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Poornikoo, Mehdi, and Muhammad Azeem Qureshi. "System dynamics modeling with fuzzy logic application to mitigate the bullwhip effect in supply chains." Journal of Modelling in Management 14, no. 3 (2019): 610–27. http://dx.doi.org/10.1108/jm2-04-2018-0045.
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Purpose A plethora of studies focused on the cause and solutions for the bullwhip effect, and consequently many have successfully experimented to dampen the effect. However, the feasibility of such studies and the actual contribution for supply chain performance are yet up for debate. This paper aims to fill this gap by providing a holistic system-based perspective and proposes a fuzzy logic decision-making implementation for a single-product, three-echelon and multi-period supply chain system to mitigate such effect. Design/methodology/approach This study uses system dynamics (SD) as the central modeling method for which Vensim® is used as a tool for hybrid simulation. Further, the authors used MATLAB for undertaking fuzzy logic modeling and constructing a fuzzy inference system that is later on incorporated into SD model for interaction with the main supply chain structure. Findings This research illustrated the usefulness of fuzzy estimations based on experts’ linguistically and logically defined parameters instead of relying merely on the traditional demand forecasting based on time series. Despite the increased complexity of the calculations and structure of the fuzzy model, the bullwhip effect has been considerably decreased resulting in an improved supply chain performance. Practical implications This dynamic modeling approach is not only useful in supply chain management but also the model developed for this study can be integrated into a corporate financial planning model. Further, this model enables optimization for an automated system in a company, where decision-makers can adjust the fuzzy variables according to various situations and inventory policies. Originality/value This study presents a systemic approach to deal with uncertainty and vagueness in dynamic models, which might be a major cause in generating the bullwhip effect. For this purpose, the combination between fuzzy set theory and system dynamics is a significant step forward.
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Jamegh, Riyadh, Dr AllaEldin Kassam, and Dr Sawsan Sabih. "DEVELOPMENT OF FUZZY LOGIC APPROACH TO OPTIMIZE SAFETY STOCK LEVEL IN DETERIORATED PRODUCTS/A SUPPLY CHAIN DAIRY INDUSTRIES CASE STUDY." Al-Qadisiyah Journal for Engineering Sciences 11, no. 3 (2019): 332–44. http://dx.doi.org/10.30772/qjes.v11i3.564.
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In today's complex environment, a high responding ability represents a core for each organization to survive in a competitive environment. To grip your position in intense competition market, the organization must design high efficiency inventory system that has the ability to respond to changes in demand and at the same time reduce holding cost of accommodation to the lowest possible value by controlling inventory drivers such as safety stock level (SS). The traditional approaches of safety stock are limited to deal with dynamic behavior of market. Advanced approaches based on soft computing allow the dynamic updating of SS level. In this paper, a highly advanced dynamic fuzzy logic (DFL) has been suggested as an innovation step to identify safety stock level in dairy industries with objective of minimizing total cost and meet with customer requirements. The proposed approach consists of three main steps firstly, identifying demand uncertainty conditions by applying fuzzy logic steps embedded by identifying dynamic (N) factor which represents the increasing level in demand in period time. Secondly, identifying of raw material availability conditions by applying fuzzy logic steps, and finally, identification of inventory on hand conditions by applying fuzzy logic steps. It is necessary to identify the level of SS dynamically in fuzzy logic as an output embedded with identifying of period specification concept which describes states of demand in a specific period in which the demand is high, medium, or low which leads to identify maximum values of universe of discourse of output (safety stock). Here Matlab program was used. The provided solution demonstrates the proposed model validity. There has been a significant reduction in safety stock level ranging from (7-98)% depending on product type and period specification with a reduction also in holding cost, while keeping the requirements fulfillment of customers demand
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Xu, Bowei, Weiting Liu, and Junjun Li. "Resilience Regulation Strategy for Container Port Supply Chain under Disruptive Events." Journal of Marine Science and Engineering 11, no. 4 (2023): 732. http://dx.doi.org/10.3390/jmse11040732.
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There are many inevitable disruptive events, such as the COVID-19 pandemic, natural disasters and geopolitical conflicts, during the operation of the container port supply chain (CPSC). These events bring ship delays, port congestion and turnover inefficiency. In order to enhance the resilience of the CPSC, a modified two-stage CPSC system containing a container pretreatment system (CPS) and a container handling system (CHS) is built. A two-dimensional resilience index is designed to measure its affordability and recovery. An adaptive fuzzy double-feedback adjustment (AFDA) strategy is proposed to mitigate the disruptive effects and regulate its dynamicity. The AFDA strategy consists of the first-level fuzzy logic control system and the second-level adaptive fuzzy adjustment system. Simulations show the AFDA strategy outperforms the original system, PID, and two pipelines for improved dynamic response and augmented resilience. This study effectively supports the operations manager in determining the proper control policies and resilience management with respect to indeterminate container waiting delay and allocation delay due to disruptive effects.
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Matawale, Chhabi Ram, Saurav Datta, and S. S. Mahapatra. "A fuzzy embedded leagility assessment module in supply chain." Benchmarking: An International Journal 23, no. 7 (2016): 1937–82. http://dx.doi.org/10.1108/bij-12-2013-0113.
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Purpose In today’s ever-changing global business environment, successful survival of manufacturing firms/production units depends on the extent of fulfillment of dynamic customers’ demands. Appropriate supply chain strategy is of vital concern in this context. Lean principles correspond to zero inventory level; whereas, agile concepts motivate safety inventory to face and withstand in turbulent market conditions. The leagile paradigm is gaining prime importance in the contemporary scenario which includes salient features of both leanness and agility. While lean strategy affords markets with predictable demand, low variety and long product life cycle; agility performs best in a volatile environment with high variety, mass-customization and short product life cycle. Successful implementation of leagile concept requires evaluation of the total performance metric and development of a route map for integrating lean production and agile supply in the total supply chain. To this end, the purpose of this paper is to propose a leagility evaluation framework using fuzzy logic. Design/methodology/approach A structured framework consisting of leagile capabilities/attributes as well as criterions has been explored to assess an overall leagility index, for a case enterprise and the data, obtained thereof, has been analyzed. Future opportunities toward improving leagility degree have been identified as well. This paper proposes a Fuzzy Overall Performance Index to assess the combined agility and leanness measure (leagility) of the organizational supply chain. Findings The proposed method has been found fruitful from managerial implication viewpoint. Originality/value This paper aimed to present an integrated fuzzy-based performance appraisement module in an organizational leagile supply chain. This evaluation module helps to assess existing organizational leagility degree; it can be considered as a ready reference to compare performance of different leagile organization (running under similar supply chain architecture) and to benchmark candidate leagile enterprises; so that best practices can be transmitted to the less-performing organizations. Moreover, there is scope to identify ill-performing areas (barriers of leagility) which require special managerial attention for future improvement.
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Aengchuan, Prasert, and Busaba Phruksaphanrat. "Inventory System Design by Fuzzy Logic Control: A Case Study." Advanced Materials Research 811 (September 2013): 619–24. http://dx.doi.org/10.4028/www.scientific.net/amr.811.619.
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Existing inventory lot-sizing models assume certain demand and sufficient supply, which are not practical for industry. Dynamic inventory models can serve uncertain demand, but supply is assumed to be available. However, in the real world situation, supply is not always offered. So, the method that can deal with both uncertain demand and supply should be developed. Fuzzy logic control is now being the effective methodology in many applications under uncertainty. Therefore, a fuzzy logic approach for solving the problem of inventory control under uncertainty was proposed for a case study factory. In the proposed Fuzzy Inventory System (FIS), both demand and availability of supply are described by linguistic terms. Then, the developed fuzzy rules are used to extract the fuzzy order quantity and the fuzzy reorder point continuously. The order quantity and reorder point are both adjusted according to the FIS system. In this research, the suitable ranges for the inputs of the FIS model are justified for the case study factory. Moreover, the effect of trend demands for both increase and decrease are also analyzed with the proposed range. Inventory costs of the proposed fuzzy inventory system are compared with the existing model based on historical data of the case study factory. It found that the proposed range can obtain lower cost than the previous research FIS lot-sizing model, which is better than conventional approaches.
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Pérez-Pimentel, Yolanda, Ismael Osuna-Galán, Carlos Avilés-Cruz, and Juan Villegas-Cortez. "Power Supply Management for an Electric Vehicle Using Fuzzy Logic." Applied Computational Intelligence and Soft Computing 2018 (November 5, 2018): 1–9. http://dx.doi.org/10.1155/2018/2846748.
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The technology of power electronic systems has diversified into industrial, commercial, and residential areas. Developing a strategy to improve the performance of the electrical energy of an electric vehicle (EV) requires an analysis of the model that describes it. EVs are complex mechatronic systems described by nonlinear models and, therefore, its study is not an easy task. It can improve the performance of a battery bank by creating new batteries that allow for greater storage or by developing a management energy system. This article shows the development of a power supply management system based on fuzzy logic for an electric vehicle, in order to minimize the total energy consumption and optimize the battery bank. The experimental result is shown using the fuzzy controller under standard operating conditions. An increase in battery performance and overall performance of energy consumption is shown. Speed signals acquired show improvements in some dynamic, such as overshoot, settling time, and steady-state error parameters. It is shown that this fuzzy controller increases the overall energy efficiency of the vehicle.
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Al-Zabidi, Ayoub, Ateekh Ur Rehman, and Mohammed Alkahtani. "An Approach to Assess Sustainable Supply Chain Agility for a Manufacturing Organization." Sustainability 13, no. 4 (2021): 1752. http://dx.doi.org/10.3390/su13041752.
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Worldwide business organizations realize that agility of sustainable supply-chain is a requisite need for survival in a dynamic, competitive, and unpredictable market. The contribution of this research is to explore and evaluate sustainable agility in supply chains for a dairy manufacturing organization located in Saudi Arabia. Other contributions of this research are to update the literature about the different factors contributing to achieve agile supply chain, propose conceptual framework and assessment approach incorporating the relationships between sustainable supply-chain capabilities, enablers, and attributes, and shortlisting the agility barriers and how they would facilitate manufacturing organizations’ performance. The paper presents supply chain agility evaluation approach, which covers identification of agile supply-chain capabilities and drivers. It also presents a conceptual model and a framework to define agility level and barriers within the supply-chain. In the paper, fuzzy logic approach is preferred, owing to its capability to incorporate and deal with problems involving impreciseness and vagueness phenomena. Threshold-value in this study for the case organization is set to 0.24829. The outcome of the adopted approach indicates that 21 attributes performed below the threshold value; these attributes are further categorized as agility barriers. These are the barriers within their supply chain that impact the agility-level. For the case organization, the foremost priority is to enhance maintainability and serviceability to make it flexible and inexpensive to establish an agile responsive supply chain. At the same time, it should have priority to focus on development and integration of their core competencies to deal with cross-functional and cross-enterprise issues in supply chain. For the case organization, the agility level was found “very agile,” although it is below the “extremely agile.” Thus, a study was developed to understand the behaviour of the supply chain agility and assess/evaluate it to support decision makers in order to develop a strategic solution for different organizational barriers.
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Richey, R. Glenn, Chadwick B. Hilton, Michael G. Harvey, Lauren Skinner Beitelspacher, Mert Tokman, and Miriam Moeller. "Aligning operant resources for global performance: An assessment of supply chain human resource management." Journal of Management & Organization 17, no. 3 (2011): 364–82. http://dx.doi.org/10.1017/s1833367200001528.
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AbstractPurpose:The intent of the paper is to develop the service marketing logic (S-D logic) strategy that is centered on service as a means to differentiate global strategy from those of competitors. The context of the paper is to examine S-D logic in global supply chains. Design/Methodology:The paper is a theory driven conceptual piece.Findings:Globalization emphasizes complex interconnected systems, while S-D logic emphasizes the importance of leveraging operant resources in order to achieve sustainable competitive advantage. Both S-D logic and globalization apply in the supply chain context. This paper focuses on the global supply chain and the importance of leveraging service based operant resources. Because the focus of management has shifted from a domestic to a more complex, three-dimensional network, it is critical for practitioners and researchers to understand how to optimize service based operant resources in the global marketplace.Practical Implications:Because the focus of management has shifted from a domestic to a more complex, three-dimensional global network, it is critical for practitioners and researchers to understand how to optimize service based operant resources in the global marketplace. We suggest that in this dynamic marketplace, both globalization and S-D logic are required to fully explain supply chain performance. Specifically, we suggest that managers develop a global ‘supply-chain management’ perspective allowing for the key operant resource – human capital – to create synergistic partner relationships and customer experiences resulting in superior performance.Originality/Value:This is one of the first (if not the first) paper that examines S-D logic in a global context. This move forward from the domestic orientation of many/most of the recent literature provides the foundation for future global research into the S-D logic.
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Richey, R. Glenn, Chadwick B. Hilton, Michael G. Harvey, Lauren Skinner Beitelspacher, Mert Tokman, and Miriam Moeller. "Aligning operant resources for global performance: An assessment of supply chain human resource management." Journal of Management & Organization 17, no. 3 (2011): 364–82. http://dx.doi.org/10.5172/jmo.2011.17.3.364.
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AbstractPurpose:The intent of the paper is to develop the service marketing logic (S-D logic) strategy that is centered on service as a means to differentiate global strategy from those of competitors. The context of the paper is to examine S-D logic in global supply chains. Design/Methodology:The paper is a theory driven conceptual piece.Findings:Globalization emphasizes complex interconnected systems, while S-D logic emphasizes the importance of leveraging operant resources in order to achieve sustainable competitive advantage. Both S-D logic and globalization apply in the supply chain context. This paper focuses on the global supply chain and the importance of leveraging service based operant resources. Because the focus of management has shifted from a domestic to a more complex, three-dimensional network, it is critical for practitioners and researchers to understand how to optimize service based operant resources in the global marketplace.Practical Implications:Because the focus of management has shifted from a domestic to a more complex, three-dimensional global network, it is critical for practitioners and researchers to understand how to optimize service based operant resources in the global marketplace. We suggest that in this dynamic marketplace, both globalization and S-D logic are required to fully explain supply chain performance. Specifically, we suggest that managers develop a global ‘supply-chain management’ perspective allowing for the key operant resource – human capital – to create synergistic partner relationships and customer experiences resulting in superior performance.Originality/Value:This is one of the first (if not the first) paper that examines S-D logic in a global context. This move forward from the domestic orientation of many/most of the recent literature provides the foundation for future global research into the S-D logic.
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Kamal, Esraa, Amal F. Abdel Abdel-Gawad, and Shereen Zaki. "Neutrosophic-based Machine Learning Techniques in the Context of Supply Chain Management: A Survey." International Journal of Neutrosophic Science 21, no. 2 (2023): 142–60. http://dx.doi.org/10.54216/ijns.210213.
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Supply Chain Management (SCM) plays a critical role in the success of any business organization. Individuals involved in business activities often have to make decisions regarding different aspects of the supply chain, including planning, procurement, production, inventory management, transportation, distribution, and customer relationship management. The combination of neutrosophic logic and machine learning has gained significant attention in the field of SCM as a means to tackle uncertainties and improve decision-making. This paper highlights the potential benefits and applications of integrating neutrosophic reasoning and machine learning in SCM. Neutrosophic reasoning provides a framework for handling imprecise and uncertain information, while machine learning techniques offer powerful tools for data analysis, pattern recognition, and predictive modeling. By leveraging machine learning algorithms within the context of neutrosophic logic, SCM practitioners can enhance demand forecasting accuracy, optimize inventory management, improve transportation and routing decisions, and strengthen supply chain collaboration. The integration of neutrosophic logic and machine learning enables the handling of complex supply chain data, accommodates dynamic and uncertain environments, and supports proactive decision-making. Furthermore, the combination of these approaches can contribute to improved supply chain resilience, sustainability, and customer satisfaction. This paper applied the neutrosophic AHP method as a feature section to select the highest importance criteria as an input to machine learning. Then we applied two machine learning models named random forest and decision. The results show the random forest has the highest accuracy followed by a decision tree.
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Wang, Yuelong, and Weiqing Wang. "Research on the Control Strategy of Urban Integrated Energy Systems Containing the Fuel Cell." Processes 11, no. 5 (2023): 1584. http://dx.doi.org/10.3390/pr11051584.
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High efficiency is one of the many benefits of this novel kind of energy; clean and pollution free fuel cells have attracted the attention of many experts and scholars. The efficient use of fuel cells will certainly become the mainstay of energy transformation and environmental protection. However, fuel cells have low power density, soft electrical output characteristics, and significantly delayed response to sudden load changes. When fuel cells are used as power supply energy alone, the output voltage fluctuates greatly, and the power supply reliability could be higher. To increase the fuel cell’s service life in real world applications, a DC converter and an appropriate auxiliary energy storage power supply are combined to form a fuel cell hybrid power supply system that makes efficient use of the auxiliary energy storage system’s availability, enhances the power supply system’s adaptability through dynamic reconfiguration, and provides better flexibility overall. This work proposes a method for managing the energy produced by an urban integrated power supply system that includes fuel cells, supercapacitors, and solar cells. Applying the IF-THEN rule of load power and the state of charge of the supercapacitors, the power balance is adjusted between the su-percapacitors, photovoltaic cells, and fuel cells according to the defined fuzzy logic control. The intermittent nature of solar power production and the erratic nature of fuel cell output may both be mitigated using this technique, allowing the load power to operate more reliably. The simulation results show that the control strategy adopted in this paper is able to not only meet the load requirements but also reasonably allocate the functional requirements and improve the working efficiency of the system, resulting in a clear optimization effect on the system’s control. In this paper, we focus on the fuel cell hybrid power supply system design, and then we use the idea of fuzzy logic control energy management to build the structure of the fuzzy logic control system, design the fuzzy controller, determine the functions, and verify the solutions through simulation and experimentation.
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Pinto, Constâncio António, José Torres Farinha, Hugo Raposo, and Diego Galar. "Stochastic versus Fuzzy Models—A Discussion Centered on the Reliability of an Electrical Power Supply System in a Large European Hospital." Energies 15, no. 3 (2022): 1024. http://dx.doi.org/10.3390/en15031024.
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This paper discusses the Reliability, Availability, Maintainability, and Safety (RAMS) of an electrical power supply system in a large European hospital. The primary approach is based on fuzzy logic and Petri nets, using the CPNTools software to simulate and determine the most important modules of the system according to the Automatic Transfer Switch. Fuzzy Inference System is used to analyze and assess the reliability value. The stochastic versus fuzzy approach is also used to evaluate the reliability contribution of each system module. This case study aims to identify and analyze possible system failures and propose new solutions to improve the system reliability of the power supply system. The dynamic modeling is based on block diagrams and Petri nets and is evaluated via Markov chains, including a stochastic approach linked to the previous analysis. This holistic approach adds value to this type of research question. A new electrical power supply system design is proposed to increase the system’s reliability based on the results achieved.
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Cheng, Jun, Baitao Zhang, Haoyu Mao, and Sichuan Xu. "Modeling and Fuzzy Feedforward Control of Fuel Cell Air Supply System." World Electric Vehicle Journal 12, no. 4 (2021): 181. http://dx.doi.org/10.3390/wevj12040181.
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As an important part of the fuel cell subsystem, the air supply system of the proton exchange membrane fuel cell (PEMFC) plays an important role in improving the output performance and durability of fuel cells. It is necessary to control the oxygen excess ratio of fuel cell systems in the process of variable load, preventing the oxygen starvation in the loading process and excessive parasitic power consumption caused by oxygen saturation. At this time, the modeling of fuel cell systems and the development of control strategies are critical. The development of a control strategy depends on the construction of the control model. Aiming at the difficulty of air supply system modeling, this paper uses radial basis function (RBF) neural network and state equation method to establish the dynamic model of air supply systems. At the same time, PID, fuzzy logic plus PID (FL + PID), feedforward plus PID (FF + PID), fuzzy feedforward plus fuzzy PID (FF + FLPID) control strategy are proposed to control the oxygen excess ratio of the system. The simulation results show that fuzzy feedforward plus fuzzy PID (FF + FLPID) has the best effect and the oxygen excess ratio can be followed in 1 s.
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Vasil'ev, Mikhail, Sergei Andreev, and Ivan Vasil'ev. "AIR SUPPLY REGULATOR FOR THE WORKING SPACE HEAT INSTALLATION BASED ON FUZZY LOGIC." Applied Mathematics and Control Sciences, no. 2 (June 30, 2020): 99–121. http://dx.doi.org/10.15593/2499-9873/2020.2.06.
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The combustion process in the working space of a heat installation is simulated. The static characteristic of the dependence of fuel consumption on air consumption in the conditions of stabilization of heat generated as a result of the combustion process is shown, therefore, the possibility of optimizing this process is proved. A block diagram, mathematical model and algorithm for calculating energy-saving fuzzy control of the combustion process in the working space of a thermal installation are developed. Combustion Membership functions of fuzzy sets for input linguistic variables are compiled. The rule bases are formulated taking into account the static characteristics of the control object. Examples of technological and linguistic justification of fuzzy controller rules are given. The dynamics of changing the controlled parameter is determined by solving two differential equations. The search for levels of "cut-offs" for the prerequisites of each of the rules using the "minimum" operation in accordance with the compiled database of rules is performed. The defuzzification procedure was performed (bringing it to clarity). The advantages of this system over traditional stabilizing control systems under the action of a set of random factors and a significantly nonlinear relationship between input and output values are shown. Optimal values of scaling factors for the developed automatic control system are determined. Let's consider an example of the formation of a control effect when implementing fuzzy energy-saving control of the combustion process in the working space of the boiler unit No. 3 of the GKP-1A UGPU of Gazprom dobycha Urengoy LLC. The calculations of the amount of inleakage of atmospheric air, excess air flow, the sectional area of the pipe supplying air, the total air flow in the working space of the thermal installation, the volume of natural gas participating in the combustion process, heat resulting from the combustion, the amount of air that did not participate in the combustion process, the amount of heat required to increase the temperature of excess air until the average temperature of the flue gas remaining heat of the combustion reaction, changes in the oxygen concentration in the exhaust flue gases depending on the air flow to the burner. The functional dependence of the flue gas temperature on the natural gas consumption is constructed by approximating the initial data of the regime map of the steam boiler. The dynamic properties of an inertia-delayed controlled process are taken into account when using the Euler method. The combustion control mode influence on the specific fuel consumption is estimated. The effects of using a system with fuzzy control in terms of saving natural gas and electricity over the entire range of performance of a thermal installation are estimated.
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Sivakumar, Arunachalam, Muthamizhan Thiyagarajan, and Karthick Kanagarathinam. "Mitigation of supply current harmonics in fuzzy-logic based 3-phase induction motor." International Journal of Power Electronics and Drive Systems (IJPEDS) 14, no. 1 (2023): 266. http://dx.doi.org/10.11591/ijpeds.v14.i1.pp266-274.
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<span lang="EN-US">A parallel active power filter is employed to enrich the quality of power in the power grid with non-linear loads. The induction motor drive requires better performance in many applications. The overall performance enhancement is performed by mitigating the delivery of current harmonics and related warmness losses in an induction motor. In this paper, comprehensive performance evaluation of a 3-phase induction motor is mentioned with fuzzy logic controller-based shunt active filter (SAF), and the outcomes are compared with proportional integral (PI) and proportional derivative controller (PID) controller. In this work, a new scheme of shunt active filters is connected at the supply side of the vertical speed indicator VSI fed induction motor. The simulation was performed by a fuzzy logic controller (FLC) based 3-</span><span lang="EN-US">f</span><span lang="EN-US"> induction motor drive (IMD) using parallel SAF. Simulation result from MATLAB/Simulink software has been presented to understand the reduction in harmonics by introducing an active filter near the supply side. A fuzzy suitable judgment controller is brought on this work to develop the induction motor dynamic response. Analysis of the simulation outcomes, the usage of MATLAB/Simulink software program for the proposed FLC managed induction motor had been demonstrated and overall performance enhancement of induction motor was discussed.</span>
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Sporleder, Thomas, and H. Christopher Peterson. "Intellectual capital, learning, and knowledge management in agrifood supply chains." Journal on Chain and Network Science 3, no. 2 (2003): 75–80. http://dx.doi.org/10.3920/jcns2003.x031.
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The dynamics of the food system are rapidly evolving so that intangible assets are relatively more important than tangible assets. This evolving shift in the basis of rivalry among firms puts increasing demands on corporate strategy. A future challenge for agrifood firms is to embrace strategy that includes, at least conceptually, knowledge as a strategic asset of a firm. Knowledge and its management are emerging in contemporary thought as a potential source of sustainable competitive advantage. This analysis begins by examining the next evolutionary phase in supply chain integration as a learning supply chain. Conceptually a learning supply chain offers the significant benefits of a truly agile, dynamic response capability for end-users and a fair distribution of returns to all chain participants. The focus then turns to the relationships between network embeddedness and the strategic mix between exploitation and exploration, using knowledge management logic. Managing knowledge for agrifood firms implies the creation and commercialization of intangible assets. The analysis indicates that significant intangibles in the form of brand equity may influence supply chain characteristics to strong ties and close networks. Some specific characteristics would be relatively high embeddedness, high social capital, more easily exchanged tacit knowledge, and higher levels of trust.
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Jumanov, Isroil, Sunatillo Kholmonov, and Olimjon Djumanov. "Improving the Accuracy of Identification of Non-Stationary Objects Based on the Regulation of Model Variables." E3S Web of Conferences 377 (2023): 02005. http://dx.doi.org/10.1051/e3sconf/202337702005.
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Researched and developed mechanisms for optimizing the identification of random time series based on mechanisms for searching for unknown knowledge, hidden properties, patterns, relationships, features of non-stationary objects under the condition of limited a priori information, uncertainty, non-stationary processes. A generalized model for optimizing the identification of RTS based on the use of neural networks, neuro-fuzzy networks of dynamic models, as well as fuzzy logic algorithms is implemented. Instruments for data reliability control are obtained based on statistical, dynamic, intelligent approaches suitable for the conditions of transmission of incomplete, heterogeneous, partially given information with large parametric uncertainty. The principles and methods of data reliability control in a fuzzy environment are developed based on the generalization and use of the properties of neural networks, fuzzy logic and statistical modeling methods. Algorithms for searching for correlations, trends, interrelations and regularities in data, forming training, control and test sets for solving problems of recognition, classifying images of micro-objects and predicting power supply indicators are synthesized. The results of the research are implemented in the form of a software package for identifying non-stationary objects, which ensures the adaptability of model variables, high data processing performance and accuracy of results.
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Bounab, A., A. Chaiba, and S. Belkacem. "Evaluation of the High Performance Indirect Field Oriented Controlled Dual Induction Motor Drive Fed by a Single Inverter using Type-2 Fuzzy Logic Control." Engineering, Technology & Applied Science Research 10, no. 5 (2020): 6301–8. http://dx.doi.org/10.48084/etasr.3799.
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In this paper, a high-performance indirect field-oriented controlled dual Induction Motor (IM) drive fed by a single inverter using type-2 fuzzy logic control will be presented. At first, the mathematical model of the IM is implemented in the d-q reference frame. Then, the speed control of the Dual Induction Motor (DIM) operating in parallel configuration with Indirect Field Oriented Control (IFOC) using PI and type-2 Fuzzy Logic Controller (T2-FLC) will be presented. For the control of this system, a DC supply and a Space Vector Pulse Width Modulation (SVPWM) voltage source inverter are introduced with constant switching frequency. Also, the performance of T2-FLC, which is based on the IFOC, is tested and compared to those achieved using the PI controller. The simulation results demonstrate that the T2-FLC is more robust, efficient, and has superior dynamic performance for traction system applications.
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Abror, Gezaq, Rusminto Tjatur Widodo, and M. Udin Harun Al Rasyid. "Dynamic Sleep Scheduling on Air Pollution Levels Monitoring with Wireless Sensor Network." EMITTER International Journal of Engineering Technology 5, no. 2 (2018): 209–33. http://dx.doi.org/10.24003/emitter.v5i2.185.
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Wireless Sensor Network (WSN) can be applied for Air Pollution Level Monitoring System that have been determined by the Environmental Impact Management Agency which is PM10, SO2, O3, NO2 and CO. In WSN, node system is constrained to a limited power supply, so that the node system has a lifetime. To doing lifetime maximization, power management scheme is required and sensor nodes should use energy efficiently. This paper proposes dynamic sleep scheduling using Time Category-Fuzzy Logic (Time-Fuzzy) Scheduling as a reference for calculating time interval for sleep and activated node system to support power management scheme. This research contributed in power management design to be applied to the WSN system to reduce energy expenditure. From the test result in real hardware node system, it can be seen that Time-Fuzzy Scheduling is better in terms of using the battery and it is better in terms of energy consumption too because it is more efficient 51.85% when it is compared with Fuzzy Scheduling, it is more efficient 68.81% when it is compared with Standard Scheduling and it is more efficient 85.03% when compared with No Scheduling.
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N. Madu, Christian, and Chu-Hua Kuei. "Disaster relief supply chain quality management (DRSCQM)." International Journal of Quality & Reliability Management 31, no. 9 (2014): 1052–67. http://dx.doi.org/10.1108/ijqrm-08-2013-0136.
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Purpose – The purpose of this paper is to develop a framework for disaster relief supply chain quality management (DRSCQM). Design/methodology/approach – This paper introduces a structured approach to making decisions in the following areas: system foundation, system constraints, initial sudden natural disaster encounter point(s), the intensity of disaster, the efficacy of the disaster relief supply chain systems, and post-disaster relief management. Findings – The context-intervention-mechanism-outcome logic provides guidelines for facilitating Lean Six Sigma to eliminate wastes and improve the overall performance of the DRSCQM. Research limitations/implications – The theoretical frameworks will enhance the current knowledge base in DRSCQM literature and will also be helpful to manage disaster relief operations and supply chains. However, there is a need to conduct empirical studies based on the proposed frameworks in the future. Practical implications – A transformation process based on Dr Deming's plan-do-check-act cycle has also been proposed to show how a relief organization can assess its current maturity level, react to it, develop more sustainable disaster relief practices, and move the entire system in the right direction. Social implications – The systemic and holistic procedure developed in this paper views the environment of disaster relief as dynamic, complex, chaotic, and ever-changing and takes into account the fact that relief organizations’ actions often involve a team of diverse specialists working on a project basis. Originality/value – The framework presented here helps to improve the efficiency and the effectiveness of disaster relief supply chain management. This is timely and important now as there continues to be an increase in climate-related natural disasters.
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Chakravorty, J., G. Sharma, and V. Bhatia. "Analysis of a DVR with Molten Carbonate Fuel Cell and Fuzzy Logic Control." Engineering, Technology & Applied Science Research 8, no. 2 (2018): 2673–79. http://dx.doi.org/10.48084/etasr.1849.
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As power demand constantly (and rapidly) increases and with the introduction of many sophisticated electronic devices, power quality issues are becoming a major problem for the power sector. In this context, issues of power quality, voltage swells and sags have become rather common. Custom power devices are generally used to solve this problem. A dynamic voltage restorer (DVR) is the most efficient and effective modern custom power device used in power distribution networks. In this paper a new DVR model is presented. The proposed DVR has a molten carbonate fuel cell (MCFC) as its DC source of supply with an ultra-capacitor along with a fuzzy controller as its controlling unit. The complete model is implemented in MATLAB/SIMULINK and the output of the proposed model is compared with conventional DVR model with a simple DC voltage source and a capacitor with the same fuzzy controller
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Vyas, Garima, and Shripati Vyas. "DEVELOPMENT OF INTELLIGENT CONTROLLER FOR POWER RIPPLE MITIGATION OF DFIG BASED WIND ENERGY SYSTEM." International Journal of Technical Research & Science 7, no. 09 (2022): 6–11. http://dx.doi.org/10.30780/ijtrs.v07.i09.002.
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This study offers an adaptive neuro-fuzzy controller (NFC) for a wind energy conversion system (WECS) based on a doubly fed induction generator (DFIG) that may run in standalone mode. The adaptive- network-based fuzzy inference system (ANFIS) architecture is the foundation upon which the NFC is built since it offers the singular benefit of rapid convergence while integrating the resilience of fuzzy logic and flexibility of neural network algorithm. The load side converter (LSC) control of ANFIS is intended for the independent operation of DFIG-WECS. By keeping output voltage consistent, the suggested approach shows increased dynamic performance under conditions of fluctuating wind speed and load. Due to the precise control of the LSC, the supply frequency to the load is kept consistent even while the turbine rotation changes with changing wind speed. The rotor side converter's proportional-integral (PI) control maintains the flux alignment. The simulation outcomes demonstrate the controller's exceptional performance through its effective management of supply frequency and load-voltage under variations in wind speed and demand load power.
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Zheng, Jie, Ling Wang, Jing-fang Chen, et al. "Dynamic multi-objective balancing for online food delivery via fuzzy logic system-based supply–demand relationship identification." Computers & Industrial Engineering 172 (October 2022): 108609. http://dx.doi.org/10.1016/j.cie.2022.108609.
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Chen, Shan, Yuelin Duan, Jiafu Su, and Junbo Tuo. "Differential Strategies of Continuous Agri-Product Supply Chain Considering Consumer Perception of Eco-Quality." Axioms 12, no. 2 (2023): 158. http://dx.doi.org/10.3390/axioms12020158.
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Considering the influence of the consumers’ perception of eco-quality (CPQ) on the dynamic strategies of the continuous agri-product supply chain, the paper examines a two-stage agri-product supply chain composed of a supplier and a retailer, where the supplier invests in eco-quality improvement and the retailer invests in advertising. Taking the CPQ, eco-quality and goodwill as ternary state variables, the paper formulates joint decision-making models of a continuous agri-product supply chain based on differential game theory. The paper has analyzed equilibrium strategies in decentralized and centralized scenarios, respectively, and further developed an advertising–eco-quality investment cost-sharing contract to coordinate the supply chain. Finally, comparative and numerical analyses have been conducted. The analyses results reveal that consumers’ perceptions of eco-quality and their goodwill preference towards an agri-product encourage the supplier and retailer to improve the eco-quality of the agri-product and the level of advertising. Indeed, the greater the impact of goodwill on demand, the higher level of the supplier’s eco-quality investment and the retailer’s advertising effort, and the higher the profits of the supply chain. The paper also finds that the proposed cost-sharing contract can achieve a Pareto improvement in the continuous agri-product supply chain system. Furthermore, the higher the consumer goodwill preference, the more motivated suppliers and retailers are to cooperate.
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Dietrich, Fabian, Louis Louw, and Daniel Palm. "Blockchain-Based Traceability Architecture for Mapping Object-Related Supply Chain Events." Sensors 23, no. 3 (2023): 1410. http://dx.doi.org/10.3390/s23031410.
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Supply chains have evolved into dynamic, interconnected supply networks, which increases the complexity of achieving end-to-end traceability of object flows and their experienced events. With its capability of ensuring a secure, transparent, and immutable environment without relying on a trusted third party, the emerging blockchain technology shows strong potential to enable end-to-end traceability in such complex multitiered supply networks. This paper aims to overcome the limitations of existing blockchain-based traceability architectures regarding their object-related event mapping ability, which involves mapping the creation and deletion of objects, their aggregation and disaggregation, transformation, and transaction, in one holistic architecture. Therefore, this paper proposes a novel ‘blueprint-based’ token concept, which allows clients to group tokens into different types, where tokens of the same type are non-fungible. Furthermore, blueprints can include minting conditions, which, for example, are necessary when mapping assembly processes. In addition, the token concept contains logic for reflecting all conducted object-related events in an integrated token history. Finally, for validation purposes, this article implements the architecture’s components in code and proves its applicability based on the Ethereum blockchain. As a result, the proposed blockchain-based traceability architecture covers all object-related supply chain events and proves its general-purpose end-to-end traceability capabilities of object flows.
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Yin, Peng, Jinzhou Chen, and Hongwen He. "Control of Oxygen Excess Ratio for a PEMFC Air Supply System by Intelligent PID Methods." Sustainability 15, no. 11 (2023): 8500. http://dx.doi.org/10.3390/su15118500.
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The hydrogen fuel cell is a quite promising green device, which could be applied in extensive fields. However, as a complex nonlinear system involving a number of subsystems, the fuel cell system requires multiple variables to be effectively controlled. Oxygen excess ratio (OER) is the key indicator to be controlled to avoid oxygen starvation, which may result in severe performance degradation and life shortage of the fuel cell stack. In this paper, a nonlinear air supply system model integrated with the fuel cell stack voltage model is first built, based on physical laws and empirical data; then, conventional proportional-integral-derivative (PID) controls for the oxygen excess ratio are implemented. On this basis, fuzzy logic inference and neural network algorithm are integrated into the conventional PID controller to tune the gain coefficients, respectively. The simulation results verify that the fuzzy PID controller with seven subsets could clearly improve the dynamic responses of the fuel cells in both constant and variable OER controls, with small overshoots and the fastest settling times of less than 0.2 s.
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Ye, Ying, and Kwok Hung Lau. "Designing a demand chain management framework under dynamic uncertainty." Asia Pacific Journal of Marketing and Logistics 30, no. 1 (2018): 198–234. http://dx.doi.org/10.1108/apjml-03-2017-0042.
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Purpose The purpose of this paper is to put forward a demand chain management (DCM) framework underpinned by the alignment theory and applies it to investigate the fashion apparel (FA) industry in China under the impacts of the latest economic transition. Design/methodology/approach An exploratory multiple case study methodology involving five Chinese FA firms, each with a different business model and ownership type, was employed. Semi-structured interviews, onsite observations and review of company documents were conducted to collect information for analysis. Findings Using a conceptual DCM framework as a guide for analysis, the study finds that companies with a higher level of alignment with the external market situation and among the three internal DCM dimensions, namely, market management, supply chain management (SCM), and organization management, appear to perform better under the rapidly changing economic conditions in China. Research limitations/implications This study contributes to knowledge by reviewing thoroughly the literature on SCM evolution and develops a DCM framework based on alignment theory that represents the state of the art in this area. By extending the administration-integration-production-development (A-I-P-D) logic set adopted in the alignment theory, this study has also equipped the proposed framework with an empirical tool to measure alignment. Practical implications By applying the framework to examine the Chinese apparel industry under the impacts of the latest economic transition, this study provides practitioners in the industry with a framework to help formulate strategies and a tool to measure alignment. The findings of the case study also offer insights to the industry to thrive in the rapidly changing businesses environment with dynamic uncertainties. Originality/value This study extends the application of the A-I-P-D logic set under the alignment theory to the SCM field. This endeavor successfully transforms the proposed DCM framework from a theoretical concept to a practical tool to help evaluate empirically the alignment and strategic fit of a firm and potential relationship with firm performance. As the Chinese FA market has increasingly evolved under the impact of the globalization, the findings of this study not only assist the local FA companies in coping with the dynamic uncertainties but also shed light on the future developments of the global FA industry. Besides, the alignment measurement tool embedded in the proposed DCM framework can help enhance the chances of business success during implementation.
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Espinosa, Jennifer A., Donna Davis, James Stock, and Lisa Monahan. "Exploring the processing of product returns from a complex adaptive system perspective." International Journal of Logistics Management 30, no. 3 (2019): 699–722. http://dx.doi.org/10.1108/ijlm-08-2018-0216.
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Purpose The purpose of this paper is to explore the processing of product returns at five case companies using a complex adaptive systems (CAS) logic to identify agent interactions, organization, schema, learning and the emergence of adaptations in the reverse supply chain. Design/methodology/approach Using a multiple-case study design, this research applies abductive reasoning to examine data from in-depth, semi-structured interviews and direct researcher observations collected during site visits at case companies. Findings Costly or high-risk returns may require agents to specialize the depth of their mental schema. Processing agents need freedom to interact, self-organize and learn from other agents to generate emergent ideas and adapt. Practical implications Limiting the depth of individual agent schema allows managers to better allocate labor to processing product returns during peak volume. To boost adaptability, managers need to craft a dynamic environment that encourages agents with diverse schema to interact, anticipate, and self-organize to brainstorm new ideas. Managers need to resist the urge to “control” the dynamic environment that ensues. Originality/value This paper builds on existing research that studies the key decision points in the analysis of product returns by exploring how processing-agent behaviors can create adaptability in the reverse supply chain. Additionally, this research follows in the tradition of Choi et al. (2001) and Surana et al. (2005) and proposes the application of CAS to a specific part of the supply chain – the processing of product returns.
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Orji, Ifeyinwa Juliet, and Sun Wei. "Dynamic modeling of sustainable operation in green manufacturing environment." Journal of Manufacturing Technology Management 26, no. 8 (2015): 1201–17. http://dx.doi.org/10.1108/jmtm-11-2014-0120.
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Purpose – Globally, supply chains compete in a complex and rapidly changing environment. Hence, sustainable supplier selection has become a decisive variable in the firm’s financial success. This requires reliable tools and techniques to enhance understanding on how supplier behavior evolves with time and to select the best sustainable supplier. System dynamics (SD) is an approach to investigate the dynamic behavior in which the system alterations correspond to the system variable changes. Fuzzy logic usually solves the challenges of imprecise data and ambiguous human judgment. The paper aims to discuss these issues. Design/methodology/approach – This work presents a novel modeling approach for integrating information on supplier behavior in fuzzy environment with SD simulation modeling technique. This results in a more reliable and responsible decision-support system. Supplier behavior with respect to relevant sustainability criteria were sourced through expert interviews and simulated in Vensim to select the best possible sustainable supplier. The simulation runs were carried out in four scenarios, namely, past, current, future and average time horizon for four different suppliers. A multi-criteria decision-making model was presented to compare results from the systems dynamics model. Findings – An increase in the rate of investment in sustainability by the different suppliers causes an exponential increase in total sustainability performance of the suppliers. The growth rate of the total performance of suppliers outruns their rate of investment in sustainability after about 12 months. Originality/value – While a significant work exists regarding supplier selection, little work has been found that investigates how to insure sustainable suppliers maintain their status for a long period of time.
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R, Thenmozhi, Sharmeela C, Natarajan P, and Velraj R. "Fuzzy Logic Controller Based Bridgeless Isolated Interleaved Zeta Converter for LED Lamp Driver Application." International Journal of Power Electronics and Drive Systems (IJPEDS) 7, no. 2 (2016): 509. http://dx.doi.org/10.11591/ijpeds.v7.i2.pp509-520.
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In recent times, High-Brightness Light Emitting Diodes (HB-LEDs) are developing rapidly and it is confirmed to be the future development in lighting not only because of their high efficiency and high reliability, however also because of their other exceptional features: chromatic variety, shock and vibration resistance, etc. In this paper, a Bridgeless (BL) Isolated Interleaved Zeta Converter is proposed for the purpose of reducing the diode failures or losses, the value of output ripples also gets decreased. The proposed BL isolated interleaved zeta converter operating in Discontinuous Conduction Mode (DCM) is used for controlling the brightness of LED Driver with inherent PFC at ac mains using single voltage sensor. The fuzzy logic controller (FLC) is used to adjust the Modulation Index of the voltage controller in order to improve the dynamic response of LED Lamp driver. Based on the error of converter output voltage, FLC is designed to select the optimum Modulation Index of the voltage controller. The proposed LED driver is simulated to achieve a unity power factor at ac mains for a wide range of voltage control and supply voltage fluctuations.
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Awadalla, Medhat. "Processor Speed Control for Power Reduction of Real-Time Systems." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 4 (2015): 701. http://dx.doi.org/10.11591/ijece.v5i4.pp701-713.
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Reducing energy consumption is a critical issue in the design of battery-powered real time systems to prolong battery life. With dynamic voltage scaling (DVS) processors, energy consumption can be reduced efficiently by making appropriate decisions on the processor speed/voltage during the scheduling of real time tasks. Scheduling decision is usually based on parameters which are assumed to be crisp. However, in many circumstances the values of these parameters are vague. The vagueness of parameters suggests that to develop a fuzzy logic approach to reduce energy consumption by determining the appropriate supply-voltage/speed of the processor provided that timing constraints are guaranteed. Intensive simulated experiments and qualitative comparisons with the most related literature have been conducted in the context of dependent real-time tasks. Experimental results have shown that the proposed fuzzy scheduler saves more energy and creates feasible schedules for real time tasks. It also considers tasks priorities which cause higher system utilization and lower deadline miss time.
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Slimani, Abdeldjalil, Mohammed Nacer Tanjaoui, Abdelkader Boutadara, et al. "A PV-Active Power Filter Interface Scheme for Three Phase Balanced System." International Journal of Engineering Research in Africa 46 (January 2020): 125–45. http://dx.doi.org/10.4028/www.scientific.net/jera.46.125.
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This paper presents a modified hybrid Controller based on instantaneous power-fuzzy controller (IPFLC) for a shunt active power filter (SAPF). The current produced by the AC source is polluted by harmonics injected by the non-linear loads. The supply system requires filtering by suppressing harmonic currents to improve power quality at interface bus. The filtering system consists of an LC filter and a SAPF. The proposed IPFL Controller for the SAPF is based on a combination of the p-q instantaneous power and the fuzzy logic strategy. In this part, two cases are studied, first the active filter is connected only to a capacitor by its dc side, and second case where the active filter is connected to a photovoltaic source or to a battery. The effectiveness, robustness and the dynamic speed of the proposed controller is validated and assessed using dynamic digital simulation. Digital Simulation results validated also the effectiveness of the active filter scheme with modified controller in reducing the source current THD from 25.87% to 0.83% which largely meets the standards of IEEE STD and International Electro-technical Commission (IEC). Digital Simulation and validation used MATLAB-SIMULINK Software Environment.
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Goggi Kirshna Sanyasi Rao and P.Murari. "Mitigation of Harmonics in Three - Phase Three - Wire System by using Fuzzy Logic Controlled Shunt Active Filters." November 2020 6, no. 11 (2020): 87–91. http://dx.doi.org/10.46501/ijmtst061115.
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This paper shows the method of improving the power quality using shunt active power filter. In order to protect the supply system from current harmonics, we have to use the active power filters. These are used to compensate the reactive power compensation, but the performance of active power filters are based on various control strategies. This paper presents the complete examination to estimate the working of SHAF for generating the current references under steady and transient for balanced, unbalanced and non-sinusoidal conditions by using PI controller. The P-Q theory and synchronous reference frame theory, which are widely used in SHAF. The most validate results obtained by simulation with matlab/simulink software are carried out with PI controller for P-Q control theory for various voltage conditions like balanced, unbalanced and non-sinusoidal conditions and dynamic load changes.
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Mohamed, Rachedi, and Bouanane Abdelkrim. "Hybrid controller strategy for optimization of cumulated thermal stresses, induced in X-rays tube for medical use." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 3944. http://dx.doi.org/10.11591/ijece.v9i5.pp3944-3955.
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This work presents a new control strategy of the power supply, in favor of equipment intended for the medical use. Several research investigations have been reserved for the service of this supply type, but there are still some disadvantages, which have challenged their high performance in the practical side, in particular the problems which concern the weight, the size and especially, the efficiency of these installations and this, on the cost side, energy balance, and lifetime of this equipment. A control technique is presented to overcome these constraints; its principle is based on the deduction of a hybrid control of which two controllers are simultaneously used for the same radiological dose, known by the fuzzy logic and the PID which have already been tested [1], [3]. This hybrid control has been greatly enhanced and developed, thanks to its robustness against the various intolerable dynamic states applied to the system and also to the unpredictable external disturbances.
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Rawat, Swati, Bhola Jha, Manoj Kumar Panda, and Jyotshana Kanti. "Interval Type-2 Fuzzy Logic Control-Based Frequency Control of Hybrid Power System Using DMGS of PI Controller." Applied Sciences 11, no. 21 (2021): 10217. http://dx.doi.org/10.3390/app112110217.
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The load frequency control of a microgrid is one of the emerging areas due to the changes in demand and supply in power system. So the controllers’ implementation must be changed accordingly. This paper proposes an interval type-2 fuzzy logic-based, dual-mode gain scheduling (DMGS) of the proportional and integral controller in which the gains of the PI controller werescheduled through the dynamic selector. This proposed controller was implemented ina hybrid microgrid power system in which nonconventional energy sources wereadded to each area of the conventional power plant, which madethe system much more prone to frequency variations. The controller was designed for three areas, consisting of a photovoltaic (PV) system, a wind power system, a fuel cell and a diesel engine/hydropower generator in which the generation rate constraint (GRC) was considered as a nonlinearity. The proposed power system was investigated under various load conditions in the MATLAB/SIMULINK environment. A comparative evaluation of changes in frequency, tie-line power fluctuations and variations in area control errors for the test system showed the effectiveness of the current approach over simple fuzzy PI and a conventional PI-controlling approach.
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Gopal, Vijayshree, and Sumathi Srinivasan. "Power quality improvement in distributed generation system using intelligent control methods." Indonesian Journal of Electrical Engineering and Computer Science 32, no. 1 (2023): 33. http://dx.doi.org/10.11591/ijeecs.v32.i1.pp33-42.
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Hybrid <span>electric power generation and its integration with the grid to supply consumer demand is main focus of this paper. The use of nonlinear load and advanced power electronic equipment-based devices at the consumer end introduces power quality issues in the power system network in terms of voltage and current. This paper explains the design of a control algorithm for a unified power quality conditioner used for mitigating both voltage and current-based power quality issues. The dynamic voltage restorer of unified power quality controller (UPQC) is designed with a unit vector control algorithm and the distribution static synchronous compensator (DSTATCOM) is designed with fuzzy logic and adaptive network-based fuzzy inference system based instantaneous reactive power theory control algorithm. The simulation model built using the MATLAB platform includes a three-phase voltage source along with hybrid electric power generation connected to linear and non-linear loads operating under different conditions. The result is analyzed in terms of voltage and current total harmonic distortion compared with IEEE 512 power quality standards and power factor improvement. The paper shows the adaptive neuro-fuzzy inference systems (ANFIS)-based control algorithm gives better results in terms of total harmonic distortion (THD) compared to the fuzzy-based control algorithm. The power factor is improved using ANFIS-based controller proving the efficiency of the controller</span>.
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Ayat, Y., A. E. Badoud, S. Mekhilef, and S. Gassab. "Energy management based on a fuzzy controller of a photovoltaic/fuel cell/Li-ion battery/supercapacitor for unpredictable, fluctuating, high-dynamic three-phase AC load." Electrical Engineering & Electromechanics, no. 3 (April 23, 2023): 66–75. http://dx.doi.org/10.20998/2074-272x.2023.3.10.
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Introduction. Nowadays, environmental pollution becomes an urgent issue that undoubtedly influences the health of humans and other creatures living in the world. The growth of hydrogen energy increased 97.3 % and was forecast to remain the world’s largest source of green energy. It can be seen that hydrogen is one of the essential elements in the energy structure as well as has great potential to be widely used in the 21st century. Purpose. This paper aims to propose an energy management strategy based a fuzzy logic control, which includes a hybrid renewable energy sources system dedicated to the power supply of a three-phase AC variable load (unpredictable high dynamic). Photovoltaic (PV), fuel cell (FC), Li-ion battery, and supercapacitor (SC) are the four sources that make up the renewable hybrid power system; all these sources are coupled in the DC-link bus. Unlike usual the SC was connected to the DC-link bus directly in this research work in order to ensure the dominant advantage which is a speedy response during load fast change and loads transient. Novelty. The power sources (PV/FC/Battery/SC) are coordinated based on their dynamics in order to keep the DC voltage around its reference. Among the main goals achieved by the fuzzy control strategy in this work are to reduce hydrogen consumption and increase battery lifetime. Methods. This is done by controlling the FC current and by state of charge (SOC) of the battery and SC. To verify the fuzzy control strategy, the simulation was carried out with the same system and compared with the management flowchart strategy. The results obtained confirmed that the hydrogen consumption decreased to 26.5 g and the SOC for the battery was around 62.2-65 and this proves the desired goal.
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Rao, Sivakavi Naga Venkata Bramareswara, Yellapragada Venkata Pavan Kumar, Darsy John Pradeep, et al. "Power Quality Improvement in Renewable-Energy-Based Microgrid Clusters Using Fuzzy Space Vector PWM Controlled Inverter." Sustainability 14, no. 8 (2022): 4663. http://dx.doi.org/10.3390/su14084663.
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An increased electricity demand and dynamic load changes are creating a huge burden on the modern utility grid, thereby affecting supply reliability and quality. It is thus crucial for modern power system researchers to focus on these aspects to reduce grid outages. High-quality power is always desired to run various businesses smoothly, but power-electronic-converter-based renewable energy integrated into the utility grid is the major source of power quality issues. Many solutions are constantly being invented, yet a continuous effort and new optimized solutions are encouraged to address these issues by adhering to various global standards (IEC, IEEE, EN, etc.). This paper therefore proposes a concept of establishing a renewable-energy-based microgrid cluster by integrating various buildings located in an urban community. This enhances power supply reliability by managing the available energy in the cluster without depending on the utility grid. Further, a “fuzzy space vector pulse width modulation” (FSV-PWM) technique is proposed to control the inverter, which improves the power supply quality. This work uniquely optimized the dq reference currents using fuzzy logic theory, which were used to plot the space vectors with effective sector selection to generate accurate PWM signals for inverter control. The modeling/simulation of the microgrid cluster involving the FSV-PWM-based inverter was carried out using MATLAB/Simulink®. The efficacy of the proposed FSV-PWM over the conventional ST-PWM was verified by plotting voltage, frequency, real/reactive power, and harmonic distortion characteristics. Various power quality indices were calculated under different disturbance conditions. The results showed that the use of the proposed FSV-PWM-based inverter adhered to all the key standard requirements, while the conventional system failed in most of the indices.
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El-Shahat, Adel, and Erhuvwu Ayisire. "Novel Electrical Modeling, Design and Comparative Control Techniques for Wireless Electric Vehicle Battery Charging." Electronics 10, no. 22 (2021): 2842. http://dx.doi.org/10.3390/electronics10222842.
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Dynamic wireless power systems are an effective way to supply electric vehicles (EVs) with the required power while moving and to overcome the problems of low mileage and extensive charging times. This paper targets modeling and control for future dynamic wireless charging using magnetic resonance coupling because of the latter’s efficiency. We present a 3D model of transmitter and receiver coils for EV charging with magnetic resonance wireless power developed using ANSYS Maxwell. This model was incorporated into the physical design of the magnetic resonance coupling using ANSYS Simplorer in order to optimize the power. The estimated efficiency was around 92.1%. The transient analysis of the proposed circuit was investigated. A closed-loop three-level cascaded PI controller- was utilized for wireless charging of an EV battery. The controller was designed to eliminate the voltage variation resulting from the variation in the space existing between coils. A single-level PI controller was used to benchmark the proposed system’s performance. Furthermore, solar-powered wireless power transfer with a maximum power point tracker was used to simulate the wireless charging of an electric vehicle. The simulation results indicated that the EV battery could be charged with a regulated power of 12 V and 5 A through wireless power transfer. Fuzzy logic and neuro-fuzzy controllers were employed for more robustness in the performance of the output. The neuro-fuzzy controller showed the best performance in comparison with the other designs. All the proposed systems were checked and validated using the OPAL Real-Time simulator. The stability analysis of the DC–DC converter inside the closed-loop system was investigated.
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Hsueh, Sung-Lin, and Min-Ren Yan. "A Multimethodology Contractor Assessment Model for Facilitating Green Innovation: The View of Energy and Environmental Protection." Scientific World Journal 2013 (2013): 1–14. http://dx.doi.org/10.1155/2013/624340.
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The trends of the green supply chain are attributed to pressures from the environment and from customers. Green innovation is a practice for creating competitive advantage in sustainable development. To keep up with the changing business environment, the construction industry needs an appropriate assessment tool to examine the intrinsic and extrinsic effects regarding corporate competitive advantage. From the viewpoint of energy and environmental protection, this study combines four scientific methodologies to develop an assessment model for the green innovation of contractors. System dynamics can be used to estimate the future trends for the overall industrial structure and is useful in predicting competitive advantage in the industry. The analytic hierarchy process (AHP) and utility theory focus on the customer’s attitude toward risk and are useful for comprehending changes in objective requirements in the environment. Fuzzy logic can simplify complicated intrinsic and extrinsic factors and express them with a number or ratio that is easy to understand. The proposed assessment model can be used as a reference to guide the government in examining the public constructions that qualified green contractors participate in. Additionally, the assessment model serves an indicator of relative competitiveness that can help the general contractor and subcontractor to evaluate themselves and further green innovations.
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N.V., Masalsky. "Synthesis of Low-Voltage Logic Gates on Surrounding Gate SOI CMOS Nanotransistors." Nano- i Mikrosistemnaya Tehnika 23, no. 2 (2021): 75–82. http://dx.doi.org/10.17587/nmst.23.75-82.
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We discuss the issues of synthesis of low-voltage logic gates on cylindrical surrounding gate SOI CMOS nanotransistors in the supply voltage range up to 0.8 V. In this transistor architecture, it becomes possible to more effectively control the charge in its working area, primarily due to its design parameters. It is also characterized by effective suppression of short-channel effects and a low capacitance value. This leads to a decrease in the level of power dissipation in combination with a reduction in the occupied area. TCAD models of n- and p-types nanotransistors have been developed. The anomalous behavior of the dependence of the threshold voltage on the diameter of the working area is revealed, which is associated with the peculiarities of the manifestation of short-channel effects due to the capacitive interaction of the gate-channel regions and drain-source transitions at small gate lengths. They were used to select prototypes of transistors with optimal parameters for the synthesis of complex logic gates with low supply voltage. Using the mathematical core of the HSPICE program, the dynamic characteristics of the developed physical models of the inverter, the inverter chain, and the XOR2 are numerically investigated. At control voltages of 0.8 V and a frequency of 50 GHz, the inverter model predicts a maximum switching delay of 3.3 ps, a limit level of active power of 1.1 mkW, static 0.3 pW, the XOR2 predicts a maximum switching delay of 8.6 ps, a limit level of active power of 4.9 mkW, static 1.5 pW. The minimum of the product "delay * power" of the adder is at a supply voltage of 0.72 V. Its position does not depend on the set of input signals. At the same time, the maximum switching delay is 10.8 ps, the maximum active power level is 3.9 mkW. The totality of the obtained characteristics allows us to consider the analyzed transistor architecture for creating low-power electronic devices.
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Thuyen, Chau Minh. "Improved p-q Harmonic Detection Method for Hybrid Active Power Filter." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 2910. http://dx.doi.org/10.11591/ijece.v8i5.pp2910-2919.
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<p>The accuratedetermination of the load harmonic current is one of the important factors, it decides to effect of harmonic filtering and reactive power compensation for Hybrid Active Power Filter. The p-q harmonic detection method has been widely used in determining the harmonic currents of Hybrid Active Power Filter. However, when using this method, the dynamic response of Hybrid Active Power Filter in the transient period will have a large transient time and overshoot whenever the load changes abruptly. Therefore, in this paper an improved p-q harmonic current detection method based on fuzzy logic is proposed, which aims to reduce the overshoot and transient time in transient duration of Hybrid Active Power Filter. In order to compare the dynamic response of conventional and improved p-q harmonic detection methods, simulation results have demonstrated that: the proposed method has a shorter response time, the magnitude of the supply current in the transient time is smaller and the overshoot of the fundamental active and reactive power components is very small. This has a practical significance that contributes to the stability of the Hybrid Active Power Filter system</p>
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Kumar, Yellapragada Venkata Pavan, Sivakavi Naga Venkata Bramareswara Rao, Kottala Padma, et al. "Fuzzy Hysteresis Current Controller for Power Quality Enhancement in Renewable Energy Integrated Clusters." Sustainability 14, no. 8 (2022): 4851. http://dx.doi.org/10.3390/su14084851.
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Steady increase in electricity consumption, fossil fuel depletion, higher erection times of conventional plants, etc., are encouraging the use of more and more onsite renewable energy. However, due to the dynamic changes in environmental factors as well as the customer load, renewable energy generation is facing issues with reliability and quality of the supply. As a solution to all these factors, renewable energy integrated cluster microgrids are being formed globally in urban communities. However, their effectiveness in generating quality power depends on the power electronic converters that are used as an integral part of the microgrids. Thus, this paper proposes the “Fuzzy Hysteresis Current Controller (FHCC)-based Inverter” for improving the power quality in renewable energy integrated cluster microgrids that are operated either in grid-connected or autonomous mode. Here, the inverter is controlled through a fuzzy logic-based hysteresis current control loop, thereby achieving superior performance. System modelling and simulations are done using MATLAB/Simulink®. The performance analysis of the proposed and conventional inverter configurations is done by computing various power quality indices, namely voltage characteristics (swell, sag, and imbalance), frequency characteristics (deviations), and total harmonic distortion. The results reveal that the proposed FHCC-based inverter achieves a better quality of power than the traditional ST-PWM-based multilevel inverter in terms of IEEE/IEC/EN global standards for renewable energy integrated cluster microgrids application.
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Xu, Wenxiang, Mengnan Liu, and Liyou Xu. "Simulation of multi-power composite electric tractor based on power fluctuation ratio." Journal of Physics: Conference Series 2125, no. 1 (2021): 012007. http://dx.doi.org/10.1088/1742-6596/2125/1/012007.
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Abstract All Combined with the characteristics of frequent abrupt load in the field operation of tractors, and aiming at the problems of single motor energy input and large fluctuation of battery state in the energy system of pure electric tractors, a power supply structure with multiple battery packs was proposed. A dynamic model considering real-time power and load fluctuation and a multi-power cooperative input model based on fuzzy control threshold logic rule based on power fluctuation ratio are established. Matlab and Simulink are used to simulate the model and compare it with the traditional single power model. The results show that when the speed is constant ploughing, the output power of the lithium battery of the multi-power cooperative input model is effectively compensated compared with that of the single-power model under sudden load. The average fluctuation ratio of rising power decreases from 5.8% / s to 2.7% / s, which realizes “peak clipping” and “slow peak” when the current fluctuates greatly. and then made the estimation of battery state of charge (SOC) more accurate, and prolonged the battery life.
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Brailko, A. A., O. V. Gromov, and L. A. Druzhinin. "Digital technologies are the basis of digital economy of civil aviation airport refueling complexes." Civil Aviation High Technologies 23, no. 4 (2020): 20–32. http://dx.doi.org/10.26467/2079-0619-2020-23-4-20-32.
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The article analyzes the main information automated control systems for refueling complexes, based on this analysis, the problems of the airport ground handling functioning are identified, the main of which are the inefficiency of managing stochastic processes that occur in failure situations, as well as the lack of automated control systems for the level of purity of aviation fuel from mechanical impurities and water. The way to upgrade Groundstar Inform GmbH - a single integrated airport management system by increasing the capabilities of the system by adding new components is proposed. A solution to the problem of multi-resource planning of aircraft refueling in high-intensity flight conditions, including failure situations, based on intelligent simulation and resource management is proposed. As well as from the point of view of optimizing the solution of business process objectives the development of planning algorithms using the mathematical apparatus of fuzzy modeling and control, fuzzy sets and fuzzy logic underlying the intelligent modeling of processes is proposed. The concept of an adaptive information management system of technological processes of a refueling complex for monitoring the purity of jet fuel, based on dynamic on-line monitoring of the existence of mechanical impurities and water is introduced. The article examines the elements of creating a "Smart Refueling Complex", in which intelligent business processes are combined into one whole due to the use of "smart" operational processes and technological equipment. The introduction of digital technologies, "industry 4.0" tools and trends in automation, digitalization and digitalization of the modern aviation fuel supply for civil aviation is becoming the basis of the digital economy of civil aviation refueling complexes.
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Roselind, J. Deepika, H. M. Naveen, and S.Yuvaraj. "Artificial Intelligence enabled Dynamic Bandwidth Allocation Optimization in IoT for improved QoS." International Journal of Scientific Methods in Intelligence Engineering Networks 01, no. 02 (2023): 33–43. http://dx.doi.org/10.58599/ijsmien.2023.1204.
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The Internet of Things (IoT) is a collection of intelligently connected devices that are connect to the internet. Every day, as technology advances, an IoT device outnumbers humans on the world. The Internet of Things (IoT) systems would connect not only physical users and devices, but also virtual networks and devices that have already been implemented in various scenarios using new networking, computing, and integrated system technologies. With the rapid advancement of technology, the number of devices involved grows rapidly. IoT systems have crucial issues in supplying sufficient bandwidth to IoT Devices for Improving Quality in Services provided in the form of QoS (Quality of Service) parameters, depending on the volume of devices and data. The proposed work is an artificial intelligence enabled dynamic bandwidth allocation optimization in IoT for improved QoS comprising of IoT devices, router, bandwidth data, KM-PSO clustering, Deep Alternative Neural Network (DANN), Dynamic Bandwidth Allocation Optimization, and QoS Estimation. It provides a scalable solution for allocating the bandwidth for the IoT enabled devices for improving QoS parameters. The work uses K-Means-Particle Swarm Optimization (KM-PSO) for generating the optimum number of clusters for improving the accuracy of the proposed work. Once the optimal number of clusters are generated, a Deep Alternative Neural Network (DANN) used in the present invention detects the traffic from the IoT devices, predicts the required bandwidth to be allocated. The Artificial Intelligence enabled Dynamic Bandwidth Allocation Optimization (AIEDBAO) uses Fuzzy Logic Controller (FLC) for allocating Bandwidth based on the traffic rules generated. The improved QoS parameters achieved with the present invention are Bandwidth Consumption of 34.5Mbps, Packet Delivery Delay (PDD) of 32ms, Packet Loss of 4% and Throughput of 99% at supply of 50Mbps
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Guevara-Rivera, Edna, Roberto Osorno-Hinojosa, Victor Zaldivar-Carrillo, and Humberto Perez-Ortiz. "Dynamic simulation methodology for implementing circular economy: A new case study." Journal of Industrial Engineering and Management 14, no. 4 (2021): 850. http://dx.doi.org/10.3926/jiem.3609.
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Purpose: Circular economy (CE) principles have evolved in response to natural resource depletion as a set of guidelines for eliminating the linear take-use-dispose model of product consumption. The consequences of shifting from a linear to a circular supply chain are difficult to visualize in the long term. This study aims to design a methodology for building a simulation model to implement CE strategies in any small and medium-sized enterprise SME to prove policies before implementing them in the real world. This paper applied the methodology in a biological cycle case study: a confectionery factory in Mexico.Design/methodology/approach: This study evaluated service-dominant logic, ecosystem services, system dynamics, and agent-based modeling to design the proposed methodology. A series of interviews with stakeholders were performed to assess the simulation model during the development phase. The circular economy indicator prototype (CEIP) was used as a circular maturity measure of the confectionery factory. The simulator was executed in Netlogo software, implementing a four-scenario analysis based on two CE policies for the caramel recycling process. Five state variables were proposed in this analysis: confectionery waste, recycled glucose, recycling utilization, costs of recycled glucose, and profit.Findings: The CEIP score of the confectionery factory was 52%, rated as a “good” product. Regarding scenario analysis, the first scenario had the highest profit improvement.Practical implications: The simulator allowed stakeholders to understand the operation of the recycling process and visualize all variables involved in the system.Originality/value: In the CE literature, little attention has been paid to proposing a methodology for designing a simulation model to implement CE strategies in any industry. Thus, this study implements a nine-step methodology based on services context and dynamic simulation tools to design a platform to evaluate and visualize the consequences of CE strategies implementation in the long term.
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Snoussi, Jamila, Seifeddine Ben Elghali, Mohamed Benbouzid, and Mohamed Mimouni. "Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles." Energies 11, no. 8 (2018): 2118. http://dx.doi.org/10.3390/en11082118.
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The global need to solve pollution problems has conducted automotive engineers to promote the development and the use of electric vehicle technologies. This paper focuses on the fuel cell hybrid electric vehicle which uses a proton exchange membrane fuel cell as a main source associated to hybrid storage device: lithium ion battery and ultracapacitors. A common interest in such technology is to spread out the energy flow between its different sources in order to satisfy the power demand for any requested mission. However, the challenging task stills the optimization of this split to reduce hydrogen consumption and respect, at the same time, the system limitations such as admissible limits of storage system capacities and battery current variation. An adaptive filtering-based energy management strategy is proposed in this paper to ensure an optimum distribution of the energy between the sources taking into account dynamic and energetic constraints of each device. For more performance, a fuzzy logic system is used to adapt the frequency of separation with the system state evolution. A sliding mode control is applied to control electric characteristics (voltage and currents) in the considered hybrid power supply. Simulation results, obtained under MATLAB®/SimPowerSystems® for four driving cycles are presented. The proposed strategy achieved good performances by respecting the ultracapacitors state of charge while preserving the battery lifetime under various driving missions.
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Obaze, Yolanda. "The transformative community-based humanitarian service ecosystem." Journal of Humanitarian Logistics and Supply Chain Management 9, no. 3 (2019): 410–37. http://dx.doi.org/10.1108/jhlscm-06-2018-0039.
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Purpose The purpose of this paper is to explore the humanitarian service management categories that influence long-term transformation within complex community-based service ecosystems. Design/methodology/approach This study utilizes mixed methods to present a dynamic model that provides insight into the complexities of supplying, distributing and transporting charitable resources to underserved communities. The interdisciplinary study draws on the theory of service-dominant logic and service science, presents critical elements of transformative service research and uses system dynamics approach to propose a visual causal loop model. Findings This study develops a dynamic model for studying humanitarian service and value propositions in underserved communities. This paper combines the extant literature to emphasize key humanitarian service categories that influence, and are influenced by, service exchanges within community-based contexts. Research limitations/implications This paper is limited in providing quantitative methods in analyzing the case study data. However, the research is still helpful in providing acumen via the causal loop diagram to specifically look into each variable and see their cause and effect relationships in the community-based ecosystem. The research represents an opportunity to model the humanitarian aid and relief scenarios to help make more effective decision-making interventions. Practical implications The model serves as a managerial tool to determine critical services that optimize resource utilization within the community-based service ecosystems. Insights from this research are broadly applicable to the contexts of humanitarian logistics and supply chain management (HLSCM) solutions for community-based ventures. Originality/value This paper conceptualizes how the management of service-for-service exchanges, logistics services and charitable donation management provides transformational humanitarian services and value propositions within underserved communities. This study further provides fundamental contributions by addressing research gaps in the HLSCM domain by supporting service research and the community-based context.
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Ramash Kumar, K. "FLC and PWM SMC for KY Boost Converter." Journal of Circuits, Systems and Computers 28, no. 11 (2019): 1950184. http://dx.doi.org/10.1142/s0218126619501846.
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This paper presents a design and implementation of fuzzy logic controller (FLC) plus PWM sliding mode controller (SMC) for 2nd order-d KY positive output voltage boost converter (KYPOVBC) operated in continuous inductor current mode (CICM). It is more suitable for steady power source in liquid crystal display (LCD), I-pad, CCTV camera, computer parts, light emitting diode (LED), renewable energy and industrial application. The 2nd order-d KYPOVBC always works in CICM and replica of synchronous rectification characteristics. The ON/OFF nature of the 2nd order-d KYPOVBC is nonlinear and their dynamic performance becomes poor. The classical linear controllers are noncapable of output voltage regulation of this converter during the high input supply voltage and load disparities. With the purpose of improving dynamic performance, an output voltage and inductor current regulation of the 2nd order-d KYPOVBC, a SMC plus FLC is designed. The state-space equations of the 2nd order-d KYPOVBC are arrived and then, SMC parameters are calculated. The FLC rules are framed according to the working nature of the 2nd order-d KYPOVBC without mathematical modeling, which is one of the major advantages of the FLC. The SMC acts as an inside loop of this converter to regulate the inductor current, whereas the FLC and proportional integral (PI) controllers act as an outside loop of the same converter for controlling the output voltage. The performance of the designed model is investigated at various operating regions by developing both the experimental and matrix laboratory (MATLAB)/simulation link (Simulink) models in comparison with the SMC plus PI controller. The results are presented to show the best performance of the designed model.