Journal articles on the topic 'Other industrial, systems and processes engineering'
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NIKOLAEV, M. YU, V. A. ZAKHARENKO, E. V. NIKOLAEVA, and A. K. NIKITIN. "MODELING OF INTERACTION PROCESSES AND METROLOGY IN ELECTRIC PULSE SYSTEMS." Actual Issues Of Energy 3, no. 1 (2021): 058–62. http://dx.doi.org/10.25206/2686-6935-2021-3-1-58-62.
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Electro-pulse systems have an undeniable number of advantages, since they use eddy-current non-contact interaction of the electromagnetic field of the inductor with electrically conductive surfaces. The resulting intense and high-speed deformation creates instantaneous (10-4 - 10-5c) mechanical overloads that destroy the bonds of substances with surfaces, without violating the mechanical strength of the surfaces themselves. Such systems can be used in construction, mechanical engineering, railway transport, heat and power engineering and other areas of industrial activity to remove various materials from the walls and structural elements of equipment, including icicles and ice from the eaves and roofs of houses, which is an effective, low-cost and technological method.
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BENNEYAN, JAMES C., and CLAIRE BOND. "SYSTEMS ENGINEERING APPROACHES FOR IMPROVING REUSABLE MEDICAL EQUIPMENT REPROCESSING PROCESSES." International Journal of Innovation and Technology Management 10, no. 03 (June 2013): 1340009. http://dx.doi.org/10.1142/s0219877013400099.
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Hospital reusable medical equipment (RME) includes any items that are intended to be reprocessed and reused indefinitely, including surgical instruments, dental equipment, endoscopes, and others. Such equipment represent a significant portion of a hospital's inventory costs and recently have generated significant patient cross-contamination concerns due to reprocessing cleaning failures. This paper discusses recent applications of industrial and systems engineering (ISyE) methods within healthcare organizations to help manage, understand, and improve RME processes, including quality control (QC), reliability, patient safety, facility layout, queuing networks, and inventory management models. Several examples demonstrate the value of these approaches for improved reprocessing management of RME technology.
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Bogdanic, Grozdana. "Group contribution methods for estimating the properties of polymer systems." Chemical Industry 60, no. 11-12 (2006): 287–305. http://dx.doi.org/10.2298/hemind0612289b.
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Polymer materials are nowadays used in a wide range of technological applications. Reliable knowledge of the thermo physical properties of pure polymers and their mixtures in the whole composition and a wide temperature and pressure range determines whether a given polymer is suitable for a specific application. On the other hand, accurate knowledge of the thermodynamic properties of the systems is a vital prerequisite for computer-aided syntheses, design, and the optimization of industrial polymer processes. However, the experimental data on polymer solubility are often scarce, and at this point, thermodynamics provide a powerful tool for modeling and extrapolating the experimental data. These models, together with factual data banks, are powerful software tools for the reliable development of chemical processes and other applications of industrial interest. The status of the different approaches and important applications of industrial interest using thermodynamic information derived from data banks or by using predictive thermodynamic models are presented in this review.
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Hawryluk, Marek, and Jacek Ziemba. "Lubrication in hot die forging processes." Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology 233, no. 5 (June 28, 2018): 663–75. http://dx.doi.org/10.1177/1350650118784728.
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This article presents selected aspects of lubricant application, as well as lubrication methods and devices in the context of forging tool durability and accessories used in die forging processes at elevated temperatures. The properties and applications of the currently used lubricating and cooling agents in selected industrial forging processes were analyzed. The authors’ original studies on the influence of lubricant application, dose size, time and feed direction as well as other factors affecting tribological conditions are also presented. A review of lubricating and cooling systems and devices is provided, as well as a lubricating device built on the basis of the authors’ knowledge and experience is presented. The developed system, implemented into an industrial process, makes it possible to select and maintain its optimal tribological conditions through the control of the size and frequency of the administered lubricant dose. It may be an alternative to the manual lubricant application method, where human error is a factor, or to fully automated, but expensive, lubrication systems.
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Popovic, Ana, Sonja Milicevic, Vladan Milosevic, Branislav Ivosevic, Jelena Carapic, Vladimir Jovanovic, and Dragan Povrenovic. "Fenton process in dispersed systems for industrial wastewater treatment." Chemical Industry 73, no. 1 (2019): 47–62. http://dx.doi.org/10.2298/hemind181019005p.
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Industrial wastewater contains recalcitrant organic compounds with a very complex chemical structure, built of molecules with long chains of carbon atoms and attached different functional groups. Chemical or biological treatments used for removal of these compounds are being replaced with more efficient non-commercial wastewater treatments. Advanced oxidation processes overcome limitations of conventional methods regarding formation of by-products during degradation of recalcitrant organic compounds. The Fenton process, or use of the Fenton?s reagent, has became one of the most utilized processes due to simplicity, economy and accessible amounts of ferrous iron and hydrogen-peroxide, which are used in the process. In specific, the Fenton?s reagent is a catalytic-oxidative mixture of these two components. The ferrous iron Fe2+ initiates and catalyzes decomposition of H2O2, resulting in generation of hydroxyl radicals, which are the main radical species in the process able to detoxify several organic pollutants by oxidation. In addition, other mechanisms besides formation of hydroxyl radicals may occur during the Fenton process and participate in degradation of target pollutants. Generally, the treatment efficiency relies upon the physical and chemical properties of target pollutants and the process operating conditions. The main disadvantage of the Fenton process is production of sludge formed by iron hydroxide at certain pH values. An alternative solution for this problem is application of this process in fluidized bed reactors. This paper presents an overview of Fenton and photo-Fenton processes in dispersed systems for removal of different industrial wastewater pollutants. The most important process parameters, required for efficient degradation of recalcitrant organic compounds are also described, such as the catalyst type, pH value, temperature, H2O2 concentration and retention time. Strict control of Fenton process parameters in fluidized bed reactors at desired values can bring these systems to the commercial use.
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Zuev, A. S., M. A. Makushchenko, M. E. Ivanov, and E. S. Merkulov. "Extended reality technology – a new component in industrial engineering and production systems." Russian Technological Journal 8, no. 4 (August 6, 2020): 46–65. http://dx.doi.org/10.32362/2500-316x-2020-8-4-46-65.
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Extended (virtual, augmented and mixed) reality technology gets considered as a new universal component of production (industrial) engineering’s methodological basis, receiving the possibilities for wide use in both extensive and intensive development of carrying and other branches of the fourth, fifth and the forming nucleus of the sixth technological wave. The article gives grounds for the role and place of this kind of technology in contemporary technological processes and production systems (including the flexible, small-volume and discrete production), and in the context of cyberphysical systems and the incoming fourth industrial revolution. The authors describe underline the set of tasks that are universal for a wide range of branches in any national economy, that can be most efficiently completed in terms of the current and prognosed level of development of man-machine interaction can be provided for as a result of using VR, AR and MR technologies. Based on the comparison of implementation principles and examples of applied implementation, the article gives grounds for term correspondence and opportunities of use of “extended reality technology”. The authors have made and explained the conclusion on practicability of integrating extended reality technology based on a universal hardwaresoftware complex that provides VR, AR and MR services corresponding to the composition of a given task within the technological process or the operating mode chosen by a user. The article gives descriptions of task assignments, terms of conduct and results of experiments on designing and testing extended reality interactive environments performed at the institute of information technology RTU MIREA in 2019–2020.
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Kannengiesser, Udo, and John S. Gero. "What distinguishes a model of systems engineering from other models of designing? An ontological, data-driven analysis." Research in Engineering Design 33, no. 2 (January 15, 2022): 129–59. http://dx.doi.org/10.1007/s00163-021-00382-9.
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AbstractThis paper investigates how the core technical processes of the INCOSE model of systems engineering differ from other models of designing used in the domains of mechanical engineering, software engineering and service design. The study is based on fine-grained datasets produced using mappings of the different models onto the function-behaviour-structure (FBS) ontology. By representing every model uniformly, the same statistical analyses can be carried out independently of the domain of the model. Results of correspondence analysis, cumulative occurrence analysis and Markov model analysis show that the INCOSE model differs from the other models in its increased emphasis on requirements and on behaviours derived from structure, in the uniqueness of its verification and validation phases, and in some patterns related to the temporal development and frequency distributions of FBS design issues.
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Rudas, Imre J. "Intelligent Engineering Systems." Journal of Advanced Computational Intelligence and Intelligent Informatics 2, no. 3 (June 20, 1998): 69–71. http://dx.doi.org/10.20965/jaciii.1998.p0069.
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Building intelligent systems has been one of the great challenges since the early days of human culture. From the second half of the 18th century, two revolutionary changes played the key role in technical development, hence in creating engineering and intelligent engineering systems. The industrial revolution was made possible through technical advances, and muscle power was replaced by machine power. The information revolution of our time, in turn, canbe characterized as the replacement of brain power by machine intelligence. The technique used to build engineering systems and replace muscle power can be termed "Hard Automation"1) and deals with industrial processes that are fixed and repetitive in nature. In hard automation, the system configuration and the operations are fixed and cannot be changed without considerable down-time and cost. It can be used, however, particularly in applications calling for fast, accurate operation, when manufacturing large batches of the same product. The "intelligent" area of automation is "Soft Automation," which involves the flexible, intelligent operation of an automated process. In flexible automation, the task is programmable and a work cell must be reconfigured quickly to accommodate a product change. It is particularly suitable for plant environments in which a variety of products is manufactured in small batches. Processes in flexible automation may have unexpected or previously unknown conditions, and would require a certain degree of "machine" intelligence to handle them.The term machine intelligence has been changing with time and is machinespecific, so intelligence in this context still remains more or less a mysterious phenomenon. Following Prof. Lotfi A. Zadeh,2) we consider a system intelligent if it has a high machine intelligence quotient (MIQ). As Prof. Zadeh stated, "MIQ is a measure of intelligence of man-made systems," and can be characterized by its well defined dimensions, such as planning, decision making, problem solving, learning reasoning, natural language understanding, speech recognition, handwriting recognition, pattern recognition, diagnostics, and execution of high level instructions.Engineering practice often involves complex systems having multiple variable and multiple parameter models, sometimes with nonlinear coupling. The conventional approaches for understanding and predicting the behavior of such systems based on analytical techniques can prove to be inadequate, even at the initial stages of setting up an appropriate mathematical model. The computational environment used in such an analytical approach is sometimes too categoric and inflexible in order to cope with the intricacy and complexity of real-world industrial systems. It turns out that, in dealing with such systems, one must face a high degree of uncertainty and tolerate great imprecision. Trying to increase precision can be very costly.In the face of the difficulties above, Prof. Zadeh proposes a different approach for Machine Intelligence. He separates Hard Computing techniques based Artificial Intelligence from Soft Computing techniques based Computational Intelligence.•Hard computing is oriented toward the analysis and design of physical processes and systems, and is characterized by precision, formality, and categorization. It is based on binary logic, crisp systems, numerical analysis, probability theory, differential equations, functional analysis, mathematical programming approximation theory, and crisp software.•Soft computing is oriented toward the analysis and design of intelligent systems. It is based on fuzzy logic, artificial neural networks, and probabilistic reasoning, including genetic algorithms, chaos theory, and parts of machine learning, and is characterized by approximation and dispositionality.In hard computing, imprecision and uncertainty are undesirable properties. In soft computing, the tolerance for imprecision and uncertainty is exploited to achieve an acceptable solution at low cost, tractability, and a high MIQ. Prof. Zadeh argues that soft rather than hard computing should be viewed as the foundation of real machine intelligence. A center has been established - the Berkeley Initiative for Soft Computing (BISC) - and he directs it at the University of California, Berkeley. BISC devotes its activities to this concept.3) Soft computing, as he explains2),•is a consortium of methodologies providing a foundation for the conception and design of intelligent systems,•is aimed at formalizing of the remarkable human ability to make rational decision in an uncertain, imprecise environment.The guiding principle of soft computing, given by Prof. Zadeh2) is: Exploit the tolerance for imprecision, uncertainty, and partial truth to achieve tractability, robustness, low solution cost, and better rapport with reality.Fuzzy logic is mainly concerned with imprecision and approximate reasoning, neurocomputing mainly with learning and curve fitting, genetic computation mainly with searching and optimization and probabilistic reasoning mainly with uncertainty and propagation of belief. The constituents of soft computing are complementary rather than competitive. Experience gained over the past decade indicates that it can be more effective to use them combined, rather than exclusively.Based on this approach, machine intelligence, including artificial intelligence and computational intelligence (soft computing techniques) is one pillar of Intelligent Engineering Systems. Hundreds of new results in this area are published in journals and international conference proceedings. One such conference, organized in Budapest, Hungary, on September 15-17, 1997, was titled'IEEE International Conference on Intelligent Engineering Systems 1997' (INES'97), sponsored by the IEEE Industrial Electronics Society, IEEE Hungary Section, Bá{a}nki Doná{a}t Polytechnic, Hungary, National Committee for Technological Development, Hungary, and in technical cooperation with the IEEE Robotics & Automation Society. It had around 100 participants from 29 countries. This special issue features papers selected from those papers presented during the conference. It should be pointed out that these papers are revised and expanded versions of those presented.The first paper discusses an intelligent control system of an automated guided vehicle used in container terminals. Container terminals, as the center of cargo transportation, play a key role in everyday cargo handling. Learning control has been applied to maintaining the vehicle's course and enabling it to stop at a designatedlocation. Speed control uses conventional control. System performance system was evaluated by simulation, and performance tests slated for a test vehicle.The second paper presents a real-time camera-based system designed for gaze tracking focused on human-computer communication. The objective was to equip computer systems with a tool that provides visual information about the user. The system detects the user's presence, then locates and tracks the face, nose and both eyes. Detection is enabled by combining image processing techniques and pattern recognition.The third paper discusses the application of soft computing techniques to solve modeling and control problems in system engineering. After the design of classical PID and fuzzy PID controllers for nonlinear systems with an approximately known dynamic model, the neural control of a SCARA robot is considered. Fuzzy control is discussed for a special class of MIMO nonlinear systems and the method of Wang generalized for such systems.The next paper describes fuzzy and neural network algorithms for word frequency prediction in document filtering. The two techniques presented are compared and an alternative neural network algoritm discussed.The fifth paper highlights the theory of common-sense knowledge in representation and reasoning. A connectionist model is proposed for common-sense knowledge representation and reasoning, and experimental results using this method presented.The next paper introduces an expert consulting system that employs software agents to manage distributed knowledge sources. These individual software agents solve users' problems either by themselves or thorough mutual cooperation.The last paper presents a methodology for creating and applying a generic manufacturing process model for mechanical parts. Based on the product model and other up-to-date approaches, the proposed model involves all possible manufacturing process variants for a cluster of manufacturing tasks. The application involves a four-level model structure and Petri net representation of manufacturing process entities. Creation and evaluation of model entities and representation of the knowledge built in the shape and manufacturing process models are emphasised. The proposed process model is applied in manufacturing process planning and production scheduling.References:1) C. W. De Silva, "Automation Intelligence," Engineering Application of Artificial Intelligence, 7-5, 471-477, (1994).2) L. A. Zadeh, "Fuzzy Logic, Neural Networks and Soft Computing," NATO Advanced Studies Institute on Soft Computing and Its Application, Antalya, Turkey, (1996).3) L. A. Zadeh, "Berkeley Initiative_in Soft Computing," IEEE Industrial Electronics Society Newsletter. 41-3, 8-10, (1994).
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Alperin, Boris, Inna Zibareva, and Aleksey Vedyagin. "CRIS Systems in Research Organization Administrating." Science Management: Theory and Practice 4, no. 1 (March 28, 2022): 143–56. http://dx.doi.org/10.19181/smtp.2022.4.1.8.
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Complementary to storage, management and exchange of scientific metadata, the CRIS system SciAct of the Boreskov Institute of Catalysis by means of special modules provides online support for a number of standard business processes regarding to research organization’s (RO) everyday administrating. The processes cover: preparing of expert judgments on research materials submitting for publication; preparing of applications on filling of vacant positions, together with conducting of corresponding competitions; conducting of open or / and secret voting of Academic and Dissertation Councils including generating of corresponding protocols; administrating of documents and procedures regarding to postgraduateeducation; as well as some other processes. This substantially simplifies inner document flow of RO and facilitates personnel’s online / remote work from the one hand; and provides comfortable conditions for genuine research activities from the other hand. Flexibility of the SciAct system allows embracing of additional business processes, as well as already realized its exploitation at other ROs.
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Ziegler, Lynn R., and Richard C. Dorf. "An analysis of the geometry of light-striping vision systems for feedrate control in robot welding and other industrial processes." Robotics 3, no. 2 (June 1987): 167–73. http://dx.doi.org/10.1016/0167-8493(87)90004-0.
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Klochkov, Yu V., S. D. Fomin, O. V. Vakhnina, T. A. Sobolevskaya, M. Yu Klochkov, and A. S. Andreev. "Finite element modeling of the processes of elastic-plastic deformation of reclamation objects of the agro-industrial complex." IOP Conference Series: Earth and Environmental Science 965, no. 1 (January 1, 2022): 012049. http://dx.doi.org/10.1088/1755-1315/965/1/012049.
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Abstract Annotation. To study the processes of nonlinear deformation of reclamation objects and engineering systems of the agro-industrial complex, taking into account the plastic stage of the used structural material, a finite element model was created based on a volumetric prismatic discretization element with quadrangular bases. The plastic stage of deformation of the applied structural material of the object is taken into account on the basis of the provisions of the deformation theory of plasticity. The plasticity matrix at the (j + 1)-th stage of sequential loading was compiled as a result of applying the operation of differentiating the stress tensor components accumulated over the j previous stages of sequential loading with respect to the strain tensor components. The stiffness matrix and the column of nodal forces of a prismatic discretization element with quadrangular bases at the (j + 1)-th stage of loading were obtained by minimizing the Lagrange functional. Numerical experiments on the calculation of a tubular outlet proved the adequacy of the developed finite element model and the accuracy of calculating the required strength parameters of the studied reclamation objects and other engineering systems of the agro-industrial complex, sufficient for engineering practice.
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Song, Zhengyi, and Young Moon. "Performance analysis of CyberManufacturing Systems." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 233, no. 5 (May 18, 2017): 1362–76. http://dx.doi.org/10.1177/0954405417706996.
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CyberManufacturing System is an advanced vision for future manufacturing where physical components are fully integrated and seamlessly networked with computational processes, forming an on-demand, intelligent, and communicative manufacturing resource and capability repository with optimal and sustainable manufacturing solutions. The CyberManufacturing System utilizes recent developments in Internet of things, cloud computing, fog computing, service-oriented technologies, among others. Manufacturing resources and capabilities can be encapsulated, registered, and connected to each other directly or through the Internet, thus enabling intelligent behaviors of manufacturing components and systems such as self-awareness, self-prediction, self-optimization, and self-configuration. This research presents an introduction to the CyberManufacturing System, establishing the architecture and functions of the CyberManufacturing System, designing the pivotal control strategy, and investigating the performance analysis of the CyberManufacturing System using modeling and simulation techniques. In total, five component-level examples and one system-level case study have been developed and used for illustration and validation of the CyberManufacturing System operations. The results show that the CyberManufacturing System is superior to other types of manufacturing systems in terms of functionality and cooperative performance.
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Setiyo, Muji, Tuessi Ari Purnomo, Dori Yuvenda, Muhammad Kunta Biddinika, Nor Azwadi Che Sidik, Olusegun David Samuel, Aditya Kolakoti, and Alper Calam. "Industry 4.0: Challenges of Mechanical Engineering for Society and Industry." Mechanical Engineering for Society and Industry 1, no. 1 (July 21, 2021): 3–6. http://dx.doi.org/10.31603/mesi.5309.
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Today, in the industry 4.0 era, the boundaries of scientific disciplines are blurred, everything seems to be interrelated and shows the ability to be combined. Intelligent sensors combined with Artificial Intelligence (AI) have demonstrated their ability to influence processes, design, and maintenance in manufacturing systems. Mechanical engineering tasked with solving complex engineering problems must be able to adapt to this transformation, especially in the use of digital and IT to combine the principles of physics and engineering mathematics with materials science to design, analyze, manufacture, and maintain mechanical systems. On the other hand, mechanical engineering must also contribute to a better future life. Therefore, one of the keys to consistently playing a role is to think about sustainability, in order to provide benefits for society and industry, in any industrial era.
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Tomov, Pancho, and Lubomir Dimitrov. "THE ROLE OF DIGITAL INFORMATION MODELS FOR HORIZONTAL AND VERTICAL INTERACTION IN INTELLIGENT PRODUCTION." Facta Universitatis, Series: Mechanical Engineering 17, no. 3 (November 29, 2019): 397. http://dx.doi.org/10.22190/fume190422037t.
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Intelligent production is the future of industrial production. It is the leading way to a new industrial era and it best defines the concept of the Fourth Industrial Revolution. Getting the real-time data on quality, resources and costs it provides significant advantages over classical production systems. Intelligent production must be built on sustainable and service-oriented technological and business practices. They are characterized by flexibility, adaptability and self-learning, resilience to failures, and risk management. The high levels of automation, on the other hand, become a mandatory standard for them, which is possible thanks to a flexible network of production-based systems that automatically monitor the production processes. Flexible systems and models that are capable of responding in real time allow internal processes to be radically optimized. Production benefits are not limited to one-off production conditions, and the capabilities include optimization through a global network of adaptive and self-regulating manufacturing components belonging to more than one operator.
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Ullman, David G., and Bruce D'Ambrosio. "Taxonomy for classifying engineering decision problems and support systems." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 9, no. 5 (November 1995): 427–38. http://dx.doi.org/10.1017/s0890060400002742.
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AbstractThe design of even the simplest product requires thousands of decisions. Yet few of these decisions are supported with methods on paper or on computers. Is this because engineering design decisions do not need support or is it because techniques have yet to be developed that are usable on a wide basis? In considering this question a wide range of decision problem characteristics need to be addressed. In engineering design some decisions are made by individuals, others by teams – some are about the product and others about the processes that support the product – some are based on complete, consistent, quantitative data and others on sparse, conflicting, qualitative discussions. To address the reasons why so little support is used and the characteristics of potentially useful decision support tools, a taxonomy of decision characteristics is proposed. This taxonomy is used to classify current techniques and to define the requirements for an ideal engineering design decision support system.
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Martins, K. L. "Practical Guide to Determine the Impact of Radon and Other Radionuclides on Water Treatment Processes." Water Science and Technology 26, no. 5-6 (September 1, 1992): 1255–64. http://dx.doi.org/10.2166/wst.1992.0568.
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During treatment of groundwater, radon is often coincidentally removed by processes typically used to remove volatile organic compounds (VOCs)-for example, processes such as liquid-phase granular activated carbon (LGAC) adsorption and air stripping with vapor-phase carbon (VGAC). The removal of radon from drinking water is a positive benefit for the water user; however, the accumulation of radon on activated carbon may cause radiologic hazards for the water treatment plant operators and the spent carbon may be considered a low-level radioactive waste. To date, most literature on radon removal by water treatment processes was based on bench- or residential-scale systems. This paper addresses the impact of radon on municipal and industrial-scale applications. Available data have been used todevelop graphical methods of estimating the radioactivity exposure rates to facility operators and determine the fate of spent carbon. This paper will allow the reader to determine the potential for impact of radon on the system design and operation as follows.Estimate the percent removal of radon from water by LGAC adsorbers and packed tower air strippers. Also, a method to estimate the percent removal of radon by VGAC used for air stripper off-gas will be provided.Estimate if your local radon levels are such that the safety guidelines, suggested by USEPA (United States Environmental Protection Agency), of 25 mR/yr (0.1 mR/day) for radioactivity exposure may or may not be exceeded.Estimate the disposal requirements of the waste carbon for LGAC systems and VGAC for air stripper “Off-Gas” systems. Options for dealing with high radon levels are presented.
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JOVE PEREZ, ESTEBAN, JOSE LUIS CALVO ROLLE, DANIEL URDA MUÑOZ, ALVARO HERRERO COSIO, URKO ZURUTUZA, and VALENTINA CASOLA. "RECENT ADVANCES IN THE APPLICATION OF DATA SCIENCE TO INDUSTRIAL CYBERSECURITY." DYNA 96, no. 3 (May 1, 2021): 231–32. http://dx.doi.org/10.6036/10178.
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Over the last decades, the concept of cybersecurity has been gaining weight in many fields, such as industry or telecommunications, among others. Cybersecurity is defined as a set of processes and technologies designed to protect programs, computers, communication networks and data against attacks and/or unauthorized access, thus ensuring the confidentiality, integrity and availability of systems.
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Rudas, Imre J. "Intelligent Engineering Systems." Journal of Advanced Computational Intelligence and Intelligent Informatics 4, no. 4 (July 20, 2000): 237–39. http://dx.doi.org/10.20965/jaciii.2000.p0237.
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The "information revolution" of our time affects our entire generation. While a vision of the "Information Society," with its financial, legal, business, privacy, and other aspects has emerged in the past few years, the "traditional scene" of information technology, that is, industrial automation, maintained its significance as a field of unceasing development. Since the old-fashioned concept of "Hard Automation" applicable only to industrial processes of fixed, repetitive nature and manufacturing large batches of the same product1)was thrust to the background by keen market competition, the key element of this development remained the improvement of "Machine Intelligence". In spite of the fact that L. A. Zadeh already introduced the concept of "Machine Intelligence Quotient" in 1996 to measure machine intelligence2) , this term remained more or less of a mysterious meaning best explicable on the basis of practical needs. The weak point of hard automation is that the system configuration and operations are fixed and cannot be changed without incurring considerable cost and downtime. Mainly it can be used in applications that call for fast and accurate operation in large batch production. Whenever a variety of products must be manufactured in small batches and consequently the work-cells of a production line should be quickly reconfigured to accommodate a change in products, hard automation becomes inefficient and fails due to economic reasons. In these cases, new, more flexible way of automation, so-called "Soft Automation," are expedient and suitable. The most important "ingredient" of soft automation is its adaptive ability for efficiently coping with changing, unexpected or previously unknown conditions, and working with a high degree of uncertainty and imprecision since in practice increasing precision can be very costly. This adaptation must be realized without or within limited human interference: this is one essential component of machine intelligence. Another important factor is that engineering practice often must deal with complex systems of multiple variable and multiple parameter models almost always with strong nonlinear coupling. Conventional analysis-based approaches for describing and predicting the behavior of such systems in many cases are doomed to failure from the outset, even in the phase of the construction of a more or less appropriate mathematical model. These approaches normally are too categorical in the sense that in the name of "modeling accuracy," they try to describe all structural details of the real physical system to be modeled. This significantly increases the intricacy of the model and may result in huge computational burden without considerably improving precision. The best paradigm exemplifying this situation may be the classic perturbation theory: the less significant the achievable correction is, the more work must be invested for obtaining it. Another important component of machine intelligence is a kind of "structural uniformity" giving room and possibility to model arbitrary particular details a priori not specified and unknown. This idea is similar to that of the ready-to-wear industry, whose products can later be slightly modified in contrast to the custom-tailors' made-to-measure creations aiming at maximum accuracy from the beginning. Machines carry out these later corrections automatically. This "learning ability" is another key element of machine intelligence. To realize the above philosophy in a mathematically correct way, L. A. Zadeh separated Hard Computing from Soft Computing. This revelation immediately resulted in distinguishing between two essential complementary branches of machine intelligence: Hard Computing based Artificial Intelligence and Soft Computing based Computational Intelligence. In the last decades, it became generally known that fuzzy logic, artificial neural networks, and probabilistic reasoning based Soft Computing is a fruitful orientation in designing intelligent systems. Moreover, it became generally accepted that soft computing rather than hard computing should be viewed as the foundation of real machine intelligence via exploiting the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness, low solution cost and better rapport with reality. Further research in the past decade confirmed the view that typical components of present soft computing such as fuzzy logic, neurocomputing, evolutionary computation and probabilistic reasoning are complementary and best results can be obtained by their combined application. These complementary branches of Machine Intelligence, Artificial Intelligence and Computational Intelligence, serve as the basis of Intelligent Engineering Systems. The huge number of scientific results published in journals and conference proceedings worldwide substantiates this statement. Three years ago, a new series of conferences in this direction was initiated and launched with the support of several organizations including the IEEE Industrial Electronics Society and IEEE Hungary Section in technical cooperation with IEEE Robotics & Automation Society. The first event of the series hosted by Bdnki Dondt Polytechnic, Budapest, Hungary, was called "19997 IEEE International Conference on Intelligent Engineering Systems " (INES'97). The Technical University of Vienna, Austria hosted the next event of the series in 1998, followed by INES'99 held by the Technical University of Kosice, Slovakia. The present special issue consists of the extended and revised version of the most interesting papers selected out of the presentations of this conference. The papers exemplify recent development trends of intelligent engineering systems. The first paper pertains to the wider class of neural network applications. It is an interesting report of applying a special Adaptive Resonance Theory network for identifying objects in multispectral images. It is called "Extended Gaussian ARTMAP". The authors conclude that this network is especially advantageous for classification of large, low dimensional data sets. The second paper's subject belongs to the realm of fuzzy systems. It reports successful application of fundamental similarity relations in diagnostic systems. As an example failure detection of rolling-mill transmission is considered. The next paper represents the AI-branch of machine intelligence. The paper is a report on an EU-funded project focusing on the storage of knowledge in a corporate organizational memory used for storing and retrieving knowledge chunks for it. The flexible structure of the system makes it possible to adopt it to different SMEs via using company-specific conceptual terms rather than traditional keywords. The fourth selected paper's contribution is to the field of knowledge discovery. For this purpose in the first step, cluster analysis is done. The method is found to be helpful whenever little or no information on the characteristics of a given data set is available. The next paper approaches scheduling problems by the application of the multiagent system. It is concluded that due to the great number of interactions between components, MAS seems to be well suited for manufacturing scheduling problems. The sixth selected paper's topic is emerging intelligent technologies in computer-aided engineering. It discusses key issues of CAD/CAM technology of our days. The conclusion is that further development of CAD/CAM methods probably will serve companies on the competitive edge. The seventh paper of the selection is a report on seeking a special tradeoff between classical analytical modeling and traditional soft computing. It nonconventionally integrates uniform structures obtained from Lagrangian Classical Mechanics with other simple elements of machine intelligence such as saturated sigmoid transition functions borrowed from neural nets, and fuzzy rules with classical PID/ST, and a simplified version of regression analysis. It is concluded that these different components can successfully cooperate in adaptive robot control. The last paper focuses on the complexity problem of fuzzy and neural network approaches. A fuzzy rule base, be it generated from expert operators or by some learning or identification schemes, may contain redundant, weakly contributing, or outright inconsistent components. Moreover, in pursuit of good approximation, one may be tempted to overly assign the number of antecedent sets, thereby resulting in large fuzzy rule bases and much problems in computation time and storage space. Engineers using neural networks have to face the same complexity problem with the number of neurons and layers. A fuzzy rule base and neural network design, hence, have two important objectives. One is to achieve a good approximation. The other is to reduce the complexity. The main difficulty is that these two objectives are contradictory. A formal approach to extracting the more pertinent elements of a given rule set or neurons is, hence, highly desirable. The last paper is an attempt in this direction. References 1)C. W. De Silva. Automation Intelligence. Engineering Application of Artificial Intelligence. Vol. 7. No. 5. 471-477 (1994). 2)L. A. Zadeh. Fuzzy Logic, Neural Networks and Soft Computing. NATO Advanced Studies Institute on Soft Computing and Its Application. Antalya, Turkey. (1996). 3)L. A. Zadeh. Berkeley Initiative in Soft Computing. IEEE Industrial Electronics Society Newsletter. 41, (3), 8-10 (1994).
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Markovič, Jaromír, Radko Popovič, Peter Trebuňa, Miriam Pekarčíková, and Marek Kliment. "Virtual Commissioning as a Part of Mechatronical System." Applied Mechanics and Materials 816 (November 2015): 521–25. http://dx.doi.org/10.4028/www.scientific.net/amm.816.521.
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The paper deals with the mechatronical system, that are necessary during the implementation of the production processes in the companies. Mechatronics systems is a relatively new approach to product design and development, merging the principles of electrical, mechanical, computer and industrial engineering. Examples include robots, photocopiers, PC disk drives, sensors, automotive equipment sucha s anti-lock braking systems and many others. This paper focuses on robots and their possibilities of commissioning to the real production processes.
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Cichocki, Max, Christian Landschützer, and Hannes Hick. "Development of a Sharing Concept for Industrial Compost Turners Using Model-Based Systems Engineering, under Consideration of Technical and Logistical Aspects." Sustainability 14, no. 17 (August 27, 2022): 10694. http://dx.doi.org/10.3390/su141710694.
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The trend of sharing concepts is constantly increasing, whether this may be for economic or environmental reasons. Consequently, numerous scientific research works have addressed the subject of sharing concepts. Many of these works have dealt with questions on the topic of sharing concepts itself, however, much less research has been dedicated to the question of how the sharing concept can be developed in the very first place. Thus, the purpose of this work was to systematically use systems engineering methods to develop a sharing concept for heavy-duty agricultural vehicles, while having a strong focus on technical and logistical aspects. Due to the multidisciplinary complexity of the sharing concept, a method from the field of model-based systems engineering, ARCADIA, was chosen. On ARCADIA’s top level, operational analysis was carried out to identify the key stakeholders. The next level, systems analysis, showed that the sharing model can be divided into three main processes: (1) data acquisition and preparation; (2) location planning; (3) and route planning. For these main processes, corresponding methods, algorithms and models were sought and compared against each other in the last level, logical analysis. It can be concluded that the ARCADIA method has provided a framework for evaluating the correlations and interrelationships between methods, algorithms and models at different levels to develop a sharing concept for compost turners from a technical perspective.
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Fraile, Sanchis, Poler, and Ortiz. "Reference Models for Digital Manufacturing Platforms." Applied Sciences 9, no. 20 (October 18, 2019): 4433. http://dx.doi.org/10.3390/app9204433.
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This paper presents an integrated reference model for digital manufacturing platforms, based on cutting edge reference models for the Industrial Internet of Things (IIoT) systems. Digital manufacturing platforms use IIoT systems in combination with other added-value services to support manufacturing processes at different levels (e.g. design, engineering, operations planning, and execution). Digital manufacturing platforms form complex multi-sided ecosystems, involving different stakeholders ranging from supply chain collaborators to Information Technology (IT) providers. This research analyses prominent reference models for IIoT systems to align the definitions they contain and determine to what extent they are complementary and applicable to digital manufacturing platforms. Based on this analysis, the Industrial Internet Integrated Reference Model (I3RM) for digital manufacturing platforms is presented, together with general recommendations that can be applied to the architectural definition of any digital manufacturing platform.
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Vochitoiu, Haralambie, Camelia Lavinia Unguraş, Olga Miclea, Bogdan Gaita, Ioan Rus, Gabriel Ioan Ilcea, Gabriel Dragos Vasilescu, Nicolae Iliaş, Dan Dumitru Pintilie, and Ciprian Mateiu. "Innovative methodological tool for occupational risk quantification." MATEC Web of Conferences 343 (2021): 10002. http://dx.doi.org/10.1051/matecconf/202134310002.
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This paper presents research in the field of estimating and assessing occupational risks, in order to secure the activities carried out in the presence of specific hazards of industrial work systems, and is based on an in-depth knowledge of interdisciplinary notions in various fields related to systems security engineering. The innovative methodological tool highlights a way to quantify the phenomenon of manifestation of hazards specific to work processes that generate occupational risks with impact, both on the human component and at the level of other components specific to work systems, which significantly reduces the inherent subjectivity in assessing the risks caused by the human factor.
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D’Addona, Doriana M., and Alessandro A. Bruzzone. "Formal Tools for Management of Manufacturing Systems: A Multi Agents System Approach." International Journal of Automation Technology 13, no. 5 (September 5, 2019): 691–99. http://dx.doi.org/10.20965/ijat.2019.p0691.
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To overcome the consequences of the 2008 crisis on the real sector, especially manufacturing, Industry 4.0 gives guidelines to drive production by emphasizing technological innovations, such as industrial internet, cloud manufacturing, etc. The proposed paper focuses on cognitive manufacturing within the framework of the emergent synthesis paradigm. Specifically, the structuring process by which the manufacturing assets are organized to provide the finished goods is analyzed. The study is carried out by considering the analogies between manufacturing and other inventive processes supported by formal tools such as formal languages, semantic webs, and multi agent system.
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Yildiz, Turkay, and Funda Yercan. "ENVIRONMENTAL REPORTING OF INDUSTRIAL AND SUPPLY CHAIN BUSINESS PROCESSES WITHIN THE CONTEXT OF SUSTAINABLE DEVELOPMENT." Business: Theory and Practice 12, no. 1 (March 10, 2011): 5–14. http://dx.doi.org/10.3846/btp.2011.01.
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Green issues in industrial and supply chain business processes have been receiving exponentially growing attention over the past decade. Consumers are demanding green products and services more and more, and on the other side of the marketplace, businesses and industries are now much more responsive to green issues. Furthermore, businesses and industrial systems are, in present conditions, positively reacting to green issues. From an academic perspective, there are considerable numbers of research on this topic in various disciplines. Thus, for the green strategies with respect to the sustainable development, this paper delves into the literature of the significance of sustainability concept with an emphasis on the ecological dimension and then brings a range of essential perspectives along with the applied framework of environmental reporting of industrial and supply chain business processes.
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Klocke, Fritz, Benjamin Döbbeler, Marvin Binder, and Dieter Lung. "The Ecological Footprint on Product Level in Machining – From the Conceptional Methodology to the Industrial Application." Advanced Materials Research 907 (April 2014): 417–26. http://dx.doi.org/10.4028/www.scientific.net/amr.907.417.
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In line with the striving for a more sustainable orientation in manufacturing systems and industrial pursuit of resource efficiency, companies are looking for efficient processes. The consumption of electrical energy and other resources during the manufacturing phase is considered by the ecological footprint. This study offers a conception for the determination of the ecological footprint within manufacturing systems based on life cycle assessments. The existence of basic data is a requirement for such an evaluation. Therefore, a holistic measurement system is presented which is adaptable to small as well as large scaled production environments and different usage scenarios, e.g. full scale measurement or detailed process analysis.
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Al Shahrani, Ali M., Madani Abdu Alomar, Khaled N. Alqahtani, Mohammed Salem Basingab, Bhisham Sharma, and Ali Rizwan. "Machine Learning-Enabled Smart Industrial Automation Systems Using Internet of Things." Sensors 23, no. 1 (December 28, 2022): 324. http://dx.doi.org/10.3390/s23010324.
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Industrial automation uses robotics and software to operate equipment and procedures across industries. Many applications integrate IoT, machine learning, and other technologies to provide smart features that improve the user experience. The use of such technology offers businesses and people tremendous assistance in successfully achieving commercial and noncommercial requirements. Organizations are expected to automate industrial processes owing to the significant risk management and inefficiency of conventional processes. Hence, we developed an elaborative stepwise stacked artificial neural network (ESSANN) algorithm to greatly improve automation industries in controlling and monitoring the industrial environment. Initially, an industrial dataset provided by KLEEMANN Greece was used. The collected data were then preprocessed. Principal component analysis (PCA) was used to extract features, and feature selection was based on least absolute shrinkage and selection operator (LASSO). Subsequently, the ESSANN approach is proposed to improve automation industries. The performance of the proposed algorithm was also examined and compared with that of existing algorithms. The key factors compared with existing technologies are delay, network bandwidth, scalability, computation time, packet loss, operational cost, accuracy, precision, recall, and mean absolute error (MAE). Compared to traditional algorithms for industrial automation, our proposed techniques achieved high results, such as a delay of approximately 52%, network bandwidth accomplished at 97%, scalability attained at 96%, computation time acquired at 59 s, packet loss achieved at a minimum level of approximately 53%, an operational cost of approximately 59%, accuracy of 98%, precision of 98.95%, recall of 95.02%, and MAE of 80%. By analyzing the results, it can be seen that the proposed system was effectively implemented.
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Egan, I., J. M. Ritchie, and P. D. Gardiner. "Measuring performance change in the mechanical design process arena." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 219, no. 12 (December 1, 2005): 851–63. http://dx.doi.org/10.1243/095440505x32724.
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Measurement of the design process is an issue facing business and academic practitioners alike. This paper outlines an approach used to formalize design process measurement within a large electromechanical original equipment manufacturer (OEM) by applying a derivation of the Carnegie-Mellon/Software Engineering Institute systems engineering capability maturity model(R) (SE-CMM(R)), entitled the process capability model-mechanical design (PCM-MD). This new model was created using a similar structure and format of questions as the SE-CMM(R), with modifications to suit mechanical engineering terminology. This was then applied to the mechanical engineering design department of the partner company where it was successfully piloted and then reapplied to produce a picture of how the effectiveness or otherwise of the processes associated with their multidisciplinary mechanical design function altered over time. This work provided the building blocks for further detailed studies to be carried out at other sites in the same company and within the mechanical engineering departments of other firms.
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Agouridas, Vassilis, and Peter Simons. "Antecedence and consequence in design rationale systems." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 22, no. 4 (September 18, 2008): 375–86. http://dx.doi.org/10.1017/s0890060408000255.
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AbstractIdentification of latent or unarticulated customer and other stakeholder needs has been a significant barrier to improving the efficiency and effectiveness of the front-end phase of new product development processes. In-depth determination of stakeholder needs entails analysis of their intentions; the overall aim of the work reported in this article is to establish a framework of intentional analysis, and its associated methods and techniques for improving traceability of design practice during the early phases of the design process. The specific aim of this article is to present a conceptual framework for design rationale systems. The framework built upon the cross-fertilization of approaches and methods drawn from systems engineering and philosophy, focussing on the notions of antecedence and consequence. It was developed in the course of tackling design problems originating in industrial contexts. The methods developed were thus evaluated, updated, and refined in real applications. Two application cases are described that have been drawn from the aerospace and power sectors, respectively. The applications showed that the framework's central antecedent/consequent scheme provides a cell from which to develop either a history of actual successive changes, or a tree of alternative possible projected designs.
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RUIZ, LEANDRO, MANUEL TORRES, ALEJANDRO GOMEZ VILANOVA, SEBASTIAN DIAZ DIAZ, and FRANCISCO CAVAS MARTINEZ. "MANUFACTURING PROCESSES TRANSFORMATION IN AERONAUTICAL SECTOR IN AN INDUSTRY 4.0 CONTEXT." DYNA 96, no. 3 (May 1, 2021): 233–34. http://dx.doi.org/10.6036/9938.
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Adoption by the aeronautical sector of developments and technologies of the so-called Industry 4.0 is a major transformation, due to the added value that these new processes bring to the production chain. It is in this context, in which the relevance of the digitalization and automation of all manufacturing processes is observed, with the increasingly widespread implantation of robotic cells and other technologies such as systems of vision and artificial intelligence, will lead to a new digital scenario that will allow the creation in real time of reconfigurable and sustainable spaces with high productivity and reliability.
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Sbanca, Mădălin Petru, Răzvan Gabriel Boboc, and Gheorghe Leonte Mogan. "Fiber Tensioning Systems in a Robotized Winding Procedure for Composite Materials Building Processes." Electronics 12, no. 2 (January 4, 2023): 254. http://dx.doi.org/10.3390/electronics12020254.
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The winding process of carbon fiber is not a new concept, but until now only a few studies have been made in carbon fiber tensioning and winding on complex shapes. The main purpose of the article is to analyze the possibility to conduct the carbon fiber winding using two industrial robots connected as master slave, one to realize the winding and the other to hold and rotate the mandrel, using an own design of an automatic fiber tensioning tool. To have control of the system a force transducer was implemented. The measured force was used to make trajectory adjustments for the robots, having a predefined trajectory. The results obtained from the experimental tests showed that the winding process with two robots and a tensioning system can realize fiber windings with variable tension in molds with complex configurations (3D) of the winding paths. In this way, compact structures of the constantly tensioned fiber bundle can be obtained, according to product requirements.
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Asim, Taimoor, Rakesh Mishra, and Mohamed Alseddiqi. "Development of an Information Quality Framework for Mechanical Engineering Modules with Enhanced Treatment for Pedagogical Content." International Journal of Handheld Computing Research 7, no. 3 (July 2016): 16–23. http://dx.doi.org/10.4018/ijhcr.2016070102.
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The technology based learning systems have capability to comply with diverse requirements of all the stakeholders in the modern education system. In technology based modules, such as those taught in Mechanical Engineering courses, the psychomotor content takes precedence over other domains of teaching and learning. Effective integration of pedagogical content within the Mechanical Engineering modules is of utmost importance for effectiveness in teaching and learning processes in these modules. Published literature is limited in this regard, and hence, the present study focuses on developing a novel an information quality framework for Mechanical Engineering modules, through which an enhanced treatment has been provided to the pedagogical content, in order to meet the educational goals and the industrial requirements worldwide. The novel information quality framework developed in the present study can be used as a guideline for measuring the effectiveness of Mechanical Engineering modules.
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Mack, Daniel L. C., Gautam Biswas, Hamed Khorasgani, Dinkar Mylaraswamy, and Raj Bharadwaj. "Combining expert knowledge and unsupervised learning techniques for anomaly detection in aircraft flight data." at - Automatisierungstechnik 66, no. 4 (April 25, 2018): 291–307. http://dx.doi.org/10.1515/auto-2017-0120.
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AbstractFault detection and isolation schemes are designed to detect the onset of adverse events during operations of complex systems, such as aircraft, power plants, and industrial processes. In this paper, we combine unsupervised learning techniques with expert knowledge to develop an anomaly detection method to find previously undetected faults from a large database of flight operations data. The unsupervised learning technique combined with a feature extraction scheme applied to the clusters labeled as anomalous facilitates expert analysis in characterizing relevant anomalies and faults in flight operations. We present a case study using a large flight operations data set, and discuss results to demonstrate the effectiveness of our approach. Our method is general, and equally applicable to manufacturing processes and other industrial applications.
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Rodriguez, Ignacio, Rasmus Suhr Mogensen, Andreas Fink, Taus Raunholt, Søren Markussen, Per Hartmann Christensen, Gilberto Berardinelli, Preben Mogensen, Casper Schou, and Ole Madsen. "An Experimental Framework for 5G Wireless System Integration into Industry 4.0 Applications." Energies 14, no. 15 (July 23, 2021): 4444. http://dx.doi.org/10.3390/en14154444.
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The fourth industrial revolution, or Industry 4.0 (I4.0), makes use of wireless technologies together with other industrial Internet-of-Things (IIoT) technologies, cyber–physical systems (CPS), and edge computing to enable the optimization and the faster re-configuration of industrial production processes. As I4.0 deployments are ramping up, the practical integration of 5G wireless systems with existing industrial applications is being explored in both Industry and Academia, in order to find optimized strategies and to develop guidelines oriented towards ensuring the success of the industrial wireless digitalization process. This paper explores the challenges arisen from such integration between industrial systems and 5G wireless, and presents a framework applicable to achieve a structured and successful integration. The paper aims at describing the different aspects of the framework such as the application operational flow and its associated tools, developed based on analytical and experimental applied research methodologies. The applicability of the framework is illustrated by addressing the integration of 5G technology into a specific industrial use case: the control of autonomous mobile robots. The results indicate that 5G technology can be used for reliable fleet management control of autonomous mobile robots in industrial scenarios, and that 5G can support the migration of the on-board path planning intelligence to the edge-cloud.
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Kakinuma, Yasuhiro, and Daisuke Kono. "Special Issue on Self-Optimizing Machining Systems." International Journal of Automation Technology 16, no. 2 (March 5, 2022): 125. http://dx.doi.org/10.20965/ijat.2022.p0125.
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The concept of Self-Optimizing Machining Systems (SOMS) has been proposed against the background of Industry 4.0 and the Digital Twin concept, based on cyber-physical systems. In order to improve manufacturing productivity, quality, and efficiency, each component technology related to the machining process, such as CAD/CAM, process modeling/simulation, process monitoring/control, and workpiece assessment, as well as the machine tools themselves, has been developed independently to date. However, series of processes, including the interactions among these component technologies, have finally determined the machining performance and the quality of the products. SOMS deals with the information links among these components comprehensively and plays the important role of combining these links and functionalities to optimize the overall machining system. Nevertheless, an intensive implementation and combination of these technologies has yet to become state-of-the-art in industry, while further research and development for SOMS is required for Industry 4.0 and Digital Twin. This special issue focuses on the research trends of SOMS, especially the interaction links among machine tools, process monitoring, and work assessment. From researchers who are active on the front lines of manufacturing engineering, the latest achievements related to the development of SOMS are presented in 6 papers. On one hand, the development of sensor-integrated components is indispensable for SOMS to monitor the status of a process and feed it back to a related component in order to control the machining process and its environment. On the other hand, it can be said that visual simulation, virtual metrology, and other epoch-making, on-machine technologies for evaluating machined surfaces, as well as process optimization based on machined surface information, are strongly required. We hope this special issue will contribute to future research and development for researchers and engineers in the field of manufacturing and machining systems.
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MAHER, MARY LOU. "Blurring the boundaries." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 21, no. 1 (January 2007): 7–10. http://dx.doi.org/10.1017/s0890060407070047.
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Early research in artificial intelligence (AI) in design was “AI in the large.” Artificial intelligence promised a revolutionary approach to assisting or automating design processes, separate from other computational systems. As the field matures, “AI in the small” has the most potential. Rather than seeing large AI programs, we see the results of research in AI in design providing the glue that holds larger systems together using reasoning systems that represent or manage processes, information, and interaction devices that use conventional procedural programming; effectively blurring the boundaries between AI and non-AI. Alternatively, we see research in AI in design as playing a role in blurring the boundaries between the physical and the virtual.
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Fernando-Foncillas, Clara, Maria M. Estevez, Hinrich Uellendahl, and Cristiano Varrone. "Co-Management of Sewage Sludge and Other Organic Wastes: A Scandinavian Case Study." Energies 14, no. 12 (June 9, 2021): 3411. http://dx.doi.org/10.3390/en14123411.
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Wastewater and sewage sludge contain organic matter that can be valorized through conversion into energy and/or green chemicals. Moreover, resource recovery from these wastes has become the new focus of wastewater management, to develop more sustainable processes in a circular economy approach. The aim of this review was to analyze current sewage sludge management systems in Scandinavia with respect to resource recovery, in combination with other organic wastes. As anaerobic digestion (AD) was found to be the common sludge treatment approach in Scandinavia, different available organic municipal and industrial wastes were identified and compared, to evaluate the potential for expanding the resource recovery by anaerobic co-digestion. Additionally, a full-scale case study of co-digestion, as strategy for optimization of the anaerobic digestion treatment, was presented for each country, together with advanced biorefinery approaches to wastewater treatment and resource recovery.
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Leizea, Ibai, Imanol Herrera, and Pablo Puerto. "Calibration Procedure of a Multi-Camera System: Process Uncertainty Budget." Sensors 23, no. 2 (January 4, 2023): 589. http://dx.doi.org/10.3390/s23020589.
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The Automated six Degrees of Freedom (DoF) definition of industrial components has become an added value in production processes as long as the required accuracy is guaranteed. This is where multi-camera systems are finding their niche in the market. These systems provide, among other things, the ease of automating tracking processes without human intervention and knowledge about vision and/or metrology. In addition, the cost of integrating a new sensor into the complete system is negligible compared to other multi-tracker systems. The increase in information from different points of view in multi-camera systems raises the accuracy, based on the premise that the more points of view, the lower the level of uncertainty. This work is devoted to the calibration procedures of multi-camera systems, which is decisive to achieve high performance, with a particular focus on the uncertainty budget. Moreover, an evaluation methodology has been carried out, which is key to determining the level of accuracy of the measurement system.
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Maes, Marc A., and Markus Dann. "Hierarchical Bayes methods for systems with spatially varying condition states." Canadian Journal of Civil Engineering 34, no. 10 (October 1, 2007): 1289–98. http://dx.doi.org/10.1139/l07-049.
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In engineering decision making, we often face problems where the conditions governing certain response models vary spatially. In such cases, the use of hierarchical Bayesian models is often beneficial. Such models are based on a “condition state” vector that is assumed to be conditionally independent given a set of “hyper-parameters.” All other process parameters are then conditional on this state variable vector. Such models can be applied to a large variety of problems where data from various systems or sources need to be spatially “mixed,” such as in deteriorating infrastructure, spatial aspects of corrosion, preference and consequence modeling, and system failure models for large industrial plants. The models are especially useful for performing statistical inference and for updating in the context of life-cycle optimization, optimal inspection, and maintenance planning. A detailed extension is explored that allows for the spatial correlation of the individual “states” given the hyper-parameters. This allows an efficient posterior assessment of high-level upcrossing rates for the purpose of risk analysis.Key words: spatially distributed processes, hierarchical Bayes models, statistical inference for large systems, spatial correlation.
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Vattam, Swaroop S., Michael E. Helms, and Ashok K. Goel. "A content account of creative analogies in biologically inspired design." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24, no. 4 (October 25, 2010): 467–81. http://dx.doi.org/10.1017/s089006041000034x.
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AbstractThe growing movement of biologically inspired design is driven in part by the need for sustainable development and in part by the recognition that nature could be a source of innovation. Biologically inspired design by definition entails cross-domain analogies from biological systems to problems in engineering and other design domains. However, the practice of biologically inspired design at present typically isad hoc, with little systemization of either biological knowledge for the purposes of engineering design or the processes of transferring knowledge of biological designs to engineering problems. In this paper we present an intricate episode of biologically inspired engineering design that unfolded over an extended period of time. We then analyze our observations in terms ofwhy,what,how, andwhenquestions of analogy. This analysis contributes toward a content theory of creative analogies in the context of biologically inspired design.
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Llop, A., F. Borrull, and E. Pocurull. "Comparison of the removal of phthalates and other organic pollutants from industrial wastewaters in membrane bioreactor and conventional activated sludge treatment plants." Water Science and Technology 60, no. 9 (November 1, 2009): 2425–37. http://dx.doi.org/10.2166/wst.2009.314.
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In recent years greater attention has been paid to the presence of pollutants in wastewater treatment plants, mainly because of strict environmental regulations and the possibility of reusing treated water in industrial processes. Since some organic pollutant compounds are not sufficiently removed in conventional activated sludge treatment (CAST) plants, new treatment processes have been developed, such as membrane bioreactors (MBRs). In this study a submerged membrane bioreactor (MBR) was used to treat mixed industrial wastewaters in parallel with a CAST plant. Two hydraulic retention times (HRT) of wastewater were tested as one of the operational conditions of MBR and the quality of effluents of the two processes were studied and compared. Several general quality parameters were analysed in wastewaters: chemical oxygen demand (COD), pH, conductivity, nitrogen, phosphate, suspended solids (SS) and turbidity. The two systems reduced COD by around 90%. SS was reduced by around 81% in the CAST plant and around 90% in the MBR plant. The results for the other general parameters were similar or better in the MBR process, which worked at a lower HRT. We also studied the removal of a group of six phthalates and bis(2-ethylhexyl)adipate ester by SPME/GC—MS in the two treatment plants. Most of these compounds were not completely removed in the two treatment plants and were identified at low μg l−1 levels. We also tentatively identify some organic compounds in the wastewaters. Most of the compounds we found in the influent, MBR effluent and CAST effluent were benzene derivates, styrene, naphthalene and naphthalene derivates, and phenol derivates.
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Lutsenko, Igor, Svitlana Koval, and Valerii Tytiuk. "Developing interactive interaction of dual buffering systems and conversion class systems with continuous supply of technological products." Eastern-European Journal of Enterprise Technologies 5, no. 4 (113) (October 29, 2021): 20–25. http://dx.doi.org/10.15587/1729-4061.2021.240163.
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Many modern industrial production facilities consist of sequentially operating systems with a continuous supply of technological product. The task of stabilizing the qualitative and quantitative parameters of output products at all stages of such production is a very difficult task and often leads to additional time and money costs. Therefore, improving the efficiency of these processes is a relevant issue. A review of analogous solutions to this type of problem revealed the variability of their authors’ approaches. However, all of them are aimed at optimizing existing control trajectories, rather than creating a new, more accurate trajectory. Earlier, as part of the description of the basic principles of structural and parametric optimization of the management of production processes of this type, only the improved work of technological subsystems was reported. This paper describes the principles of control over the proposed dual buffering system and its interactive interaction with other technological subsystems. The introduction of buffering systems makes sequential technological subsystems more independent of each other. That makes it possible to increase the degree of freedom for each control subsystem and thereby improve the efficiency of finding the optimal mode of operation of the entire cybernetic system. A conceptual model of the dual buffering system was built, the stabilization of the quantitative parameter at the output of the buffering system was substantiated through the development of an adaptation mechanism, and simulation modeling of the synthesized system was carried out. The study shows that the use of buffering systems could improve the quality of energy utilization and reduce the wear of technological mechanisms by 14 % in general
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Jiménez López, Eusebio, Francisco Cuenca Jiménez, Gabriel Luna Sandoval, Francisco Javier Ochoa Estrella, Marco Antonio Maciel Monteón, Flavio Muñoz, and Pablo Alberto Limón Leyva. "Technical Considerations for the Conformation of Specific Competences in Mechatronic Engineers in the Context of Industry 4.0 and 5.0." Processes 10, no. 8 (July 24, 2022): 1445. http://dx.doi.org/10.3390/pr10081445.
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The incursion of disruptive technologies, such as the Internet of Things, information technologies, cloud computing, digitalization and artificial intelligence, into current production processes has led to a new global industrial revolution called Industry 4.0 or Manufacturing 4.0. This new revolution proposes digitization from one end of the value chain to the other by integrating physical assets into systems and networks linked to a series of technologies to create value. Industry 4.0 has far-reaching implications for production systems and engineering education, especially in the training of mechatronic engineers. In order to face the new challenges of the transition from manufacturing 3.0 to Industry 4.0 and 5.0, it is necessary to implement innovative educational models that allow the systematic training of engineers. The competency-based education model has ideal characteristics to help mechatronic engineers, especially in the development of specific competencies. This article proposes 15 technical considerations related to generic industrial needs and disruptive technologies that serve to determine those specific competencies required by mechatronic engineers to meet the challenges of Industry 4.0 and 5.0.
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Kasper, Lukas, Felix Birkelbach, Paul Schwarzmayr, Gernot Steindl, Daniel Ramsauer, and René Hofmann. "Toward a Practical Digital Twin Platform Tailored to the Requirements of Industrial Energy Systems." Applied Sciences 12, no. 14 (July 10, 2022): 6981. http://dx.doi.org/10.3390/app12146981.
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Digitalization and concepts such as digital twins (DT) are expected to have huge potential to improve efficiency in industry, in particular, in the energy sector. Although the number and maturity of DT concepts is increasing, there is still no standardized framework available for the implementation of DTs for industrial energy systems (IES). On the one hand, most proposals focus on the conceptual side of components and leave most implementation details unaddressed. Specific implementations, on the other hand, rarely follow recognized reference architectures and standards. Furthermore, most related work on DTs is done in manufacturing, which differs from DTs in energy systems in various aspects, regarding, for example, multiple time-scales, strong nonlinearities and uncertainties. In the present work, we identify the most important requirements for DTs of IES. We propose a DT platform based on the five-dimensional DT modeling concept with a low level of abstraction that is tailored to the identified requirements. We address current technical implementation barriers and provide practical solutions for them. Our work should pave the way to standardized DT platforms and the efficient encapsulation of DT service engineering by domain experts. Thus, DTs could be easy to implement in various IES-related use cases, host any desired models and services, and help get the most out of the individual applications. This ultimately helps bridge the interdisciplinary gap between the latest research on DTs in the domain of computer science and industrial automation and the actual implementation and value creation in the traditional energy sector.
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Darlington, M. J., and S. J. Culley. "Current research in the engineering design requirement." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 216, no. 3 (March 1, 2002): 375–88. http://dx.doi.org/10.1243/0954405021520049.
Full textAbstract:
The design requirement is a description of the desired solution to a problem. In engineering design, as in all other, a clear expression of a well-formulated design goal is vital for successful and efficient completion of the design task. The nature of the design requirement and the processes by which it is achieved have been the subject of a wide variety of research. The purpose of the paper is twofold. Firstly, it sets out to collate and discuss representative research in this area in order to give an overview of the current scope of the work. Secondly, it seeks to draw a comparison with the task of developing the design requirement for software and information systems and to initiate a discussion that considers to what extent the substantial body of research in software requirements engineering might help to give an understanding of the design requirement for the engineering design domain. A tentative characterization of the differences between the tasks in the two domains is presented, and representative papers from requirements engineering are used to suggest areas of overlap as a starting point for further investigation.
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Park, Sebeom, Shokhrukh Bokijonov, and Yosoon Choi. "Review of Microsoft HoloLens Applications over the Past Five Years." Applied Sciences 11, no. 16 (August 6, 2021): 7259. http://dx.doi.org/10.3390/app11167259.
Full textAbstract:
Since Microsoft HoloLens first appeared in 2016, HoloLens has been used in various industries, over the past five years. This study aims to review academic papers on the applications of HoloLens in several industries. A review was performed to summarize the results of 44 papers (dated between January 2016 and December 2020) and to outline the research trends of applying HoloLens to different industries. This study determined that HoloLens is employed in medical and surgical aids and systems, medical education and simulation, industrial engineering, architecture, civil engineering and other engineering fields. The findings of this study contribute towards classifying the current uses of HoloLens in various industries and identifying the types of visualization techniques and functions.
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Toyoizumi, Hiroshi, J. George Shanthikumar, and Ronald W. Wolff. "Two Extremal Autocorrelated Arrival Processes." Probability in the Engineering and Informational Sciences 11, no. 4 (October 1997): 441–50. http://dx.doi.org/10.1017/s0269964800004964.
Full textAbstract:
Extremal arrival processes, in the sense of increasing convex order of waiting time of queueing systems, are investigated. Two types of extremal processes are proposed: one in the class of processes that have identical marginal distributions and the other in the class of bounded stochastic processes that have the same mean and covariance structure. The worst performance with regard to waiting time in the sense of increasing convex order is guaranteed when these extremal processes are fed into a first in-first out single-server queue.
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Borjan, Dragana, Maja Gračnar, Željko Knez, and Maša Knez Marevci. "Determination of Viscosity, Density and Interfacial Tension of the Carbon Dioxide–Isopropanol, Argon–Isopropanol, Sulphur Hexafluoride–Isopropanol Binary Systems at 313.15 K and 333.15 K and at Elevated Pressures." Processes 10, no. 11 (November 3, 2022): 2275. http://dx.doi.org/10.3390/pr10112275.
Full textAbstract:
Viscosity, density, and interfacial tension of three binary systems (carbon dioxide–isopropanol, argon–isopropanol, and sulphur hexafluoride–isopropanol) were measured at temperatures of 313.15 K and 333.15 K and at pressures up to 100 bar for carbon dioxide, and for argon and sulphur hexafluoride up to 500 bar. A vibrating tube densimeter method has been used for density measurements and a variable-volume high-pressure optical view cell with some modifications for the other measurements. The results showed that pressure does not have a high impact on viscosity. Density is found to be a linear function of pressure and temperature and the densities of the investigated binary systems increase with pressure and decrease with temperature. Interfacial tension decreased with the elevated pressure at a constant temperature for all the investigated systems. Accurate prediction of thermodynamic and mass transfer data is fundamental in various engineering and industrial operations to design processes with a higher yield of targeted compounds.
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Aksenov, Aleksey, Larisa Bryndina, Ivan Bartenev, P. Popikov, Vladimir Zolnikov, Natal'ya Evsikova, B. Kumitskiy, and A. Gribanov. "MECHANICAL FACULTY OF VSUFT NAMED AFTER G.F. MOROZOV: THE PAST AND THE PRESENT." Forestry Engineering Journal 10, no. 4 (January 19, 2021): 5–22. http://dx.doi.org/10.34220/issn.2222-7962/2020.4/1.
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The article discusses the formation and development of the Faculty of Mechanics from the moment of its creation to the present. The material on the creation of departments of the faculty is presented. The main historical moments of their formation are reflected. The biography of the staff of the departments, who have made a significant contribution to the development of the departments of the faculty, is presented. The department of forestry mechanization was organized in 1937. The scientists of the department take an active part in solving many problems in the forestry industry, forestry and protective afforestation, in the development of machines and tools. The department gave a start in science to many scientists working in research institutions, design organizations, industrial enterprises and universities of the forest profile. The Department of Automation of Industrial Processes has existed since 1975. The staff of the department is actively introducing their scientific developments into the practice of forestry complex: systems for automatic regulation of the processes of forest seed drying, growing forest planting material in closed ground, pneumatic transport of technological chips, systems for automatic control and management of the production of round timber, plywood and other developments. The Department of Computer Engineering and Information Systems spun off from the Department of Automation of Industrial Processes in 1992, as the Department of Computer Engineering, since 2008 it bears its current name. The main scientific activity is work in the field of creating a highly reliable radiation-resistant electronic component base and the development of methods of system analysis and information technologies for their support. The Department of General and Applied Physics was founded in 1949. The lecturers of the department studied the electrical conductivity of wood materials, the properties of thin layers of liquids during impregnation and filtration, molecular acoustics, and forest biogeophysics. In the current period, the main direction of work is related to the study of the response of high-molecular, biopolymer composite and other materials to the effect of physical fields of various natures. The Department of Life Safety and Legal Relations was founded in 1973. The research work of the department was aimed at finding ways and means to improve labor safety, environmental protection and protection of the population in the event of emergencies. Currently, the research work of the department is aimed at solving labor safety problems in the forest and woodprocessing complex
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Grobelna, Iwona, and Andrei Karatkevich. "Challenges in Application of Petri Nets in Manufacturing Systems." Electronics 10, no. 18 (September 19, 2021): 2305. http://dx.doi.org/10.3390/electronics10182305.
Full textAbstract:
Petri nets are a useful mathematical formalism for specification of manufacturing systems, supported by various analysis and verification methods. The progress made in automating control systems and the widespread use of Industry 4.0 pose a number of challenges to their application, starting from the education at university level and ending with modelling of real case studies. The paper aims to present and analyse the most relevant challenges and opportunities related to the use of Petri nets as a modelling technique of manufacturing systems. The review of the literature is primarily based on the years 2019–2020 to reflect the current state of the art. The newest approaches to deadlock prevention and recovering, but also other important analysis problems and difficulties in modelling real industrial processes are discussed. Trends for the future are also identified.
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Novikov, A. V., K. V. Panevnikov, and I. V. Pisarev. "On Miner's Location in Underground Mines." Mining Industry Journal (Gornay Promishlennost), no. 4/2021 (August 25, 2021): 80–83. http://dx.doi.org/10.30686/1609-9192-2021-4-80-83.
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To ensure industrial and mining safety the established safety rules for coal mines envisage the use of a number of complexes and systems, combined into multifunctional safety systems. These automated systems provide for people to be involved in the management of technological processes. The purpose of this paper is to assess how the coal mine safety requirements are aligned with other regulatory documents as they apply to modern safety systems in coal mines. To achieve this goal, the personnel location (positioning) and emergency alert systems in coal mine workings are analyzed for compliance with the requirements of the national standard for multifunctional safety systems in coal mines. It is shown that the current requirements for positioning systems are met by systems that have high accuracy in determining the location coordinates of people. It is suggested that positioning systems of the zonal type should be either upgraded to increase the number of readout devices to bring them up to the requirements of safety regulations in coal mines or replaced.