investigates application feasibility of PVD TiN/TiCN/TiN coated cermet and CVD Al2O3/TiCN coated SiAlON for dry machining of Inconel 825 superalloy. Machining performance is interpreted through cutting force magnitude, tool-tip temperature, and mechanisms of tool wear. Results are compared to that of CVD multi-layer TiN/TiCN/Al2O3/TiN coated WC-Co tool. It is evidenced that SiAlON tool generates lower cutting force but experiences higher tool-tip temperature than other two counterparts. Apart from abrasion and adhesion, carbide tool witnesses coating peeling and ploughing. In contrast, SiAlON tool suffers from inexorable chipping and notching. Wear pattern of cermet tool seems less severe than carbide and SiAlON. Chip's underside surface morphology appears relatively better in case of cermet tool.

SLS Process Parameter Optimization to Improve Surface Quality and Accuracy of Polyamide Parts

The contribution of selective laser sintering (SLS) technique in the 4.0 manufacturing industry is undisputedly significant. SLS part quality exhibits high dependence on SLS process parameters and is a major challenge. Therefore, this research aims to investigate the effect of input parameters (i.e., part orientation, bed temperature, and layer thickness) on the surface roughness and accuracy of laser-sintered polyamide specimens. Response surface methodology (RSM) and ANOVA analysis aided the testing and evaluation. Optimal working conditions for minimum shrinkage were 0.17 mm layer thickness, 177.89°C part bed temperature, and part orientation at 88.91 degrees. The surface quality deteriorated with the increment in part bed temperature and layer thickness, and it shows an inverse trend (or improves) with the part orientation in the prescribed range. The optimal surface roughness was at a layer thickness of 0.11 mm, bed temperature at 174.55°C, and part orientation at 86.5 degrees.

Combining Response Surface Method and Metaheuristic Algorithms for Optimizing SPIF Process

Recently, studies have focused on optimization as a method to reach the finest conditions for metal forming processes. This study tests various optimization techniques to determine the optimum conditions for single point incremental forming (SPIF). SPIF is a die-less forming process that depends on moving a tool along a path designed for a specific feature. As it involves various parameters, optimization based on experimental studies would be costly, hence a finite element model (FE-model) for the SPIF process is developed and validated through experimental results. In the second phase, statistical analyses based on the response surface method (RSM) are conducted. The optimum conditions are determined using the desirability optimization method, in addition to two metaheuristic optimization algorithms, namely genetic algorithm (GA) and particle swarm optimization (PSO). The results of all optimization techniques are compared to each other and a confirmation test using the FE-model is subsequently performed.