Surface reconstruction for incremental forming

In spite of extensive efforts being made with regard to virtual process optimization technology, the production of prototype parts is still a necessity. With respect to the production of sheet metal parts in low quantities, incremental sheet metal forming (ISMF) is a highly interesting process. ISMF allows the production of complex parts with drastically reduced costs in tooling and machinery compared to conventional processes like deep drawing. However, ISMF, with it’s incremental nature, introduces the need for generating a tool path considering both final geometry and process-induced deviations or constraints. Consequently, for the generation of the tool path a (tool path) surface, with an adequate offset, is necessary. That is why, within the scope of extensive research work at the Institute of Forming Technology and Lightweight Construction (IUL), a special correction module has been developed, determining this offset e.g. depending on the workpiece geometry. This paper presents the algorithm, the application, and the effect on the produced parts. Furthermore, a concept for an extension regarding further constraints like elastic workpiece behavior is presented.     

Determination of Active Slip/Twinning Modes in AZ31 Mg Alloy Near Room Temperature

In order to determine the deformation modes in AZ31 magnesium alloy at room temperature, computer simulations of deformation texture development and calculation of formability have been carried out. The simulation results were compared with the measured texture results. Based on agreement between the experiments and simulations the active deformation modes were determined. A Visco Plastic Self Consistent model was employed for the simulation of plastic deformation. Simulations and experiments were performed for different initial textures. The goal of the study was to develop the understanding of deformation texture evolution and its effects on mechanical properties of magnesium, with an ultimate goal of improving room temperature formability of magnesium alloys. This article was presented at Materials Science & Technology 2006, Innovations in Metal Forming symposium held in Cincinnati, OH, October 15-19, 2006.     

Developing a limb repositioning robotic interface for persons with severe physical disabilities

Limb repositioning is necessary for individuals with severe physical disabilities to sustain muscle strength and prevent pressure sores. As robotic technologies become ubiquitous, these tools offer promise to support the repositioning process. However, research has yet to focus on ways in which individuals with severe physical disabilities can control robots for these tasks. This paper presents a study that examines the needs and attitudes of potential users with physical disabilities to control a robotic aid for limb repositioning. Subjects expressed interest in using brain–computer interface (BCI) and speech recognition technologies for purposes of executing robotic tasks. The performance of four subjects controlling arm movements on an avatar through the keyboard, mouse, BCI, and Dragon NaturallySpeaking speech recognition was evaluated. Although BCI and speech technologies may limit physical fatigue, more challenges were faced using BCI and speech conditions compared to the keyboard and mouse. This research promotes accessibility into mainstream robotic technologies and represents the first step in the development of a robotic prototype using a BCI and speech recognition technologies for limb repositioning.     

Optimized deep learning-based intrusion detection for wireless sensor networks

The technological innovations and wide use of Wireless Sensor Network (WSN) applications need to handle diverse data. These huge data possess network security issues as intrusions that cannot be neglected or ignored. An effective strategy to counteract security issues in WSN can be achieved through the Intrusion Detection System (IDS). IDS ensures network integrity, availability, and confidentiality by detecting different attacks. Regardless of efforts by various researchers, the domain is still open to obtain an IDS with improved detection accuracy with minimum false alarms to detect intrusions. Machine learning models are deployed as IDS, but their potential solutions need to be improved in terms of detection accuracy. The neural network performance depends on feature selection, and hence, it is essential to bring an efficient feature selection model for better performance. An optimized deep learning model has been presented to detect different types of attacks in WSN. Instead of the conventional parameter selection procedure for Convolutional Neural Network (CNN) architecture, a nature-inspired whale optimization algorithm is included to optimize the CNN parameters such as kernel size, feature map count, padding, and pooling type. These optimized features greatly improved the intrusion detection accuracy compared to Deep Neural network (DNN), Random Forest (RF), and Decision Tree (DT) models.     

Aluminum phosphate sealing to improve insulation resistance of plasma-sprayed alumina coating

The insulation resistance of conventional atmospheric plasma-sprayed alumina coatings with 10–15% porosity is ～10¹¹ Ω. The presence of pores, lamellae boundaries, and other non-fillings dampens the insulation resistance of the coating. In the present study, aluminum phosphate was used to seal the surface of plasma-sprayed alumina coating and evaluate the effect of sealing on the insulation resistance and its thermal cycling response. Sealing was carried out with three concentrations of sealant (P/Al molar ratio of 3, 10, and 15). Characterization by X-ray diffraction and scanning electron microscopy revealed the primary sealing phase as aluminum metaphosphate and effective sealing of the pores by the aluminum phosphate phases. Insulation resistance is improved by two orders of magnitude after sealing the coated samples. Sealing with P/Al molar ratio 3 exhibited maximum insulation resistance of ～10¹³ Ω at room temperature. Thermal cycling studies between 650°C and 200°C on the sealed samples showed deterioration in thermal cycling life after sealing.     

Investigation of machining characteristics in rotary ultrasonic machining of alumina ceramic

Alumina ceramic is well documented as a much-demanded advanced ceramic in the present competitive structure of manufacturing and industrial applications owing to its excellent and superior properties. The current article aimed to experimentally investigate the influence of several process variables, namely: spindle speed, feed rate, coolant pressure, and ultrasonic power, on considered machining characteristics of interest, i.e., chipping size and material removal rate in the rotary ultrasonic machining of alumina ceramic. Response surface methodology has been employed in the form of a central composite rotatable design to design the experiments. Variance analysis testing has also been performed with a view to observing the consequence of the considered parameters. The microstructure of machined rod samples was evaluated and analyzed using a scanning electron microscope. This analysis has revealed and confirmed the presence of plastic deformation that caused removal of material along with brittle fractures in rotary ultrasonic machining of alumina ceramic. The validity and competence of the developed mathematical model have been verified with test results. The multi-response optimization of machining responses (material removal rate and chipping size) has also been attempted by employing a desirability approach, and at an optimized parametric setting the obtained experimental values for material removal rate and chipping size were 0.4166?mm³/s and 0.5134?mm, respectively, with a combined desirability index value of 0.849.     

A Comparative Investigation of Optical and Structural Properties of Cu-Doped CdO-Derived Nanostructures

In this report, we studied various structural and optical properties of pure and copper-doped cadmium oxide (CdO) thin films. Nanostructured Cu-doped CdO films were deposited using sol–gel spin-coating technique. The structural and morphological changes have been observed by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), and atomic force microscopy (AFM) studies. The optical and electrical properties of the pure and Cu-doped CdO thin films were studied by UV–vis spectroscopy and four-point probe method, respectively. The XRD peaks show the formation of nanocrystalline CdO with cubic face-centered crystal structure. The band gaps of the as deposited films were found in the range of 2.32–2.73 eV, while after doping, it decreases due to structural deformation. The electrical resitivity was found to decrease approximately ～10 in Cu-doped CdO thin films.     

Mesoporous titanium dioxide nanocatalyst: a recyclable approach for one‐pot synthesis of 5‐hydroxymethylfurfural

The present study deals with the production of 5‐hydroxymethyl furfural (HMF) from fructose by chemo‐conversion method using chemical catalyst, conventionally achieved by microwave‐assisted dehydration process. Five different chemical catalysts, namely oxalic acid, phosphotungstic acid and mesoporous titanium dioxide nanoparticles (TNPs) were compared at constant conditions of which TNPs yielded a maxima of 33.95%. The optimum temperature and catalyst loading were found to be 200°C and 20%, respectively, at a 5% optimum substrate concentration during 15 min optimum reaction time to yield 61.53% HMF. The efficiency of synthesised TNPs was investigated further through reusability studies. TNPs were properly recycled and the catalytic activity recovery was good even after a 14 batch reactions. The specific surface area of the TNP obtained is about 105.46 m² /g and its pore‐volume is about 0.42 cm³ /g according to single point adsorption. A large accessible surface area combined with a minimal pore size (15.92 nm) obtained with mesoporous TNPs is desirable for better catalyst loading, high‐yield HMF, retention and reduced diffusion constraints.Inspec keywords: mesoporous materials, recycling, production management, dissociation, nanoparticles, nanotechnologyOther keywords: mesoporous titanium dioxide nanocatalyst, recyclable approach, one‐pot synthesis, 5‐hydroxymethyl furfural production, HMF, chemo‐conversion method, chemical catalyst, microwave‐assisted dehydration process, oxalic acid, phosphotungstic acid, mesoporous titanium dioxide nanoparticles, TNP     

Green synthesis of highly stable carbon nanodots and their photocatalytic performance

The present study reports a novel, facile, biosynthesis route for the synthesis of carbon nanodots (CDs) with an approximate quantum yield of 38.5%, using Musk melon extract as a naturally derived‐precursor material. The synthesis of CDs was established by using ultraviolet–visible (UV–vis) spectroscopy, Dynamic light scattering, photoluminescence spectroscopy, X‐ray diffraction, transmission electron microscopy and Fourier transform infrared (FTIR) spectroscopy. The as‐prepared CDs possess an eminent fluorescence under UV–light (λ _ex  = 365 nm). The size range of CDs was found to be in the range of 5–10 nm. The authors further explored the use of such biosynthesised CDs as a photocatalyst material for removal of industrial dye. Degradation of methylene blue dye was performed in a photocatalytic reactor and monitored using UV–vis spectroscopy. The CDs show excellent dye degradation capability of 37.08% in 60 min and reaction rate of 0.0032 min⁻¹. This study shows that synthesised CDs are highly stable in nature, and possess potential application in wastewater treatment.Inspec keywords: carbon, nanostructured materials, nanofabrication, catalysis, photochemistry, ultraviolet spectra, visible spectra, photoluminescence, X‐ray diffraction, transmission electron microscopy, Fourier transform infrared spectra, fluorescence, dyesOther keywords: green synthesis, highly stable CD, photocatalytic performance, biosynthesis route, carbon nanodots, quantum yield, Musk melon extract, naturally derived‐precursor material, ultraviolet‐visible spectroscopy, dynamic light scattering, photoluminescence spectroscopy, X‐ray diffraction, transmission electron microscopy, Fourier transform infrared spectroscopy, FTIR spectroscopy, fluorescence, biosynthesised CD, photocatalyst material, industrial dye, methylene blue dye degradation, photocatalytic reactor, UV‐vis spectroscopy, wastewater treatment, size 5 nm to 10 nm, time 60 min     

VMI versus information sharing: an analysis under static uncertainty strategy with fill rate constraints

A vendor-managed inventory (VMI) relationship between a downstream retailer and an upstream vendor consists of two distinct components: (i) information sharing (IS) and (ii) a shift in decision-making responsibility. This study compares these two components of VMI in a two-stage serial supply chain based on the ‘static uncertainty’ strategy under dynamic and random demand with fill rate constraints. Numerical experiments are conducted using analytical models to identify the conditions where the incremental value of VMI over IS is significant. The results provide guidelines relevant to academia and supply chain practitioners in taking VMI adoption decision above and beyond IS according to their specific business environment.