Search results for: parallel identical machines

Authors: Osamede Asowata, Christo Pienaar, Johan Bekker

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Photovoltaic (PV) modules may become a trend for future PV systems because of their greater flexibility in distributed system expansion, easier installation due to their nature, and higher system-level energy harnessing capabilities under shaded or PV manufacturing mismatch conditions. This is as compared to the single or multi-string inverters. Novel residential scale PV arrays are commonly connected to the grid by a single DC–AC inverter connected to a series, parallel or series-parallel string of PV panels, or many small DC–AC inverters which connect one or two panels directly to the AC grid. With an increasing worldwide interest in sustainable energy production and use, there is renewed focus on the power electronic converter interface for DC energy sources. Three specific examples of such DC energy sources that will have a role in distributed generation and sustainable energy systems are the photovoltaic (PV) panel, the fuel cell stack, and batteries of various chemistries. A high-efficiency inverter using Metal Oxide Semiconductor Field-Effect Transistors (MOSFETs) for all active switches is presented for a non-isolated photovoltaic and AC-module applications. The proposed configuration features a high efficiency over a wide load range, low ground leakage current and low-output AC-current distortion with no need for split capacitors. The detailed power stage operating principles, pulse width modulation scheme, multilevel bootstrap power supply, and integrated gate drivers for the proposed inverter is described. Experimental results of a hardware prototype, show that not only are MOSFET efficient in the system, it also shows that the ground leakage current issues are alleviated in the proposed inverter and also a 98 % maximum associated driver circuit is achieved. This, in turn, provides the need for a possible photovoltaic panel switching technique. This will help to reduce the effect of cloud movements as well as improve the overall efficiency of the system.

Keywords: grid connected photovoltaic (PV), Matlab efficiency simulation, maximum power point tracking (MPPT), module integrated converters (MICs), multilevel converter, series connected converter

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Authors: Myung-Gon Yoon, Jung-Ho Moon, Tae Kwon Ha

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This paper considers a robust stabilization problem of a single agent in a multi-agent consensus system composed of identical agents, when the network topology of the system is completely unknown. It is shown that the transfer function of an agent in a consensus system can be described as a multiplicative perturbation of the isolated agent transfer function in frequency domain. Applying known robust stabilization results, we present sufficient conditions for a robust stabilization of an agent against unknown network topology.

Keywords: single agent control, multi-agent system, transfer function, graph angle

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Authors: Ali Albadri

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The logistics equation has never been used or studied in scientific fields outside the field of ecology. It has never been used to understand the behavior of a dynamic system of mechanical machines, like an escalator. We have studied the compatibility of the logistic map against real measurements from an escalator. This study has proven that there is good compatibility between the logistics equation and the experimental measurements. It has discovered the potential of a relationship between the fractal dimension and the non-linearity parameter, R, in the logistics equation. The fractal dimension increases as the R parameter (non-linear parameter) increases. It implies that the fractal dimension increases as the phase of the life span of the machine move from the steady/stable phase to the periodic double phase to a chaotic phase. The fractal dimension and the parameter R can be used as a tool to verify and check the health of machines. We have come up with a theory that there are three areas of behaviors, which they can be classified during the life span of a machine, a steady/stable stage, a periodic double stage, and a chaotic stage. The level of attention to the machine differs depending on the stage that the machine is in. The rate of faults in a machine increases as the machine moves through these three stages. During the double period and the chaotic stages, the number of faults starts to increase and become less predictable. The rate of predictability improves as our monitoring of the changes in the fractal dimension and the parameter R improves. The principles and foundations of our theory in this work have and will have a profound impact on the design of systems, on the way of operation of systems, and on the maintenance schedules of the systems. The systems can be mechanical, electrical, or electronic. The discussed methodology in this paper will give businesses the chance to be more careful at the design stage and planning for maintenance to control costs. The findings in this paper can be implied and used to correlate the three stages of a mechanical system to more in-depth mechanical parameters like wear and fatigue life.

Keywords: logistcs map, bifurcation map, fractal dimension, logistics equation

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Authors: Jia-Yu Wu, Chih-Han Chang, Shu-Fen Chuang, Rong-Yang Lai

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Objective: This study was to examine the stress distribution of tooth with different class V restorations under different loading situations and geometry by 3D finite element (FE) analysis. `Methods: A series of FE models of mandibular premolars containing class V cavities were constructed using micro-CT. The class V cavities were assigned as the combinations of different cavity depths x occlusal -gingival heights: 1x2, 1x4, 2x2, and 2x4 mm. Three alveolar bone loss conditions were examined: 0, 1, and 2 mm. 200 N force was exerted on the buccal cusp tip under various directions (vertical, V; obliquely 30° angled, O; oblique and parallel the individual occlusal cavity wall, P). A 3-D FE analysis was performed and the von-Mises stress was used to summarize the data of stress distribution and maximum stress. Results: The maximal stress did not vary in different alveolar bone heights. For each geometry, the maximal stress was found at bilateral corners of the cavity. The peak stress of restorations was significantly higher under load P compared to those under loads V and O while the latter two were similar. 2x2mm cavity exhibited significantly increased (2.88 fold) stress under load P compared to that under load V, followed by 1x2mm (2.11 fold), 2x4mm (1.98 fold) and 1x4mm (1.1fold). Conclusion: Load direction causes the greatest impact on the results of stress, while the effect of alveolar bone loss is minor. Load direction parallel to the cavity wall may enhance the stress concentration especially in deep and narrow class cavities.

Keywords: class v restoration, finite element analysis, loading situation, stress

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Authors: Mark Salisbury

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The arrival of artificially intelligent avatars and the automation they bring is worrying many of us, not only for our livelihood but for the jobs that may be lost to our kids. We worry about what our place will be as human beings in this new economy where much of it will be conducted online in the metaverse – in a network of 3D virtual worlds – working with intelligent machines. The Future of Leadership was written to address these fears and show what our place will be – the right place – in this new economy of AI avatars, automation, and 3D virtual worlds. But to be successful in this new economy, our job will be to bring wisdom to our workplace and the marketplace. And we will use AI avatars and 3D virtual worlds to do it. However, this book is about more than AI and the avatars that we will work with in the metaverse. It’s about building Organizational intelligence (OI) -- the capability of an organization to comprehend and create knowledge relevant to its purpose; in other words, it is the intellectual capacity of the entire organization. To increase organizational intelligence requires a new kind of knowledge worker, a wisdom worker, that requires a new kind of leadership. This book begins your story for how to become a leader of wisdom workers and be successful in the emerging wisdom economy. After this presentation, conference participants will be able to do the following: Recognize the characteristics of the new generation of wisdom workers and how they differ from their predecessors. Recognize that new leadership methods and techniques are needed to lead this new generation of wisdom workers. Apply personal and professional values – personal integrity, belief in something larger than yourself, and keeping the best interest of others in mind – to improve your work performance and lead others. Exhibit an attitude of confidence, courage, and reciprocity of sharing knowledge to increase your productivity and influence others. Leverage artificial intelligence to accelerate your ability to learn, augment your decision-making, and influence others.Utilize new technologies to communicate with human colleagues and intelligent machines to develop better solutions more quickly.

Keywords: metaverse, generative artificial intelligence, automation, leadership, organizational intelligence, wisdom worker

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: Esther Burkitt

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Background: Evidence is mounting that mixed emotions can be experienced simultaneously in different ways across the lifespan. Four types of patterns of simultaneously mixed emotions (sequential, prevalent, highly parallel, and inverse types) have been identified in middle childhood and adolescence. Moreover, the recognition of these experiences tends to develop firstly when children consider peers rather than the self. This evidence from children and adolescents is based on examining the presence of experiences specified in adulthood. The present study, therefore, applied an exhaustive coding scheme to investigate whether children experience types of previously unidentified simultaneous mixed emotional experiences. Methodology: One hundred and twenty children (60 girls) aged 7 years 1 month - 9 years 2 months (X=8 years 1 month; SD = 10 months) were recruited from mainstream schools across the UK. Two age groups were formed (youngest, n = 61, 7 years 1 month- 8 years 1 months: oldest, n = 59, 8 years 2 months – 9 years 2 months) and allocated to one of two conditions hearing vignettes describing happy and sad mixed emotion events in age and gender-matched protagonist or themselves. Results: Loglinear analyses identified new types of flexuous, vertical, and other experiences along with established sequential, prevalent, highly parallel, and inverse types of experience. Older children recognised more complex experiences other than the self-condition. Conclusion: Several additional types of simultaneously mixed emotions are recognised in middle childhood. The theoretical relevance of simultaneous mixed emotion processing in childhood is considered, and the potential utility of the findings in emotion assessments is discussed.

Keywords: emotion, childhood, self, other

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Authors: Kyungsuk Cho, H. Y. Kim, S. U. Chae, J. H. Choi

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Technological development has led to the construction of super-tall buildings and insulators are increasingly used as exterior finishing materials to save energy. However, insulators are usually combustible and vulnerable to fire. Fires like that at Wooshin Golden Suite Building in Busan, Korea in 2010 and that at CCTV Building in Beijing, China are the major examples of fire spread accelerated by combustible insulators. The exterior finishing materials of a high-rise building are not made of insulators only, but they are integrated with the building’s external cladding system. There is a limit in evaluating the fire safety of a cladding system with a single small-unit material such as a cone calorimeter. Therefore, countries provide codes to evaluate the fire safety of exterior finishing materials using full-scale tests. This study compares and to examine the applicability of the methods to Korea. Standard analysis showed differences in the type and size of fire sources and duration and exterior finishing materials also differed in size. In order to confirm the differences, fire tests were conducted on identical external cladding systems to compare fire safety. Although the exterior finishing materials were identical, varying degrees of fire spread were observed, which could be considered as differences in the type and size of the fire sources and duration. Therefore, it is deduced that extended studies should be conducted before the evaluation methods and standards are employed in Korea. The two standards for evaluating fire safety provided different results. Peak heat release rate was 5.5MW in ISO method and 3.0±0.5MW in BS method. Peak heat release rate in ISO method continued for 15 minutes. Fire ignition, growth, full development and decay evolved for 30 minutes in BS method where wood cribs were used as fire sources. Therefore, follow-up studies should be conducted to determine which of the two standards provides fire sources that approximate the size of flames coming out from the openings or those spreading to the outside when a fire occurs at a high-rise building.

Keywords: external cladding systems, fire safety evaluation, ISO 13785-2, BS 8414

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Authors: Nidhi Chadha, A. K. Tiwari, Marilyn D. Milton, Anil K. Mishra

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Translocator protein (18 kDa) TSPO is highly expressed during microglia activation in neuroinflammation. Although a number of PET ligands have been developed for the visualization of activated microglia, one of the advantageous approaches is to develop potential optical imaging (OI) probe. Our study involves computational screening, synthesis and evaluation of TSPO ligand through various imaging modalities namely PET/SPECT/Optical. The initial computational screening involves pharmacophore modeling from the library designing having oxo-benzooxazol-3-yl-N-phenyl-acetamide groups and synthesis for visualization of efficacy of these compounds as multimodal imaging probes. Structure modeling of monomer, Ala147Thr mutated, parallel and anti-parallel TSPO dimers was performed and docking analysis was performed for distinct binding sites. Computational analysis showed pattern of variable binding profile of known diagnostic ligands and NBMP via interactions with conserved residues along with TSPO’s natural polymorphism of Ala147→Thr, which showed alteration in the binding affinity due to considerable changes in tertiary structure. Preliminary in vitro binding studies shows binding affinity in the range of 1-5 nm and selectivity was also certified by blocking studies. In summary, this skeleton was found to be potential probe for TSPO imaging due to ease in synthesis, appropriate lipophilicity and reach to specific region of brain.

Keywords: TSPO, molecular modeling, imaging, docking

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Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

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Authors: Christa Fricke, Sibylle Meyer, Gert G. Wagner

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Our research focuses on the question of whether assistive and social robotics could pose a promising strategy to support the independent living of elderly people and potentially relieve relatives of any anxieties. To answer the question of how elderly people perceive the potential of robotics, we analysed the data from the Berlin Aging Study BASE-II (https://www.base2.mpg.de/de) (N=1463) and data from the German SYMPARTNER study (http://www.sympartner.de) (N=120) and compared those to a control group made up of people younger than 30 years (BASE II: N=241; SYMPARTNER: N=30). BASE-II is a cohort study of people living in Berlin, Germany. The sample covers more than 2200 cases; a questionnaire on the use and acceptance of assistive and social robots was carried out with a sub-sample of 1463 respondents in 2015. The SYMPARTNER study was done by SIBIS institute of Social Research, Berlin and included a total of 120 persons between the ages of 60 and 87 in Berlin and the rural German federal state of Thuringia. Both studies included a control group of persons between the ages of 20 and 35 (BASE II: N=241; SYMPARTNER: N=30). Additional data, representative for the whole population in Germany, will be surveyed in fall 2017 (Survey “Technikradar” [technology radar] by the National Academy of Science and Engineering). Since this survey is including some identical questions as BASE-II/SYMPARTNER, comparative results can be presented at 20th International Conference on Social Robotics in New York 2018. The complexity of the data gathered in BASE-II and SYMPARTNER, encompassing detailed socio-economic background characteristics as well as personality traits such as the personal attitude to risk taking, locus of control and Big Five, proves highly valuable and beneficial. Results show that participants’ expressions of resentment against robots are comparatively low. Participants’ personality traits play a role, however the effect sizes are small. Only 15 percent of participants received domestic robots with great scepticism. Participants aged older than 70 years expressed greatest rejection of the robotic assistant. The effect sizes however account for only a few percentage points. Overall, participants were surprisingly open to the robot and its usefulness. The analysis also shows that men’s acceptance of the robot is generally greater than that of women (with odds ratios of about 0.6 to 0.7). This applies to both assistive robots in the private household and in care environments. Men expect greater benefits of the robot than women. Women tend to be more sceptical of their technical feasibility than men. Interview results prove our hypothesis that men, in particular of the age group 60+, are more accustomed to delegate household chores to women. A delegation to machines instead of humans, therefore, seems palpable. The answer to the title question of this planned presentation is: social and assistive robots at home robots are not only accepted by men – but by fewer women than men.

Keywords: acceptance, care, gender, household

Procedia PDF Downloads 176

Authors: Mamouni Mohammed Dhiya Eddine

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This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

Procedia PDF Downloads 195

Authors: Anthony I. Otuonye, Juliet N. Odii, Perpetual N. Ibe

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The obvious challenges faced by most commercial bank customers while using the services of ATMs (Automated Teller Machines) across developing countries have triggered the need for an improved system with better security features. Current ATM systems are password-based, and research has proved the vulnerabilities of these systems to heinous attacks and manipulations. We have discovered by research that the security of current ATM-assisted banking services in most developing countries of the world is easily broken and maneuvered by fraudsters, majorly because it is quite difficult for these systems to identify an impostor with privileged access as against the authentic bank account owner. Again, PIN (Personal Identification Number) code passwords are easily guessed, just to mention a few of such obvious limitations of traditional ATM operations. In this research work also, we have developed a system of fingerprint biometrics with PIN code Authentication that seeks to improve the security features of traditional ATM installations as well as other Banking Services. The aim is to ensure better security at all ATM installations and raise the confidence of bank customers. It is hoped that our system will overcome most of the challenges of the current password-based ATM operation if properly applied. The researchers made use of the OOADM (Object-Oriented Analysis and Design Methodology), a software development methodology that assures proper system design using modern design diagrams. Implementation and coding were carried out using Visual Studio 2010 together with other software tools. Results obtained show a working system that provides two levels of security at the client’s side using a fingerprint biometric scheme combined with the existing 4-digit PIN code to guarantee the confidence of bank customers across developing countries.

Keywords: fingerprint biometrics, banking operations, verification, ATMs, PIN code

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Authors: Oibar Martinez, Clara Oliver, Jose Miguel Miranda

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In this paper, we discuss the standard improvements which can be made to reduce the earth resistance in difficult terrains for optimum lightning protection, what are the practical limitations, and how the modeling can be refined for accurate diagnostics and ground resistance minimization. Ground resistance minimization can be made via three different approaches: burying vertical electrodes connected in parallel, burying horizontal conductive plates or meshes, or modifying the own terrain, either by changing the entire terrain material in a large volume or by adding earth-enhancing compounds. The use of vertical electrodes connected in parallel pose several practical limitations. In order to prevent loss of effectiveness, it is necessary to keep a minimum distance between each electrode, which is typically around five times larger than the electrode length. Otherwise, the overlapping of the local equipotential lines around each electrode reduces the efficiency of the configuration. The addition of parallel electrodes reduces the resistance and facilitates the measurement, but the basic parallel resistor formula of circuit theory will always underestimate the final resistance. Numerical simulation of equipotential lines around the electrodes overcomes this limitation. The resistance of a single electrode will always be proportional to the soil resistivity. The electrodes are usually installed with a backfilling material of high conductivity, which increases the effective diameter. However, the improvement is marginal, since the electrode diameter counts in the estimation of the ground resistance via a logarithmic function. Substances that are used for efficient chemical treatment must be environmentally friendly and must feature stability, high hygroscopicity, low corrosivity, and high electrical conductivity. A number of earth enhancement materials are commercially available. Many are comprised of carbon-based materials or clays like bentonite. These materials can also be used as backfilling materials to reduce the resistance of an electrode. Chemical treatment of soil has environmental issues. Some products contain copper sulfate or other copper-based compounds, which may not be environmentally friendly. Carbon-based compounds are relatively inexpensive and they do have very low resistivities, but they also feature corrosion issues. Typically, the carbon can corrode and destroy a copper electrode in around five years. These compounds also have potential environmental concerns. Some earthing enhancement materials contain cement, which, after installation acquire properties that are very close to concrete. This prevents the earthing enhancement material from leaching into the soil. After analyzing different configurations, we conclude that a buried conductive ring with vertical electrodes connected periodically should be the optimum baseline solution for the grounding of a large size structure installed on a large resistivity terrain. In order to show this, a practical example is explained here where we simulate the ground resistance of a conductive ring buried in a terrain with a resistivity in the range of 1 kOhm·m.

Keywords: grounding improvements, large scale scientific instrument, lightning risk assessment, lightning standards

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Authors: Ahmed Tawfik

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Oxidation of 1,4 dioxane produces metabolites by-products involving glycolaldehyde and acids that have geno- and cytotoxicity impact on microbial degradation. Thereby, the incorporation of algae with bacteria in the treatment system would eliminate and overcome the accumulation of metabolites that are utilized as a carbon source for the build-up of biomass. Therefore, the aim of the present study is to assess the potential of algae/bacteria-based membrane bioreactor (AB-MBR) for biodegradation of 1,4 dioxane-rich wastewater at a high imposed loading rate. Three identical reactors, i.e., AB-MBR1, AB-MBR2, and AB-MBR3, were operated in parallel at 1,4 dioxane loading rates of 641.7, 320.9, and 160.4 mg/L. d., and HRTs of 6.0, 12 and 24 h. respectively. The AB-MBR1 achieved 1,4 dioxane removal rate of 263.7 mg/L.d., where the residual value in the treated effluent amounted to 94.4±22.9 mg/L. Reducing the 1,4 dioxane loading rate (LR) to 320.9 mg/L.d in the AB-MBR2 maximized the removal rate efficiency of 265.9 mg/L.d., with a removal efficiency of 82.8±3.2%. The minimum value of 1,4 dioxane of 17.3±1.8 mg/L in the treated effluent of AB-MBR3 was obtained at an HRT of 24.0 h and loading rate of 160.4 mg/L.d. The mechanism of 1,4 dioxane degradation in AB-MBR was a combination of volatilization (8.03±0.6%), UV oxidation (14.1±0.9%), microbial biodegradation (49.1±3.9%) and absorption/uptake and assimilation by algae (28.8±2.%). Further, the Thioclava, Afipia, and Mycobacterium genera oxidized and produced the required enzymes for hydrolysis and cleavage of the dioxane ring into 2-hydroxy-1,4 dioxane. Moreover, the fungi, i.e., Basidiomycota and Cryptomycota, played a big role in the degradation of the 1,4 dioxane into 2-hydroxy-1,4 dioxane. Xanthobacter and Mesorhizobium were involved in the metabolism process by secreting alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), and glycolate oxidase. Bacteria and fungi produced dehydrogenase (DH) for the transformation of 2-hydroxy-1,4 dioxane into 2-hydroxy-ethoxyacetaldehyde. The latter is converted into Ethylene glycol by Aldehyde hydrogenase (ALDH). Ethylene glycol is oxidized into acids using Alcohol hydrogenase (ADH). The Diatomea, Chlorophyta, and Streptophyta utilize the metabolites for biomass assimilation and produce the required oxygen for further oxidation of the dioxane and its metabolites by-products of bacteria and fungi. The major portion of metabolites (ethylene glycol, glycolic acid, and oxalic acid were removed due to uptake and absorption by algae (43±4.3%), followed by adsorption (18.4±0.9%). The volatilization and UV oxidation contribution for the degradation of metabolites were 8.7±0.7% and 12.3±0.8%, respectively. The capabilities of genera Defluviimonas, Thioclava, Luteolibacter, and Afipia. The genera of Defluviimonas, Thioclava, Luteolibacter, and Mycobacterium were grown under a high 1,4 dioxane LR of 641.7 mg/L.d. The Chlorophyta (4.1-43.6%), Streptophyta (2.5-21.7%), and Diatomea (0.8-1.4%) phyla were dominant for degradation of 1,4 dioxane. The results of this study strongly demonstrated that the bioremediation and bioaugmentation process can safely remove 1,4 dioxane from industrial wastewater while minimizing environmental concerns and reducing economic costs.

Keywords: wastewater, membrane bioreactor, bacterial community, algal community

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Authors: Pranab Kumar Goswami, Elena Gurung

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Small and medium enterprises (SME) are considered as the driving force for the economic growth of a developing country like India. Most of the SMEs are located in residential/non-industrial areas to avoid legal obligations of occupational safety and health (OSH) provisions. This study was conducted in Delhiwith a view to analyze the accidents that occurredduringthe year 2019 & 2020. The objective of the study was to find out the accident prone SMEs in Delhi and major causes of such accidents. Methods: Survey and comprehensive data analysis methods, followed by applying simple statistical techniques, were used for this study. The accident reports for the study period collected from the labour department and police stations were analyzed for the study. The injured workers were interviewed to ascertain safety compliances, training and awareness programs, etc. The study was completed in March2021. Results: It was found that most of the accidents took place in SMEs located in residential/non- industrial areas in Delhi. The accident-prone machines were found to be power presses (42%) and injection moulding machines (37%). Predominantly unsafe machinery or unsafe working conditions and lack of training of worker were observed to be the major causes of accidents in such industries. Conclusions: It was concluded from the study that unsafe machinery/equipment and lack of proper training to the workers were two main reasons for increase in accidents.It was also concluded that the industries located in industrial areas were better placed in terms of workplace compliances. The managements who were running their operations from residential/non-industrial areaswere found to be less aware on health and safety issues. Lack of enforcement by government agencies in such areas has escalated this problem. Adequate training to workers, managing safe & healthy workplace, and sustained enforcement can reduce accidents in such industries.

Keywords: SME, accident prevention, cause of accident, unorganised

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Authors: Shiji Hu, Lei Li, Wanting Zhou, DaoHong Yang

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The data encryption, is the foundation of today’s communication. On this basis, how to improve the speed of data encryption and decryption is always a problem that scholars work for. In this paper, we proposed an elliptic curve crypto processor architecture based on SM2 prime field. In terms of hardware implementation, we optimized the algorithms in different stages of the structure. In finite field modulo operation, we proposed an optimized improvement of Karatsuba-Ofman multiplication algorithm, and shorten the critical path through pipeline structure in the algorithm implementation. Based on SM2 recommended prime field, a fast modular reduction algorithm is used to reduce 512-bit wide data obtained from the multiplication unit. The radix-4 extended Euclidean algorithm was used to realize the conversion between affine coordinate system and Jacobi projective coordinate system. In the parallel scheduling of point operations on elliptic curves, we proposed a three-level parallel structure of point addition and point double based on the Jacobian projective coordinate system. Combined with the scalar multiplication algorithm, we added mutual pre-operation to the point addition and double point operation to improve the efficiency of the scalar point multiplication. The proposed ECC hardware architecture was verified and implemented on Xilinx Virtex-7 and ZYNQ-7 platforms, and each 256-bit scalar multiplication operation took 0.275ms. The performance for handling scalar multiplication is 32 times that of CPU(dual-core ARM Cortex-A9).

Keywords: Elliptic curve cryptosystems, SM2, modular multiplication, point multiplication.

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

Procedia PDF Downloads 215

Authors: Maxim Glushenkov, Alexander Kronberg

Abstract:

Isobaric expansion (IE) process is an alternative to conventional gas/vapor expansion accompanied by a pressure decrease typical of all state-of-the-art heat engines. The elimination of the expansion stage accompanied by useful work means that the most critical and expensive parts of ORC systems (turbine, screw expander, etc.) are also eliminated. In many cases, IE heat engines can be more efficient than conventional expansion machines. In addition, IE machines have a very simple, reliable, and inexpensive design. They can also perform all the known operations of existing heat engines and provide usable energy in a very convenient hydraulic or pneumatic form. This paper reports measurement made with the engine operating as a heat-to-shaft-power or electricity converter and a comparison of the experimental results to a thermodynamic model. Experiments were carried out at heat source temperature in the range 30–85 °C and heat sink temperature around 20 °C; refrigerant R134a was used as the engine working fluid. The pressure difference generated by the engine varied from 2.5 bar at the heat source temperature 40 °C to 23 bar at the heat source temperature 85 °C. Using a differential piston, the generated pressure was quadrupled to pump hydraulic oil through a hydraulic motor that generates shaft power and is connected to an alternator. At the frequency of about 0.5 Hz, the engine operates with useful powers up to 1 kW and an oil pumping flowrate of 7 L/min. Depending on the temperature of the heat source, the obtained efficiency was 3.5 – 6 %. This efficiency looks very high, considering such a low temperature difference (10 – 65 °C) and low power (< 1 kW). The engine’s observed performance is in good agreement with the predictions of the model. The results are very promising, showing that the engine is a simple and low-cost alternative to ORC plants and other known energy conversion systems, especially at low temperatures (< 100 °C) and low power range (< 500 kW) where other known technologies are not economic. Thus low-grade solar, geothermal energy, biomass combustion, and waste heat with a temperature above 30 °C can be involved into various energy conversion processes.

Keywords: isobaric expansion, low-grade heat, heat engine, renewable energy, waste heat recovery

Procedia PDF Downloads 187

Authors: K. X. Cheng, A. L. Goh, K. T. Ooi

Abstract:

The effectiveness of microchannels in enhancing heat transfer has been demonstrated in the semiconductor industry. In order to tap the microscale heat transfer effects into macro geometries, overcoming the cost and technological constraints, microscale passages were created in macro geometries machined using conventional fabrication methods. A cylindrical insert was placed within a pipe, and geometrical profiles were created on the outer surface of the insert to enhance heat transfer under steady-state single-phase liquid flow conditions. However, while heat transfer coefficient values of above 10 kW/m2·K were achieved, the heat transfer enhancement was accompanied by undesirable pressure drop increment. Therefore, this study aims to address the high pressure drop issue using Constructal theory, a universal design law for both animate and inanimate systems. Two designs based on Constructal theory were developed to study the effectiveness of Constructal features in reducing the pressure drop increment as compared to parallel channels, which are commonly found in microchannel fabrication. The hydrodynamic and heat transfer performance for the Tree insert and Constructal fin (Cfin) insert were studied using experimental methods, and the underlying mechanisms were substantiated by numerical results. In technical terms, the objective is to achieve at least comparable increment in both heat transfer coefficient and pressure drop, if not higher increment in the former parameter. Results show that the Tree insert improved the heat transfer performance by more than 16 percent at low flow rates, as compared to the Tree-parallel insert. However, the heat transfer enhancement reduced to less than 5 percent at high Reynolds numbers. On the other hand, the pressure drop increment stayed almost constant at 20 percent. This suggests that the Tree insert has better heat transfer performance in the low Reynolds number region. More importantly, the Cfin insert displayed improved heat transfer performance along with favourable hydrodynamic performance, as compared to Cfinparallel insert, at all flow rates in this study. At 2 L/min, the enhancement of heat transfer was more than 30 percent, with 20 percent pressure drop increment, as compared to Cfin-parallel insert. Furthermore, comparable increment in both heat transfer coefficient and pressure drop was observed at 8 L/min. In other words, the Cfin insert successfully achieved the objective of this study. Analysis of the results suggests that bifurcation of flows is effective in reducing the increment in pressure drop relative to heat transfer enhancement. Optimising the geometries of the Constructal fins is therefore the potential future study in achieving a bigger stride in energy efficiency at much lower costs.

Keywords: constructal theory, enhanced heat transfer, microchannel, pressure drop

Procedia PDF Downloads 307

Authors: Javed Mallick

Abstract:

In metropolitan areas, rapid changes in land use and land cover (LULC) have ecological and environmental consequences. Saudi Arabia's cities have experienced tremendous urban growth since the 1990s, resulting in urban heat islands, groundwater depletion, air pollution, loss of ecosystem services, and so on. From 1990 to 2020, this study examines the variance and heterogeneity in land surface temperature (LST) caused by LULC changes in Abha-Khamis Mushyet, Saudi Arabia. LULC was mapped using the support vector machine (SVM). The mono-window algorithm was used to calculate the land surface temperature (LST). To identify LST clusters, the local indicator of spatial associations (LISA) model was applied to spatiotemporal LST maps. In addition, the parallel coordinate (PCP) method was used to investigate the relationship between LST clusters and urban biophysical variables as a proxy for LULC. According to LULC maps, urban areas increased by more than 330% between 1990 and 2018. Between 1990 and 2018, built-up areas had an 83.6% transitional probability. Furthermore, between 1990 and 2020, vegetation and agricultural land were converted into built-up areas at a rate of 17.9% and 21.8%, respectively. Uneven LULC changes in built-up areas result in more LST hotspots. LST hotspots were associated with high NDBI but not NDWI or NDVI. This study could assist policymakers in developing mitigation strategies for urban heat islands

Keywords: land use land cover mapping, land surface temperature, support vector machine, LISA model, parallel coordinate plot

Procedia PDF Downloads 48

Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

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In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

Procedia PDF Downloads 22

Authors: Saule Mussabekova

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Recent advances in genetics have allowed increasing acutely the capacities of the formation of reliable evidence in conducting forensic examinations. Thus, traces of biological origin are important sources of information about a crime. Currently, around the world, sexual offenses have increased, and among them are those in which the criminals use various detergents to remove traces of their crime. A feature of modern synthetic detergents is the presence of biological additives - enzymes. Enzymes purposefully destroy stains of biological origin. To study the nature and extent of the impact of modern washing powders on saliva stains on the physical evidence, specially prepared test specimens of different types of tissues to which saliva was applied have been examined. Materials and Methods: Washing machines of famous manufacturers of household appliances have been used with different production characteristics and advertised brands of washing powder for test washing. Over 3,500 experimental samples were tested. After washing, the traces of saliva were identified using modern research methods of forensic medicine. Results: The influence was tested and the dependence of the use of different washing programs, types of washing machines and washing powders in the process of establishing saliva trace and identify of the stains on the physical evidence while washing was revealed. The results of experimental and practical expert studies have shown that in most cases it is not possible to draw the conclusions in the identification of saliva traces on physical evidence after washing. This is a consequence of the effect of biological additives and other additional factors on traces of saliva during washing. Conclusions: On the basis of the results of the study, the feasibility of saliva traces of the stains on physical evidence after washing is established. The use of modern molecular genetic methods makes it possible to partially solve the problems arising in the study of unlaundered evidence. Additional study of physical evidence after washing facilitates detection and investigation of sexual offenses against women and children.

Keywords: saliva research, modern synthetic detergents, laundry detergents, forensic medicine

Procedia PDF Downloads 192

Authors: E. Ramprasath, P. Manojkumar, P. Veena

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DC motors have been widely used in the past centuries which are proudly known as the workhorse of industrial systems until the invention of the AC induction motors which makes a huge revolution in industries. Since then, the use of DC machines have been decreased due to enormous factors such as reliability, robustness and complexity but it lost its fame due to the losses. A new methodology is proposed to construct a DC motor through the simulation in LabVIEW to get an idea about its real time performances, if a change in parameter might have bigger improvement in losses and reliability.

Keywords: analysis, characteristics, direct current motor, LabVIEW software, simulation

Procedia PDF Downloads 522

Authors: Nina Øystad-Larsen, Miran Cemalovic, Amir M. Kaynia

Abstract:

The nonlinear static and dynamic analysis procedures presented in EN 1998-1 for the structural response of a RC wall-frame building are assessed. The structure is designed according to the guidelines for high ductility (DCH) in 1998-1. The finite element packages SeismoStruct and OpenSees are utilized and evaluated. The structural response remains nearly in the elastic range even though the building was designed for high ductility. The overstrength is a result of oversized and heavily reinforced members, with emphasis on the lower storey walls. Nonlinear response history analysis in the software packages give virtually identical results for displacements.

Keywords: behaviour factor, dual system, OpenSEES, overstrength, seismostruct

Procedia PDF Downloads 384

Authors: S. Jalaja, A. M. Vijaya Prakash

Abstract:

Recursive combination of an algorithm based on Karatsuba multiplication is exploited to design a generalized transpose and parallel Finite Impulse Response (FIR) Filter. Mid-range Karatsuba multiplication and Carry Save adder based on Karatsuba multiplication reduce time complexity for higher order multiplication implemented up to n-bit. As a result, we design modified N-tap Transpose and Parallel Symmetric FIR Filter Structure using Karatsuba algorithm. The mathematical formulation of the FFA Filter is derived. The proposed architecture involves significantly less area delay product (APD) then the existing block implementation. By adopting retiming technique, hardware cost is reduced further. The filter architecture is designed by using 90 nm technology library and is implemented by using cadence EDA Tool. The synthesized result shows better performance for different word length and block size. The design achieves switching activity reduction and low power consumption by applying with and without retiming for different combination of the circuit. The proposed structure achieves more than a half of the power reduction by adopting with and without retiming techniques compared to the earlier design structure. As a proof of the concept for block size 16 and filter length 64 for CKA method, it achieves a 51% as well as 70% less power by applying retiming technique, and for CSA method it achieves a 57% as well as 77% less power by applying retiming technique compared to the previously proposed design.

Keywords: carry save adder Karatsuba multiplication, mid range Karatsuba multiplication, modified FFA and transposed filter, retiming

Procedia PDF Downloads 205

Authors: Michel Kulhandjian, Dimitris A. Pados

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The objective of this work is to develop a theoretical framework for reliable digital recording system identification from digital audio files alone, for forensic purposes. A digital recording system consists of a microphone and a digital sound processing card. We view the cascade as a system of unknown transfer function. We expect same manufacturer and model microphone-sound card combinations to have very similar/near identical transfer functions, bar any unique manufacturing defect. Input voice (or other) signals are modeled as non-stationary processes. The technical problem under consideration becomes blind deconvolution with non-stationary inputs as it manifests itself in the specific application of digital audio recording equipment classification.

Keywords: blind system identification, audio fingerprinting, blind deconvolution, blind dereverberation

Procedia PDF Downloads 282

Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

Abstract:

This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

Procedia PDF Downloads 86

Authors: Kyeong-Ri Ko, Seong Bong Bae, Jang Sik Choi, Sung Bum Pan

Abstract:

A simple method for testing the posture imbalance of the human body is to check for differences in the bilateral shoulder and pelvic height of the target. In this paper, to check for spinal disorders the authors have studied ways to establish a motion capture system to obtain and express motions of 4-joints, and to acquire data based on this system. The 4 sensors are attached to the both shoulders and pelvis. To verify the established system, the normal and abnormal postures of the targets listening to a lecture were obtained using the established 4-joint based motion capture system. From the results, it was confirmed that the motions taken by the target was identical to the 3-dimensional simulation.

Keywords: inertial sensor, motion capture, motion data acquisition, posture imbalance

Procedia PDF Downloads 489

Authors: Haroon Jan Khan, Xian-Feng Xu, Syed Nasir Shah, Anooshay Niazi

Abstract:

CNC machines are not only used on a large scale but also now become a prominent necessity among households and smaller businesses. Printed Circuit Boards manufactured by the chemical process are not only risky and unsafe but also expensive and time-consuming. A 3-axis precise CNC machine has been developed, which not only fabricates PCB but has also been used for multi-tasks just by changing the materials used and tools, making it versatile. The advanced CNC machine takes data from CAM software. The TB-6560 controller is used in the CNC machine to adjust variation in the X, Y, and Z axes. The advanced machine is efficient in automatic drilling, engraving, and cutting.

Keywords: CNC, G-code, CAD, CAM, Proteus, FLATCAM, Easel

Procedia PDF Downloads 129