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Despite the extensive research, the moisture-based degradation of the 3D-printed polypropylene and polylactic acid blend is not yet reported. This research is a part of study reported on partial biodegradable blends proposed for large-scale additive manufacturing applications. However, the previous work does not provide information about the stability of the proposed blend system against moisture-based degradation. Therefore, this research presents a combination of excessive physical interlocking and minimum chemical grafting in a partial biodegradable blend to achieve stability against in-process thermal and moisture-based degradation. In this regard, a blend of polylactic acid and polypropylene compatibilized with polyethylene graft maleic anhydride is presented for fused filament fabrication. The research implements, for the first time, an ANOVA for combined thermal and moisture-based degradation. The results are explained using thermochemical and microscopic techniques. Scanning electron microscopy is used for analyzing the printed blend. Fourier transform infrared spectroscopy has allowed studying the intermolecular interactions due to the partial blending and degradation mechanism. Differential scanning calorimetry analyzes the blending (physical interlocking or chemical grafting) and thermochemical effects of the degradation mechanism. The thermogravimetric analysis further validates the physical interlocking and chemical grafting. The novel concept of partial blending with excessive interlocking reports high mechanical stability against moisture-based degradation.

This research presents a partial biodegradable polymeric blend aimed for large-scale fused deposition modeling (FDM). The literature reports partial biodegradable blends with high contents of fossil fuel-based polymers (>20%) that make them unfriendly to the ecosystem. Furthermore, the reported polymer systems neither present good mechanical strength nor have been investigated in vulnerable environments that results in biodegradation. This research, as a continuity of previous work, presents the stability against biodegradability of a partial biodegradable blend prepared with polylactic acid (PLA) and polypropylene (PP). The blend is designed with intended excess physical interlocking and sufficient chemical grafting, which has only been investigated for thermal and hydrolytic degradation before by the same authors. The research presents, for the first time, ANOVA analysis for the statistical evaluation of endurance against biodegradability. The statistical results are complemented with thermochemical and visual analysis. Fourier transform infrared spectroscopy (FTIR) determines the signs of intermolecular interactions that are further confirmed by differential scanning calorimetry (DSC). The thermochemical interactions observed in FTIR and DSC are validated with thermogravimetric analysis (TGA). Scanning electron microscopy (SEM) is also used as a visual technique to affirm the physical interlocking. It is concluded that the blend exhibits high stability against soil biodegradation in terms of high mechanical strength and high mass retention percentage.

Acrylonitrile butadiene styrene (ABS) is a renowned commodity polymer for additive manufacturing, particularly fused deposition modelling (FDM). The recent large-scale applications of 3D-printed ABS require stable mechanical properties than ever needed. However, thermochemical scission of butadiene bonds is one of the contemporary challenges affecting the overall ABS stability. In this regard, literature reports melt-blending of ABS with different polymers with high thermal resistance. However, the comparison for the effects of different polymers on tensile strength of 3D-printed ABS blends was not yet reported. Furthermore, the cumulative studies comprising both blended polymers and in-process thermal variables for FDM were not yet presented as well. This research, for the first time, presents the statistical comparison of tensile properties for the added polymers and in-process thermal variables (printing temperature and build surface temperature). The research presents Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA) to explain the thermochemical reasons behind achieved mechanical properties. Overall, ABS blend with PP shows high tensile strength (≈31 MPa) at different combinations of in-process parameters. Furthermore, some commonalities among both blends are noted, i.e., the tensile strength improves with increase of surface (bed) and printing temperature.

The materials for large scale fused filament fabrication (FFF) are not yet designed to resist thermal degradation. This research presents a novel polymer blend of polylactic acid with polypropylene for FFF, purposefully designed with minimum feasible chemical grafting and overwhelming physical interlocking to sustain thermal degradation. Multi-level general full factorial ANOVA is performed for the analysis of thermal effects. The statistical results are further investigated and validated using different thermo-chemical and visual techniques. For example, Fourier transform infrared spectroscopy (FTIR) analyzes the effects of blending and degradation on intermolecular interactions. Differential scanning calorimetry (DSC) investigates the nature of blending (grafting or interlocking) and effects of degradation on thermal properties. Thermogravimetric analysis (TGA) validates the extent of chemical grafting and physical interlocking detected in FTIR and DSC. Scanning electron microscopy (SEM) is used to analyze the morphology and phase separation. The novel approach of overwhelmed physical interlocking and minimum chemical grafting for manufacturing 3D printing blends results in high structural stability (mechanical and intermolecular) against thermal degradation as compared to neat PLA.

Acrylonitrile butadiene styrene (ABS) is a well-known material used in fused filament fabrication (FFF) for industrial and research applications. However, it has poor thermal stability due to the t...

Polylactic acid (PLA) is one of the most widely used open source fused filament fabrication materials due to its ease of extrusion, biodegradability, and mechanical strength. The mechanical strengt...

When the entire system was put together, adequate control of the robot was possible. Overall the system performed well enough to get controlled motion of the six joints of the PUMA robot arm. The system was also subsequently used to control a CNC lathe. There were, however, a few problems with the final system. The system also requires some further enhancement to achieve better control of joint positioning. The main problem occurred with the logic power supply. Every now and then the logic power, which supplies all the encoder circuits and microprocessors, would fail to power the most essential parts of the system. This would result in unpredictable behaviour from the robot arm and make it unsafe. It was found that the grounding of the logic power supply was floating causing differences in the ground of the system components. By using the ground of a bench-top power supply, this problem was solved. The rest of the problems with the final system were a result of the PID control method. The PID control was not able to account for the effects of inertia and gravity because the feedback gains of the PID algorithm were fixed. This meant that the system had a very low level of repeatability and accuracy. The Encoder PID mode of the BrainStem Moto 1.0, although working well for the wrist joints, did not perform very well for the larger joints. When a new setpoint was entered into the PID control loop, the control algorithm would output maximum voltage to the motor until it neared the new setpoint based on the feedback from the encoders and the PID gains. It did this without accounting for the effects of inertia and gravity. In practice this meant, for the shoulder and elbow joints especially, that the joint would move more rapidly in the down direction that it would in the up direction. To correct this problem, a velocity control method needs to be explored. Another problem that exists with the BrainStem Moto 1.0, is that it only has a 16-bit setpoint number and this is reduced to 15-bits as the most significant bit is a directional bit. Due to the resolution of the 250 line incremental encoders, only limited movement of a joint can be completed with each command sent to the BrainStems. This leads on to another problem with the BrainStem program. It is not able to detect when a movement is complete so that the next move of the robot can take place, i.e. there are no flags set to indicate a new setpoint has been achieved. This problem was overcome, in Visual Basic, by introducing a timer delay between selected movements. A problem also occurs when the motors are powered at high speeds. At high motor speeds the PIC fails to read the encoder pulses. This results in uncontrolled motion of the joints. In some cases the encoder circuit that was developed for the incremental encoders fails to supply the pulse train signal to the BrainStems. This may be because there was a frequency limitations on the ICs used in the encoder circuit. This problem could also arise from aliasing. This would depend on the rate at which the PIC samples the input signal from the encoder circuit. The effect of this problem is that robot must operate at reduced speeds in order to maintain control. The only other item of note is that the robot joints require calibration every time the robot is turned on. This is the purpose of the potentiometers in each motor. The potentiometers are input directly to the analogue inputs of the BrainStem Moto 1.0 that provides a 10-bit analogue-to-digital conversion of the potentiometer value. This value gives an indication of the position of the robot when it is powered up. As these problems are overcome, further planned development of the system is to integrate it with RobotWorks, a computer aided manufacturing (CAM) package. RobotWorks is an add-on package for SolidWorks, which is a commonly used CAD program. The idea being that path planning for the manufacture of various parts and 783

The collagen hydrolysate, a proteinic biopeptide, is used for various key functionalities in humans and animals. Numerous reviews explained either individually or a few of following aspects: types, processes, properties, and applications. In the recent developments, various biological, biochemical, and biomedical functionalities are achieved in five aspects: process, type, species, disease, receptors. The receptors are rarely addressed in the past which are an essential stimulus to activate various biomedical and biological activities in the metabolic system of humans and animals. Furthermore, a systematic segregation of the recent developments regarding the five main aspects is not yet reported. This review presents various biological, biochemical, and biomedical functionalities achieved for each of the beforementioned five aspects using a systematic approach. The review proposes a novel three-level hierarchy that aims to associate a specific functionality to a particular aspect and its subcategory. The hierarchy also highlights various key research novelties in a categorical manner that will contribute to future research.

The United Nations Sustainable Development Goals (SDGs) epitomize a macro-perspective on work as they apply to all societies regardless of their economic, political, or geographic considerations. From this perspective, work is no longer just about being efficient for the benefit of an employing organization (meso-level) or indeed about individuals “coping” with organizational stressors (micro-level). More fundamentally, it serves as a means to meet individuals’ daily aspirations for a decent quality of life and work life. A key concept that centrally bridges – and theoretically connects – these three levels of analysis (macro, meso, micro) is sustainable livelihood. Originally developed with respect to low-income rural communities, it resonates with most workers (and students) today. This chapter illustrates how the concept of sustainable livelihood is relevant to macropsychology and can be a figure-ground reversal in conventional work psychology. Like donning a reversible jacket, a focus on sustainable livelihood adds a fresh perspective, new ideas, and real solutions for specific global humanitarian challenges. It requires for work psychology to consider the macro-level in addition to micro- and meso-level issues. With specific reference to SDG-8 (Decent Work for All), we outline in this chapter how macro-policy related to income (working poverty, income inequality), labour mobility (from precarious informality to inclusive diversity), and the future of work afford work psychologists prime opportunities to contribute towards decent work for all.

The identification of plant disease is an imperative part of crop monitoring systems. Computer vision and deep learning (DL) techniques have been proven to be state-of-the-art to address various agricultural problems. This research performed the complex tasks of localization and classification of the disease in plant leaves. In this regard, three DL meta-architectures including the Single Shot MultiBox Detector (SSD), Faster Region-based Convolutional Neural Network (RCNN), and Region-based Fully Convolutional Networks (RFCN) were applied by using the TensorFlow object detection framework. All the DL models were trained/tested on a controlled environment dataset to recognize the disease in plant species. Moreover, an improvement in the mean average precision of the best-obtained deep learning architecture was attempted through different state-of-the-art deep learning optimizers. The SSD model trained with an Adam optimizer exhibited the highest mean average precision (mAP) of 73.07%. The successful identification of 26 different types of defected and 12 types of healthy leaves in a single framework proved the novelty of the work. In the future, the proposed detection methodology can also be adopted for other agricultural applications. Moreover, the generated weights can be reused for future real-time detection of plant disease in a controlled/uncontrolled environment.

Air pollution poses significant risks to environment and health. Air quality monitoring stations are often confined to a small number of locations due to the high cost of the monitoring equipment. They provide a low fidelity picture of the air quality in the city; local variations are overlooked. However, recent developments in low cost sensor technology and wireless communication systems like Internet of Things (IoT) provide an opportunity to use arrayed sensor networks to measure air quality, in real time, at a large number of locations. This paper reports the development of a novel low cost sensor node that utilizes cost-effective electrochemical sensors to measure Carbon Monoxide (CO) and Nitrogen Dioxide (NO2) concentrations and an infrared sensor to measure Particulate Matter (PM) levels. The node can be powered by either solar-recharged battery or mains supply. It is capable of long-range, low power communication over public or private LoRaWAN IoT network and short-range high data rate communication over Wi-Fi. The developed sensor nodes were co-located with an accurate reference CO sensor for field calibration. The low cost sensors’ data shows strong correlation with the data collected from the reference sensor. Offset and gain calibration further improves the quality of the sensor data.

The next generation fully implantable pressure sensors are valuable for intracranial pressure (ICP) monitoring, particularly in the chronic conditions of hydrocephalus. However, the accuracy, particularly in terms of the sensor drift over long duration, is a key concern. An implantable pressure monitoring system will rely on a flexible thin-film membrane as part of the pressure sensor and will interfere with a corrosive fluid (saline/blood) at a temperature of approximately 37 $$^\circ \hbox {C}$$ . The physics of the underlying thin film (material aging, mechanical fatigue), independent of the surrounding medium, triggers drift in the long-term monitoring of ICP. Therefore, finite element modeling (FEM) of thin-film deflection and fatigue life are essential. Although the FEM provides a theoretical view of the underlying issue, it is also necessary to validate the accuracy of the model. In this paper, we present both the numerical modeling and experimental validation of thin-film deflection and fatigue life of thin film titanium foils. The salient feature of this work is the approach of the thin-film deflection and fatigue testing (as part of the entire sensor) in contrast to the standard dog-bone based fatigue testing.

Collagen extracts can be electrospun to form fibers. The nanoscale structure of these fibers is not known but is expected to affect the biocompatibility of the spun materials. Collagen extracts from Macruronus novaezelandiae (hoki) skin were electrospun to form a fibrous material. The structure of the electrospun collagen fibers was analyzed and compared with the structure of native collagen, gelatin, and electrospun gelatin. Attenuated Total Reflectance Fourier Transform Infrared spectroscopy (ATR-FTIR) and SDS-PAGE were used to characterize the basic molecular structure of the biomaterials and synchrotron-based small-angle X-ray scattering (SAXS) and Transmission electron microscope (TEM) were used to investigate the fibril nanoscale structure (molecular arrangement). ATR-FTIR and SDS-PAGE revealed characteristic patterns of intact alpha chains in the electrospun collagen and hydrolyzed fragments in electrospun gelatin, as expected. TEM revealed fibers in both the native collagen material and the electrospun samples. However, SAXS patterns showed axial periodicity was not present in the electrospun fibers. This is indicative of the spinning process forming fibers that lack internal fibril structure, in contrast to the hierarchical structure of native collagen. The architecture of collagen affects its function. By characterizing the molecular and fibril structure of electrospun collagen and comparing it with native collagen fibrils, we may inform functional studies of collagen, including its configuration for cell attachment and recognition.

The extrusion system is an integral part of any fused deposition style 3D printing technique. However, the extruder designs found in commercial and hobbyist printers are mostly suitable for materials in filament form. While printing with a filament is not a problem per se, the printing of materials that may not be readily available in the filament form or not commercially viable remains untapped, e.g., biopolymers and material blends. This is particularly an issue in the research and hobbyist space where the capability of printing a variety of materials or materials recycled from already printed parts may be of utmost importance. This paper presents a pellet-based extrusion system for the 3D printing of biopolymers. The system has been designed from the first principles and therefore can be extended to other materials with parameter adjustments or slight hardware modifications. A robust mechatronic design has been realized using an unconventional yet simplistic approach. The extrusion system uses a series of control factors to generate a consistent output of material over the course of a print. The platform and surrounding processes are set up so that software can be used to define the printing parameters; this allows a simpler adaption to different materials. The utility of the extruder is demonstrated through extensive printing and testing of the printed parts.

In this paper, we present a novel method with unique surface modification technique to detect dissolved arsenite contamination of water. It features self-assembled patterns of thiol ligand like glutathione (GSH) on the gold-coated glass. Thiol easily binds with gold through Au-S linkage. In addition to this, As(III) has an affinity towards amino acids, amines, peptides and organic micro-molecules due to As-O or As-S linkages. Hence, GSH binds with gold-coated glass and arsenic. The patterns are obtained through a micro-contact printing (µCP) procedure. When these patterns are exposed to arsenic-contaminated water, the arsenic layer forms on the GSH pattern which produces an optical diffraction grating for the detection system. These self-assembled optical diffraction patterns can detect dissolved arsenite up to 20 µg/L. Our findings suggest that the proposed method can also be used for detection of a variety of other metallic and pathogenic contaminants like E. coli for water Quality monitoring.

Plant diseases affect the growth of their respective species, therefore their early identification is very important. Many Machine Learning (ML) models have been employed for the detection and classification of plant diseases but, after the advancements in a subset of ML, that is, Deep Learning (DL), this area of research appears to have great potential in terms of increased accuracy. Many developed/modified DL architectures are implemented along with several visualization techniques to detect and classify the symptoms of plant diseases. Moreover, several performance metrics are used for the evaluation of these architectures/techniques. This review provides a comprehensive explanation of DL models used to visualize various plant diseases. In addition, some research gaps are identified from which to obtain greater transparency for detecting diseases in plants, even before their symptoms appear clearly.

Additive manufacturing (AM) is rapidly evolving as the most comprehensive tool to manufacture products ranging from prototypes to various end-user applications. Fused filament fabrication (FFF) is the most widely used AM technique due to its ability to manufacture complex and relatively high strength parts from many low-cost materials. Generally, the high strength of the printed parts in FFF is attributed to the research in materials and respective process factors (process variables, physical setup, and ambient temperature). However, these factors have not been rigorously reviewed for analyzing their effects on the strength and ductility of different classes of materials. This review systematically elaborates the relationship between materials and the corresponding process factors. The main focus is on the strength and ductility. A hierarchical approach is used to analyze the materials, process parameters, and void control before identifying existing research gaps and future research directions.

In the challenging and resource scarce South African context, characterized by its cultural diversity, the deliberate combination of adventure therapy and positive psychology holds significant promise to address a number of the criticisms levelled against so-called ‘traditional’ modes of therapy. This chapter introduces the deliberate and strategic combination of adventure therapy and positive psychology as one possible answer to the World Health Organization’s call for the development of novel, integrated interventions that develop with populations, strive to both prevent disease and facilitate mental health, and make optimal use of resources within the person and his/her environment. As a new branch of psychology, it is important that positive psychology continues designing innovative interventions and incorporating interventions from other therapeutic fields that support the psychological well-being of individuals. Since the majority of positive psychology interventions are written- and verbal-based, this chapter invites clinicians and researchers from the field of positive psychology to expand their toolbox by incorporating nature-based adventure therapy intervention. Results from a number of recent South African studies, using both quantitative and qualitative methodologies, show significant increases in self-reported levels of a number of well-being indicators after conducting interventions in an adventure and nature-based context. These constructs include character strengths, resilience, self-regulation and grit. When integrated into the therapeutic space by positive psychologists and psychotherapists, adventure therapy can help build resilience in individuals and groups within non-clinical settings. This will represent an additional tool to prevent stress-related pathology in relatively healthy populations, and will positively impact the reach, scalability and affordability of health-promotion interventions delivered in resource-scarce contexts like South Africa.

The design, development, and testing of a robot-assisted biopolymer thin shell free-form printing system is presented. This fused-deposition style printing system directly extrudes pellets of biomaterial and is capable of printing directly on organically shaped 3D curved surfaces. The screw extrusion method allows direct printing from pellets. The printed structure is supported by a pre-built base (a mandrel), which is manipulated by a six degree-of-freedom industrial robot arm, an ABB IRB120. This robot is used to manipulate the orientation of the support mandrel surface. The print method works by projecting a desired 2D image onto a mathematical model of the pre-built mandrel surface. This produces a 3D point path for the system to follow. These points are then converted into vectors for the robot’s pose and orientation of the end effector, which ensures that the extrusion remains normal to the mandrel surface. Inverse kinematics is applied to convert the trajectory into joint positions for the robot to follow. This paper demonstrates the utility of the developed system through simulation and printing of concave surface designs.

Here we present, characterizations of generic fluidic components used in biosensing applications. Low-cost fluidic components such as a peristaltic pump, solenoid valve, and flow sensor have been characterized individually in this work. The solenoid valves and an electro-optical flow sensor have been fabricated in-house. An automatic fluidic system has been developed with the help of these custom-made components. Computational data, such as flow rate and volume flow curves, have also been plotted with the experimental results for validation purposes. The peristaltic pump has been used for fluidic processing. The pump performance is evaluated by connecting and disconnecting the solenoid valves in the fluidic network. In both the cases, the pump has shown a linear operation. The observed flow rate was ranging from 0 to 80 mL/min. The solenoid pinch type valves have been fabricated for controlling the fluid flow. These valves have been evaluated on the bases of the electrical parameters. The operating voltage of the valve is 12 volts. The observed holding and inrush voltages are 6 volts and 1 volt respectively. An electrooptical flow sensor has been developed for detecting the presence of fluid in the system. This is achieved by measuring the light scattered by the fluid present in the tubing. The effect of different liquids on the output of the sensor has been investigated. Design strategies are extracted and used to develop a highly sensitive and cost-effective flow sensor.

Additive Manufacturing (AM) is expanding out of the Rapid Prototyping space to an end user product manufacturing technology. The commercial interest in industry, has created research opportunities to study how quality assurance can be provided for AM end user part. There are several concerns lacking solutions at this stage, one of which is the surface finish quality on a metal AM part. The unmodified printed part extracted from an AM metal printer, often has a rough finish on the exterior surface. When the support material is removed from the part, a rough texture from the prongs bonding the support layers and part layers often leaves an even rougher texture in associated areas. For this reason, AM parts require further maintenance, often media polishing, to achieve the parts required surface finish. In cases where structural and mechanical quality is required, the surface finish can have a detrimental impact. While there are several beneficial methods employed in Subtractive, Formative and Joining manufacturing processes to improve metal surface finish, the method of interest in this study is laser reheating. More specifically, the scope of this paper studies effect laser reheating has on the surface finish of AM prints. A review of similar processes for other AM metals is studied to determine testing parameters of interest. The experimental work performed focuses on testing specimens printed in a Direct Metal Printer (DMP), applied to Stainless Steel 17-4 PH powdered material. The aim of this experiment is to determine, through stronger bonding and further melting, whether a smoother and more polished surface can be achieved. The results of the experiment performed showed high laser power and scan speed result in a better polish with each repetition, but increased reheating on just one layer caused an inward collapse. Several quality inspection techniques are compared to determine which proves the most fruitful in a studying the surface finish of the samples. Testing methods utilized, include visual inspection techniques (human eye and Scanning Electron Microscopy (SEM)), mechanical tests (compression and micro-hardness testing) and NDE roughness profiling techniques (dye-penetrant, AFM and Surface Profilometer testing).

The application of vapour exposure systems upon 3D printed objects as a means for surface modification is a thoroughly established technique. This study investigated the utilization of a generated controlled vapour chamber device to further derive the relationship between surface modification exposure to that of part structural properties, namely interlayer bonding. This controlled utilization of vapour is intended to identify potential for future sequential 3D printing methodologies. The study mirrored previous work as such an UPBox Fused deposition modelling printer was required to produce thirty acrylonitrile butadiene styrene ASTM D638 Type IV dog-bone samples. Each of these was subjected to controlled vapour exposure relative to defined sample sets, namely groups of 5 representing exposure intervals at 0%, 20%, 25%, 50%, and 100% printing completion. Analysis for these was conducted via Instron 5967 tensile testing and a Hitachi TM3030Plus Scanning electron microscopy. These samples depicted a directly proportional increase in ultimate tensile strength and layer fusion with increased vapour exposure. These values contradicted the previous uncontrolled study.

Industrial progression of Additive Manufacturing awaits novel quality management strategies to verify 3D printed parts are fit for purpose. This paper presents a review of testing technologies: tensile testing and Scanning Electron Microscopy (SEM). The experiment performed aimed to provide a comparative study, of the testing technologies, to better understand current quality management processes in the 3D printing space. Additionally, this study was performed to establish a good fundamental groundwork on which future Non-Destructive Testing research can be conducted. The study revealed the advantages of tensile and SEM testing methods, whilst highlighting a need for better technologies to cover the disadvantages.

Medical exoskeletons are robotic devices that provide paraplegics with the ability to ambulate again. There are four current market leaders in the industry: REX, by Rex Bionics; ReWalk, by Argo Medical Technologies Ltd; Ekso GT, by Ekso Bionics; and Indego, by Parker Hannifin. A weighted table-based method was used to evaluate the capability of these four devices, which was then compared to their maximum speed. The Ekso GT and the ReWalk devices achieved high speeds but had low capability scores due to their instability and minimal safety features. The REX and Indego devices achieved the highest capability scores but for contrasting reasons; the REX devices are inherently stable but have a slow, static gait, while the Indego device relies on walking aids for stability and achieves a faster speed. Both devices scored high in the safety criteria. It was derived from the results that there is an indirectly proportional relationship between speed and stability, and none of the exoskeletons achieve a balance between the two. This study found that there is an opportunity to enhance the speed, mobility, stability, and cost of medical exoskeletons, which is presented below.

The characteristics of the interlayer bonding within 3D Printed objects is a fundamental feature determining the strength of the resultant object. This study set out to identify the opportunity for additional inter layer processing within 3D Printing. Inter layer processing is the addition of processes before a new layer can be printed upon a previous layer. Thirty Acrylonitrile butadiene styrene ASTM D638 Type IV dog-bone samples were generated using an UPBox Fused deposition modelling printer. These were segmented into five groups associated with exposure at 0%, 20%, 25%, 50%, and 100% printing intervals. Tensile testing was conducted through the utilization of an Instron 5967 and a Hitachi TM3030Plus Scanning electron microscope was used for topographical analysis of sample layer fusion/bonding. Samples showed a inversely proportional change in characteristics relative to inter-layer processing, namely an increase in processing decreased the ultimate tensile strength at elongation and decreased the distinguishable layering and cavities within the sample.

Stroke affects up to 2% of the population, with an increasing number of patients surviving the event and requiring rehabilitation, placing increasing demand on medical systems. As a result, there is an emergent area of research investigating the use of robotics as a means to aid in stroke patients' rehabilitation. Projects such as the MIT Manus have provided evidence of the efficacy of robotic rehabilitation for stroke patients, but further research is required to provide ongoing improvements to this approach. Concurrent enquiry has shown mirror therapy, originally applied to treat phantom pain syndrome in amputees, to be potentially efficacious in stroke rehabilitation. A prototype robotic rehabilitation system was developed to investigate the integration of these two approaches to stroke rehabilitation as a more eclectic approach. The operation of the prototype was verified, however further development is required to produce a system suitable for patient trials.

The predominance of conventional polymer processes (CPP) is undoubtedly formidable regarding monetary benefits gained in lieu of mass production in the global market. In this research, profitable commercial status of CPP is critically questioned in case of a specific large-scale application in low quantities, considering the following three factors: cost, time, and complexity. This research paper reports the subjective analysis-based exclusion of conventional processes (injection moulding) that brings the ball in the court of additive manufacturing (AM) technologies which are superior to injection moulding in low volume production. However, the AM techniques are limited to print only small-scale products in low quantity. This paper proposes a novel application of large scale products in low quantities by extruding polymer pellets from conceptual extrusion based deposition modeling setup. The requirement of a suitable material for conceptual extrusion setup entails the analysis of various factors to verify the feasibility of current fused deposition modeling materials for the conceptual large extrusion based deposition modeling setup. Therefore, this research contributes through providing a feasibility report for the CPP, AM techniques and their materials to print large-scale products.

3D Printing additive manufacturing is a rapidly developing form of technology. Currently able to manipulate many polymers (both synthetic and organic) this technique is quickly becoming an integral part of biotechnological developments. This paper highlights the fundamentals of this technology namely the mechanisms employed in standard 3D printing it then introduces tissue engineering a field in which current versions of this technology have been employed as bioprinting. The limitations with respect to tissue engineering are discussed outlining the current technologies inability to produce nanofibre based structures common in tissue such as tendon cartilage and cornea. From this requirement for nanofibre production electrospinning is introduced as a potential pathway for future tissue engineering 3D printing technologies and finally the current combination of this technology with 3D Printing is discussed yielding current limitations in retaining required nano-resolutions.

Consumer-grade RGB-D cameras capture RGB images along with per-pixel depth information, and because of their limited cost and ability to measure distances at a high frame rate, have been used in robotics and computer vision application. However, drawbacks include the repeatability and accuracy of RGB-D cameras for object detection and localization. This paper investigates and compares RGB-D cameras' performance in terms of depth image quality, depth clouds distribution, etc. performance and configuration methods of frequently used cameras, e.g. PrimeSense, Kinect V1 and Kinect V2, in order to provide useful advice when choosing a camera for robotic applications. Experimental and Point Cloud Library (PCL)-based methods are introduced for point-to-plane distance detection. Based on the obtained results, a relationship between measurements and ground truth is built.

The nature of fibre placement/manipulation in electrospinning has been recorded through the utilization of surface actuation and electrostatic manipulation. This study investigates the potential of a simplistic approach to fibre placement manipulation through the utilization of non-uniform non-conducting collecting surfaces. A solution of Nylon 6,6 and Formic acid was electrospun with an ES1a device and through the use of SEM analysis submicron and nanofibre alignment was identified. This study achieved the generation of actuation-less and electrode-less alignment reiterating current literatures rationale of alignment formation. The study noted limitations regarding the potential combination of mold/cavity and electrospinning based manufacturing. From this work future recommendations regarding surface modification have been derived.

Additive manufacturing (AM) allows designers to build 3D parts of almost any geometry and streamline the process of moving from initial design to prototype in a shortened timeframe. However the existing technologies are limited to small size parts due only to high resolution of the generally produced designs. If a very large part with typical layer resolutions of 0.2mm is produced, the time required for making such a part will be prohibitive. In addition, the material costs will excessive and the machine size will need to be gigantic. In large scale printing the material and the high costs restrict testing on the actual structures and lends itself to the use of numerical or analytical studies of the structures before actual printing. In this paper we analyse the current state of the 3D printing within the boundaries of large scale printing and present a possible solution with numerical simulations.

A leading area of research in Additive Manufacturing, studies the quality of 3D prints using several testing strategies. This paper reviews two testing technologies: tensile testing (mechanical testing) and Scanning Electron Microscopy (SEM). The aim of this experiment was to provide a comparative study to better understand quality management processes in the 3D printing space. Additionally, this research study was performed to establish a good fundamental groundwork on which future Non-Destructive Testing research can be conducted. The study revealed the advantages of the tensile and SEM testing methods, whilst highlighting a need for better technologies to cover the disadvantages.

Sono descritte le principali tecniche colturali e postraccolta del ficodindia

Matsuoka neuronal oscillator is proposed to control the traffic signals of an isolated four-phase signalized intersection. The oscillator is a model of central pattern generator (CPG) and has seen various applications in humanoid robots. Matsuoka oscillator was chosen for the traffic signal control because of its stable and predictable rhythmic outputs that exploit autonomously the dynamics of the road system. In this paper, the dynamics of Matsuoka oscillator was described in a set of first-order differential equations and simluated in an agent-based modelling environment. This novel signal control algorithm was validated in a Application Programming Interface (API) function by AIMSUN (Advanced Interactive Microscopic Simulator for Urban and Non-Urban Networks). The results were compared to the performance of the existing traffic system and have shown the potential capability of the proposed algorithm in reductions of vehicle delay time and queues.

In this paper we study the characteristics of displacement field during installation of a model pile in granular media using particle image velocimetry (PIV). A steel pile of 12.7 mm width was driven to a depth of 120 mm in silica sand of 0.6 mm mean particle size in axisymmetric condition. The chamber for the sand was fabricated out of transparent acrylic glass to allow high resolution imaging from front side under diffused illumination condition. Instron material testing system was utilized to drive the pile into the soil with controlled speed while a custom-built imaging system recorded the images for offline processing with PIV algorithms. Before application of the technique to the model pile, PIV parameters were also optimized through a simple translation test. Results for displacement as well as strain field obtained using finite element post-processing are appended as evidence of impact of this study.

The paper presents the work on manufacturing and preliminary characterisation of fibre reinforced composite honeycomb structured composites by 3D printing. The capabilities and limitations of the processing are discussed. The work aims to compare the effectiveness of reinforcement using specimens of similar dimensions produced on the same machine and characterise them. Initially, tensile performance of unprinted fibre and printed fibre has been evaluated. Challenges associated with the testing of the printed specimens are addressed. Bend testing will follow to assess the performance as a composite structure to assess the interaction between fibre, matrix and core. Continuing work is planned to compare the effect of other parameters such as fill pattern and fill density to assess their effect on the composite.

This paper presents a novel method to improve the robotic SLAM by fusing aspects from the RGBD-SLAM and RatSLAM methods. The proposed solution takes the 3D feature representations of the environment much like the RGBD-SLAM system but instead of creating a voxel map, it creates a grid map taking elements from the RatSLAM system. The resulting integration of SLAM methods eliminates the need for a continuous stream of images as required in RGBD-SLAM and thus overcomes the problem of ambiguous data normally generated by featureless surface such as repeating wall patterns. The proposed solution is implemented on a Pioneer 3-DX mobile robot using Kinect sensor. The results show that the proposed method can successfully conduct SLAM in an efficient manner.

Reformer tube is a kind of pressure vessel working under high temperature. It is a major and expensive component in chemical process industry especially in oil and gas industry. Each reformer tube costs over thousands of dollars. A reformer furnace could contain hundreds of over 15-meter long vertically installed reformer tubes working under pressure up to 15 to 20 bar and temperature reaching 700 to 800°C. Any tube failure during production time means a catastrophic production failure and million-dollar lost. Periodic tube inspections are mandatory. Such inspections can call for significant manpower, time, and financial investment in order to meet the national and international legislations and standards for health and safety. This paper presents an approach moving towards automated reformer tube inspection. The approach presents an integrated mechatronic system that consists of five major units: reformer tube sensing, reducer (pigtail) checking, data acquisition, communication, and real time control. Such an integrated tube inspection system has the advantages of measuring both tube body and pigtail using one integrated device, obtaining distortion data in real time and processing data analysis on site to support tube replacement decision making. With the available sensing, communication, and control methodologies and technologies, the proposed integrated reformer tube inspection system could be a feasible and economical solution for plant maintenance in oil and gas industry.

Detailed anatomical models can be produced with consumer-level 3D scanning and printing systems. 3D replication techniques are significant advances for anatomical education as they allow practitioners to more easily introduce diverse or numerous specimens into classrooms. Here we present a methodology for producing anatomical models in-house, with the chondrocranium cartilage from a spiny dogfish (Squalus acanthias) and the skeleton of a cane toad (Rhinella marina) as case studies. 3D digital replicas were produced using two consumer-level scanners and specimens were 3D-printed with selective laser sintering. The fidelity of the two case study models was determined with respect to key anatomical features. Larger-scale features of the dogfish chondrocranium and frog skeleton were all well-resolved and distinct in the 3D digital models, and many finer-scale features were also well-resolved, but some more subtle features were absent from the digital models (e.g. endolymphatic foramina in chondrocranium). All characters identified in the digital chondrocranium could be identified in the subsequent 3D print; however, three characters in the 3D-printed frog skeleton could not be clearly delimited (palatines, parasphenoid and pubis). Characters that were absent in the digital models or 3D prints had low-relief in the original scanned specimen and represent a minor loss of fidelity. Our method description and case studies show that minimal equipment and training is needed to produce durable skeletal specimens. These technologies support the tailored production of models for specific classes or research aims.

Stroke affects approximately 2% of the population, and with advances in modern technology, more patients are surviving the event and requiring rehabilitation, placing further demand on already stretched medical systems. Because of this, an emergent area of research has arisen, investigating the use of robotics as a means to aid in the rehabilitation of patients affected by stroke. Projects such as the MIT Manus have provided evidence of the efficacy of robotic rehabilitation for stroke patients, but further research is required to provide ongoing improvements to this approach. Further to this, mirror therapy, a treatment initially found to be useful in the treatment of phantom pain syndrome in amputees, has also shown promise in the rehabilitation of stroke, though further research into the mechanisms behind mirror therapy need further investigation. A novel prototype robotic rehabilitation system was developed to investigate the integration of these two emergent approaches to stroke rehabilitation as a more comprehensive approach to stroke rehabilitation. This system was developed around a small industrial robot, utilising motion capture and force feedback for control of the robot with a virtual mirror therapy system to provide visual stimulation for the patient. The operation of the prototype was verified, however further development is required to produce a system suitable for patient trials.

This paper examines additive manufacturing technologies in the context of their potential use in flexible manufacturing systems. It reviews which current technologies are capable of producing full-strength production parts. It also examines which technologies might be applicable to FMS and how they might be implemented as part of a hybrid manufacturing cell.

PurposeThe purpose of this paper is to provide details on implementation of inexpensive and accurate automation solution for performing brisket cutting while the sheep/lamb is hanging by forelegs.Design/methodology/approachThe system developed uses 6 Degree of freedom (DOF) industrial manipulator, custom build tool, sterilizer, and other off the shelf products to create a machine, all the parameters in the system are designed to ensure that the highest levels of safety and hygiene standards are met. The primary system has been developed for sheep/lamb.FindingsIt is shown that the system developed enhanced both the productivity and quality of the process, while adhering to the hygiene standard in the meat processing plants.Research limitations/implicationsThe process of precise brisket can be very challenging; the system designed uses customised tools to provide a good model for the trajectory planning.Originality/valueThe system developed uses statistical tools to calculate the correct trajectories.