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Graphene sheets are the basis of nanoelectromechanical (NEMS) mass resonators that are in recent years experimentally used for detection of specific gas molecules in air. The aim of this paper is to theoretically investigate the possibility of application of graphene sheets in detection of Chemical Warfare Agents (CWA’s). By application of the nonlocal theory of elasticity and classical plate theory, equations that describe natural vibrations of the simply supported single-layer graphene sheet (SLGS) and double-layer graphene sheet (DLGS) were derived. In order to detect attached CWA molecule, the frequency shift method was applied. The results indicate that the proposed methodology could be successfully implemented in order to detect an attached CWA molecule. However, only specific mode shapes could be employed for such detection.

INTRODUCTION: Machine learning algorithms and in silico models for the COVID-19 have been used to classify infectious people and predict their condition in time. OBJECTIVES: This study aims at creating a personalized model that combines machine learning and finite element simulation approach in order to predict development of COVID-19 infection in patients. METHODS: The methodology combines several aspects (1) classification of patients into several classes of clinical condition (2) segmentation of human lungs in X ray images (3) finite element simulation to investigate the spreading of SARS-COV-2 virion in the lungs. RESULTS: The findings show accuracy larger than 90% in all aspects of methodology. FE simulation has revealed that the distribution of airflow in the lung changes in time with the infection. CONCLUSION: The key benefit of our proposed method is that it combines several methods that will be further improved in order to create a truly unique combined methodology for predictive models in patients infected with COVID-19.

Simple Summary One of the main challenges in the application of Machine Learning in medicine is data collection. Either due to ethical concerns or lack of patients, data may be scarce. In this paper Deep Convolutional Generative Adversarial Networks (DCGAN) have been applied for the purpose of data augmentation. Images of bladder mucosa are used in order to generate new images using DCGANs. Then, combination of original and generated images are used to train AlexNet and VGG16 architectures. The results show improvements in AUC score in some cases, or equal scores with apparent lowering of standard deviation across data folds during cross-validation; indicating networks trained with the addition of generated data have a lower sensitivity across the hyperparameter range. Abstract Urinary bladder cancer is one of the most common urinary tract cancers. Standard diagnosis procedure can be invasive and time-consuming. For these reasons, procedure called optical biopsy is introduced. This procedure allows in-vivo evaluation of bladder mucosa without the need for biopsy. Although less invasive and faster, accuracy is often lower. For this reason, machine learning (ML) algorithms are used to increase its accuracy. The issue with ML algorithms is their sensitivity to the amount of input data. In medicine, collection can be time-consuming due to a potentially low number of patients. For these reasons, data augmentation is performed, usually through a series of geometric variations of original images. While such images improve classification performance, the number of new data points and the insight they provide is limited. These issues are a motivation for the application of novel augmentation methods. Authors demonstrate the use of Deep Convolutional Generative Adversarial Networks (DCGAN) for the generation of images. Augmented datasets used for training of commonly used Convolutional Neural Network-based (CNN) architectures (AlexNet and VGG-16) show a significcan performance increase for AlexNet, where AUCmicro reaches values up to 0.99. Average and median results of networks used in grid-search increases. These results point towards the conclusion that GAN-based augmentation has decreased the networks sensitivity to hyperparemeter change.

COVID-19 represents one of the greatest challenges in modern history. Its impact is most noticeable in the health care system, mostly due to the accelerated and increased influx of patients with a more severe clinical picture. These facts are increasing the pressure on health systems. For this reason, the aim is to automate the process of diagnosis and treatment. The research presented in this article conducted an examination of the possibility of classifying the clinical picture of a patient using X-ray images and convolutional neural networks. The research was conducted on the dataset of 185 images that consists of four classes. Due to a lower amount of images, a data augmentation procedure was performed. In order to define the CNN architecture with highest classification performances, multiple CNNs were designed. Results show that the best classification performances can be achieved if ResNet152 is used. This CNN has achieved AUCmacro&macr, and AUCmicro&macr, up to 0.94, suggesting the possibility of applying CNN to the classification of the clinical picture of COVID-19 patients using an X-ray image of the lungs. When higher layers are frozen during the training procedure, higher AUCmacro&macr, values are achieved. If ResNet152 is utilized, AUCmacro&macr, values up to 0.96 are achieved if all layers except the last 12 are frozen during the training procedure.

Research on the implementation of inductive proximity sensors in active magnetic bearings is performed in this paper. LDC1000 digital sensors manufactured by Texas Instruments are used since they claim to provide precision measured in microns and simple acquisition of the output data. The Sensor chip is connected with the sensing coil which is placed inside the magnetic bearing, close to electromagnets. This newly developed system created a platform for research in signal quality and its resistance to electrical noise. The controller used in this application was Texas Instruments TMS320F28335 digital signal processor (DSP). Software for data acquisition from LDC1000 was written and implemented in DSP using Code Composer Studio development environment. Two different output data are acquired and processed: proximity data and frequency count. Graphs presented in this paper show different resistance to electrical noise. A conclusion derived from this research can be applied in an industry where electromagnetic noise exists, together with the need for precise distance measurement.

Despite the various hardware and software improvements in Cloud architecture, there still exists the huge performance gap between the commodity supercomputers and Cloud when running HPC communication intensive applications. In order to find what is preventing them to better scale on Cloud, we evaluated HPL and NAMD benchmarks on HPE Openstack testbed, and NAMD benchmarks on supercomputer located at Rijeka University Supercomputing Center. Our results revealed two major bottlenecks: the throughput of the interconnect, and Cloud orchestration layer, among other responsible for the management of the communication between Cloud instances. We investigated the influence of jittering, but did not find the significant influence on performance. Our conclusion is that by solely increasing the interconnect throughput, one will not improve the scalability of HPC communication intensive HPC applications in Cloud. This is also backed up with NAMD performed at HP Labs, and with HPL benchmark performed at San Diego Supercomputing Center. We propose two possible scenarios of scalability improvements. One with distributed model of Cloud Orchestration layer ; another with bare metal containers. Efficient load balancing remains the must if we want to see HPC applications scaling over many million Cloud cores. For this, we propose novel SLEM based load balancing strategy.

This paper should give overview of the software system Modelica in practice of modeling SCARA type robot. Comparison of the modeled robot will be pres ented with a commercially available robotic system. The main objective of this study was to determine the pos sibility of using the Modelica system that is based on Open Source technology in the development of robotic systems. Aim of this paper is to provide a review of the use of Modelica in virtual laboratory for the purpose of enabling sustainable economic practicum for students.

The goal of the paper is to present an outline of different modeling approach at determining of backward extrusion force on AlCu5PbBi material and to compare them with experimental obtained results. Stochastic modeling in the paper is based on the statistic processing of central composite experimental design i.e. in this investigations Central Composite Circumscribed (CCC) design. The numerical modeling is based on the Finite Element Method (FEM) using ABAQUS 6.4.1. Explication the software.

Zadnjih je godina vidljiv ulazak High-Performance Computing u klaster tipove robnih servera sustava. U isto vrijeme svjedočimo računarstvu u oblacima kao dokazanoj, stabilnoj i pouzdanoj IT paradigmi koja rabi virtualizirane klastere robnih servera kao ključne komponente. U radu se daje analiza svojstava kod primjene direktne prirodne u odnosu na virtualnu HPC MPI aplikaciju na području HPC aplikacija opće uporabe virtualizacijom InfiniBanda via IpoIB na nivou virtualnog stroja na VMware ESXi kao i KVM hypervisora uz podršku aktivne migracije spremne na proizvodnju. Aplikacije za razne male i srednje HPC klastere usmjerene su na korisnike, imajući u vidu potpunu virtualizaciju IT infrastrukture povezujući infrastrukturu opće namjene s HPC IT infrastrukturom. Aktivna migracija je ključna komponenta u okviru virtualiziranog okruženja budući da omogućuje dinamičku virtualnu IT infrastrukturu. Stoga se djelovanje svojstava aktivne migracije procjenjuje kroz arhitekturu s više platformi na slučaju proaktivne uporabe greška-tolerancija., Over recent years we have seen a constant evolution of High-Performance Computing moving into commodity servers cluster types of systems. At the same time we have seen Cloud Computing being a proven, stable and reliable IT paradigm, utilising virtualized clusters of commodity servers as key components. This paper presents a face-to-face native-to-virtual HPC MPI application performance analysis on a range of general-use HPC applications by virtualizing InfiniBand via IPoIB at the guest virtual machine level on VMware ESXi as well as KVM hypervisor with production ready live migration support. Applications running on various small and medium HPC clusters are targeted to address users, considering full IT infrastructure virtualization by merging general purpose with HPC IT infrastructure. Live migration is a key component within a virtualized environment as it enables dynamic virtual IT infrastructure, therefore live migration performance impact is evaluated through a pluggable multi-platform architecture on a proactive fault-tolerance use case.

U posljednje je vrijeme zamjetan veliki interes HPC (High Performance Computing) zajednice prema Cloud Computing paradigmi, odnosno računalstvu u oblacima. Mnoge su prednosti izvođenja HPC aplikacija u računalnom oblaku, od kojih su najvažnije bolje korištenje računalnih resursa, učinkovita naplata njihovog korištenja, te dinamička i bez prekida u radu aplikacije preraspodjela računalnih resursa. Bez obzira na očite prednosti Cloud Computing okruženja za HPC, trenutni omjer korištenja HPC aplikacija u računalnim oblacima u odnosu na one koje se izvode u tradicionalnom HPC okruženju još je uvijek vrlo malen. Neki od razloga za takvo stanje su očiti, dok kod drugih nije tako. Tako na primjer tradicionalni proizvođači HPC opreme i aplikacija još uvijek pokušavaju iskoristiti njihova ulaganja u postojeća rješenja na način koji pogoduje tradicionalnom načinu rada HPC-a. Nadalje, iako je prisutan snažan razvoj virtualizacijske tehnologije, još uvijek postoje otvorena pitanja, poput skaliranja HPC aplikacija u virtualnom okruženju, te suradnje između fizičkih i virtualnih resursa. Tu se također nameće i pitanje podrške standardnih HPC alata za uspostavu virtualiziranih okolina. Na kraju, ali ne i manje važno, pojava heterogenog HPC računalstva koje se zasniva na kombinaciji standardnih procesora (CPU) i onih specijalizirane namjene (GPU procesori i akceleratori) nameće izazovna pitanja, poput skalabilnosti, učinkovitog Linpack mjerenja performansi, te razvoja HPC aplikacija u heterogenom CPU/GPU okolišu. Uz sve to, unatoč tome što mnogi proizvođači HPC opreme i aplikacija govore o tome kako imaju potpuno funkcionalna HPC rješenja u računalnim oblacima, postoji potreba da se osigura odgovore i na dodatna pitanja: Jesu li potpuno ispunjena obećanja mogućnosti virtualizacije svih komponenti sustava, ne samo onih virtualnih, nego i fizičkih? Koje vrste računalnih oblaka su podržane: privatne, javne ili njihova kombinacija, tj. hibridni oblaci? Kako dobro pojedina HPC aplikacija skalira na nekom računalnom oblaku? U pokušaju odgovora na postavljena pitanja, u ovom radu je dat pregled trenutnih HPC rješenja u oblacima. Osim toga, namjera ovog rada je da posluži kao vodič za onoga tko je spreman napraviti pomak od standardnih HPC rješenja prema onima u Cloud Computing okruženju. Naposljetku, da bi se što je moguće više olakšao izbor HPC Cloud rješenja, predložena je njihova klasifikacija u tri kategorije, od kojih svaka reflektira područja i načine primjene pojedinih rješenja, stupanj podržanosti virtualizacije, te, zbog uglavnom javno nedostupnih rezultata mjerenja performansi, do sada iskazanu HPC ekspertizu proizvođača tih rješenja., In the last years a strong interest of the HPC (High Performance Computing) community raised towards cloud computing. There are many apparent benefits of doing HPC in a cloud, the most important of them being better utilization of computational resources, efficient charge back of used resources and applications, on-demand and dynamic reallocation of computational resources between users and HPC applications, and automatic bursting of additional resources when needed. Surprisingly, the amount of HPC cloud solutions related to standard solutions is still negligible. Some of the reasons for the current situation are evident, some not so. For example, traditional HPC vendors are still trying to exploit their current investment as much as possible, thus favoring traditional way of doing HPC. The next, although virtualization techniques are developing in ever increasing rate, there are still open questions, like scaling of HPC applications in virtual environment, collaboration between physical and virtual resources, and support of the standard HPC tools for virtualized environments. At last but not the least, the advent of GPU computing has raised difficult questions even in the traditional and well developed HPC segment, like scalability, development of HPC GPU based applications. In addition, because many HPC vendors are speaking about already having a fully functional HPC cloud solution, there is a need to provide answers to the following questions: Are they fulfilling virtualization promises, both physical and virtual? Which type of clouds do they support: private, public or both, i.e. hybrid clouds? How well HPC applications scale on their cloud solutions? This paper is an overview of the current HPC cloud solutions, for sure not complete and solely a view of authors, however intended to be a helpful compass for someone trying to shift from standard HPC to large computations in cloud environments.

The subject of this paper is investigation of steel X5CrNiMo 17-12-2 in a deep drawing process. Material and mechanical properties are investigated in order to obtain a number of parameters that are needed for the deep drawing process. Tolerances for final product dimensions were taken and a procedure for deep drawing process was calculated. Tooling was modelled with Solidworks software. Experiments were performed in order to determine functionality of tooling, feasibility and influential factors on process uncertainties.

The direction for the future development of the production process is complete autonomy, artificial intelligence, ability to diagnose errors, self-repair and, most importantly, to minimize impact of human factors. Although technology is not yet mature enough for a complete exclusion of worker from the machining process remote control could enable unmanned operation. The concept offered in this study consists of building a custom WEB application for machine tool control that provides flexibility, operation from any remote location, ensures platform independence and low cost due to use of Open Source Architecture.

Trenje je neizbježna pojava u svim postupciima plastičnog deformiranja metala i ima negativan utjecaj na parametre procesa, radni vijek alata, kao i kvalitetu radnog komada. U hladnom prostornom deformiranju veliki pritisci djeluju između alata i radnog komada. Ovi pritisci mogu biti limitirajući faktor prilikom primjene tehnologija deformiranja. Smanjenjem kontaktnog trenja, smanjuju se i kontaktni pritisci. Poznavanje parametara trenja (faktora trenja µ i/ili omjera trenja m) je od velikog značaja prilikom proračuna parametara procesa (npr. sila ili energija) i odabira odgovarajućeg sredstva za podmazivanje, kao i numeričku simulaciju obrade. Postoje mnogobrojne metode za određivanje parametara trenja u obradama deformiranjem. Neke od ovih metoda opisane su u ovom radu. Također je predstavljen i novi model za određivanje parametara trenja u obradama deformiranjem. U radu je izvršeno i mjerenje sile trenja u procesu protusmjernog istiskivanja za različite vrste maziva., Friction occurs in all metal forming operations and, in general, it has a negative impact on process parameters, die life, as well as workpiece quality. In cold metal forming processes high interface pressures between die and material take place. These pressures can be the limiting factor of application of cold forming. By reducing interfacial friction, contact pressures can be reduced too. Knowledge of friction amount (factor of friction µ and/or friction ratio m) is essential for calculation of the main process parameters (load, energy), for choosing a proper lubricant but also for numerical modelling of forming operations. There exist a number of experimental methods to determine friction in metal forming processes. Current paper deals with the possibilities to evaluate friction. It analyses and assesses a number of existing friction models in cold metal operations. Proposal of a new friction model for cold metal forming operations is presented and discussed. Measurement of friction force in backward extrusion for different lubrication conditions was also preformed.

This paper includes investigation of measuring methods for flatness on an aluminum housing filter produced with the procedure of casting. Several methods were taken in consideration for the flatness investigation. Comparison of measurements of flatness has been made, measured with CMM (Coordinate Measuring Machine), marble table and comparator. In this paper we can see that the method of the CMM is the most suitable for measurements in serial production. It can be the only right method for measuring of flatness. The maximum number of point’s necessary to achieve quality measurement is analyzed. For measurement purposes made in this paper are used the laboratories of production facilities of the “Cimos” company and laboratory of the Technical Faculty in Rijeka. The results and method are given for further flatness research for this specific part is presented.

The paper presents the methodology and approach of interconnection between University and Industry. Application of HPC for industry solution, with a focus on application of hybrid technology (CPU and GPGPU).

The main target of this paper is to find out the most suitable device for measurements of roughness of aluminum parts during the production process. Measurement and investigation are made on following devices MarSurf GD 25, PCE-1200 RT. The measurements were conducted on six pieces selected from one production cycle. Comparisons of results are presented in graphical and numerical tables and best device is selected.

This article presents a new approach for multi-objective design of the manufacturing system shopfloor. The proposed model for multi-objective design is based on the Emergent Synthesis approach. Emergent Synthesis related approaches use both, bottom-up and top-down features, unlike traditional analytical, deterministic approaches based on top-down problem decomposing. Based on the proposed approach a simulation model has been built and analysed. The Genetic Algorithm (GA) has been implemented in the proposed model for in final optimization process. From the obtained results of the simulation it can be concluded that with the utilization of the proposed approach for adaptable design the model has a high level of multi-objective adaptation in the design of the manufacturing system shopfloor. One of the major characteristics of the here proposed approach for multi-objective design of the manufacturing system is that the model has the ability for a simultaneous influence on the design and adaptation of the shop-floor layout and that it adapts to scheduling rules.

U članku je dana analiza između nekolicine modernih inteligentnih proizvodnih sustava poput: biološkog, holonskog (HMS), fraktalnog (FrMS) te ubiquitous proizvodne koncepcije. Na brzorastućim tržištima ključna je fleksibilnost proizvodnih sustava kako bi se što učinkovitije moglo odgovoriti na promjene nastale u tržišnom okruženju. Dan je detaljan prikaz karakteristika navedenih sustava, te su navedene njihove komparativne prednosti i nedostaci. Prikazani su utjecajni čimbenici i dane su smjernice za daljnji nastavak istraživanja., This article gives an analysis of a few modern intelligent production systems: biological, holon (HMS), fractal (FrMS) and ubiquitous production concepts. The key to success in modern fast growing systems is a flexibility of the production system in order to respond quickly to changes within the market. A detail representation of the characteristics as well as the advantages and disadvantages for these systems is given. Influential factors have been listed as well as guidelines for further research.

New environmental characteristics and requirements have challenged manufacturing enterprises to improve the efficiency and productivity of their production activities. Cellular manufacturing (CM) as one of the solutions to this problem, as implementation of Group technology (GT), was proposed. Performance of cellular manufacturing systems depends heavily on the cell structure. In this paper we present and evaluate a novel approach for solving the cell-formation problem based on implementation of a GA, called modified genetic algorithm (MGA). Implementation of the GA in here presented simulation model is based on Emergent Synthesis idea, of top-down problem decomposition and emerging solution from bottom-up feedback.

The aim of the research presented in this paper is to test the efficiency of the proposed genetic algorithm in the fast or real-time optimizations. Proposed partial genome fitness evaluation mechanism was tested on the wireless network topology optimization and job shop scheduling problem (JSSP). Wireless network topology optimization requires frequent and very fast (sometimes real time) adjustments. Job shop scheduling problem is one of the most general and difficult of all traditional scheduling problems. Search based on traditional genetic algorithms usually are not suitable in solving these problems. Long computational time and high memory usage if a large population and/or a large number of generations are used, on the other hand, a larger population and a larger number of generations usually provide better results. In comparison with two other similar and commonly used genetic the proposed algorithms have significant improvements in speed and some case solution quality.

This paper presents a approach for multi-objective design and reconfiguration of the current manufacturing system. A proposed model for multi-objective design and adaptable reconfiguration is based on the multi-agent principles and Emergent Synthesis concept. Emergent Synthesis is introduced in the adaptable reconfiguration within implementation of the layered based architecture and utilizing the multi-agent concept. Based on the proposed approach a simulation model has been built and evaluated. For the purpose of analysis of this approach it was simulated production in the shop-floor of the manufacturing system with the two different initial configurations. For evaluation of here presented approach the case study was performed using realistic data ; it was simulated production of the cellular phone devices. From obtained results of the simulation it can be conclude that a proposed model has a high level of multi-objective adaptation of the manufacturing system shop-floor.

Metal forming technology has been applied to effective production of metallic components in various fields. One of the newer metal forming techniques is so called „joining by forming“. With this method two or more separate parts are joined together using plastic deformation. Self-piercing riveting, clinching and coin and medal production are some of the joining by forming operations, which have been successfully applied in industry. The present study is bound to a process of joining of two bimetallic axisymmetric components from various materials by upsetting bimetallic components in a closed die. The external component is a ring and the central part is a cylinder – like element. By upsetting those two elements in closed die, inseparable workpiece has been obtained. Therefore, two different cases (geometries) have been investigated. In the first case the simple ring and profiled inner cylinder are combined while in the second case vice versa combination is applied. Also, forming load, material flow and filling of joint section were analyzed. The process has been investigated experimentally. In short, current investigation has yielded considerable insight into the process of joining two metallic components.

In this paper the radioscopic measurements of a die cast product the fuel filter (C4001469SE) support is investigated. Alloy AlSi9Cu3 is investigated for porosity with X - ray machine. The used measurement instrument was X - ray machine YXLON CABINET 1200. An investigation of material composition was also conducted in order to detect elements that influence porosity occurrence. The measurement conditions and plan used for selected measurement procedure are discussed. The results are compared with ASTM E505 standard reference radiographs for inspection of aluminium and magnesium die casting.

The accurate clamping and locating is essential in factory automation process. Fast localization of strategic placement of structure elements for 3-2-1 fixture based on genetic algorithm and milling tool path is presented. Travelling salesmen method is used for a 2D tool path search. A final design of an optimised placement is also shown with improved overall workpiece force and deflection influence.

In this paper we have presented a new method for preliminary (initial) optimization of the jig design for milling processes. Main reason for proposing this approach is shortening the time needed for preparation of the production process. In this method we have used GA in combination with TSP and classical 3-2-1 design method for obtaining the optimal solution of the process of design.

The focus of this paper will be on comparison at the measurement of container lids between Advanced TOpometric Optical Sensor - ATOS III SO (GOM mbH) and traditional coordinate measuring machine CMM for the measurement of surfaces - Form Talysurf Series 2 (Taylor Hobson Ltd). In the paper, two kinds of measuring methods (noncontact method at ATOS and contact method at CMM Form Talysurf) and techniques will be made for comparison: digitizing measuring system based on the triangulation principle and traditional measuring systems based on the collecting of points from an object by touching it.

This paper presents a system for automatic beam light detection from oncoming vehicles traveling in the opposite direction to the vehicle in which the system is implemented. The system is designed to operate during low light conditions (at night), with the goal to automatically change light intensity from high beam to low beam when a vehicle is detected. An approach using artificial neural network for image classification is proposed and implemented and test results are given in the paper. Furthermore, directions for future work and conclusions are presented.

The purpose of this research is to focus on the solution of the resource sizing problem for the real production system. The resource sizing problem is tackled by usage of the mathematical makespan minimization method and comparative simulations of the two different production models. Only two production model simulations were realized due to specificities of the handled production system. Simulation results were presented, compared and discussed. This paper presents an approach which allows studying the heavy machine sizing problem realistically, through the use of simulation tools. The approach used would be of great help in making a decision on whether two new heavy machines should be introduced into an existing production system or not.

Članak se bavi eksperimentalnim ispitivanjem rezne sposobnosti izmjenjivih reznih umetaka. Testirano je 11 tipova izmjenjivih reznih umetaka od pet različitih proizvođača. Ispitivani su rezni umetci bili istog oblika a razlikovali su se naročito po materijalu i vrsti površinskog sloja. Glavni je cilj bio izabrati odgovarajući test za određivanje rezne sposobnosti zamjenjivih reznih umetaka te kreirati takav postupak ispitivanja koji bi omogućio usporedbu i ocjenu rezne sposobnosti odabranih reznih umetaka. Nakon ispitivanja izvršeni su potrebni proračuni za usporedbu rezne sposobnosti i bilježenje trošenja alata korištenjem mikroskopa. Uspoređena je i prodiskutirana rezna sposobnost., The article deals with experimental testing of the cutting ability of exchangeable cutting inserts. Eleven types of exchangeable cutting inserts from five different manufacturers were tested. The tested cutting inserts were of the same shape and were different especially in material and coating types. The main aim was both to select a suitable test for determination of the cutting ability of exchangeable cutting inserts and to design such testing procedure that could make it possible to compare and evaluate the cutting ability of the selected cutting inserts. After the testing the necessary calculations were performed for comparison of the cutting abilities and recording the tool-wear using a microscope. The cutting ability was compared and discussed.

SMEs are in general highly flexible and agile in order to accommodate the customer demands in the paradigm of High Mix-Low Volume manufacturing. The flexibility and agility have mainly been enabled by manual labor, but as we are entering the technology and data driven fourth industrial revolution, where augmented operators and machines work in cooperation in a highly flexible and productive manufacturing system both an opportunity and a need has raised for developing highly flexible and efficient automation.

Proceedings of International Conference on I nnovative Technologies, IN-TECH 2014

ost of current high performanc e today are based only on CPU, but usage of accelerators and coprocessors are rapidly gaining acceptance in the last few years since they are used to boost performance and lower power consumption. There is a large number of high performance processors available: CPUs, GPUs, MICs, DSPs, FPGAs... each with its own char acteristics, advantages and disadvantages.

The paper presents a digital control system based on the TMS320F2812 digital signal processor. The role of this system is to allow easier and faster development and testing of advanced control structures for synchronous generator connected to the power network. The code development is supported by two software tools where the code can be developed in the C/C++ programming language or in a graphical environment. New generation of digital signal controllers together with the software programing tools offers good platform in area of development complex control algorithms and laboratory testing of new control strategies for synchronous generator excitation control.

In this study novel method of recording the true stress – strain curves, originally derived from well known hydraulic bulging test has been critically reconsidered. New method allows more accurate determination of membrane stress in the deforming material. Assumption on the bulk geometry is no longer needed since modification, using sphere as an obstacle, determines the radius of curvature needed in acquisition of membrane stress. Use of the small transducer integrated in tooling, enables acquisition of force and thus reliable stress acquisition upon the known (spherical) geometry. Performing modified hydraulic bulging upon just one test specimen yields three points of stress-strain curve. Two different sheet thicknesses and two different sphere diameters have been researched in attempt to establish whether the assumption of membrane stress can be somewhat neglected or disregarded. The modified method has proved to be adequate for checking the numerical model, because it enables direct experimental measurement of the true stresses in the material, which cannot be obtained when classical hydraulic bulging test is performed.