Reconfiguration Issues Research Articles

Toward smart manufacturing systems incorporating reconfiguration issues

Toward smart manufacturing systems incorporating reconfiguration issues

Enabling simulation services for digital twins of 5G/B5G mobile networks

Digital Twins (DTs) have been proposed as digital replicas of physical entities (e.g., manufacturing equipment), which one can observe in real-time and interact with. Digital Twins of Networks (DTNs) are increasingly being discussed in the literature, as an enabler for efficient data-driven network management and performance-driven network optimization (e.g., to support dynamic reconfiguration, or anticipate the effects of faults). A DTN includes service mapping models, i.e. models that can be fed with acquired data to produce insight on the network itself - e.g., to run what-if scenarios, based on multiple underlying technologies, from Machine Learning to analytical models, e.g. Markov Chains. In this paper we examine the case of DTNs of mobile networks, DTMNs, tailored to 5G and beyond, where issues of dynamic reconfiguration and fault anticipation are critical. We argue that simulation services should be offered by the DTMN in order to allow performance-driven network optimization, and that discrete-event network simulators are ideal instruments to be employed for this purpose. We discuss the challenges that need be addressed to make this happen, e.g., centralized vs. distributed implementation, gathering input from the physical network, security issues and hosting, and we review the possibilities offered by network simulation in terms of what-if analysis, defining the concepts of lockstep and branching analysis. We present a framework to endow a DTMN with simulation services and we exemplify it using Simu5G, a popular 5G/B5G simulation library for OMNeT++, as a reference case study.

The importance of reconfiguration of the distribution network to achieve minimization of energy losses using the dragonfly algorithm

In this article, a method for reconfiguring the distribution network with the presence of production sources to minimize energy losses is presented. Also, besides the reconfiguration issue, the Super distribution tap transformers and the power factor of resources in the network will have their optimal values based on the amount of energy consumption as factors affecting the number of losses. According to the stated parameters, the optimization problem in this article is a non-linear problem with a large search space, for which the dragonfly optimization algorithm was used. To make the results realistic, all types of loads, including commercial, residential and office, have been considered in 24 h and two seasons of the year, cold and hot. The program was prepared with the help of MATLAB software on a sample network of 16 buses, and its applications and results have been evaluated. The obtained results show that determining the optimal reconfiguration is very effective in reducing network losses because, with this method, the amount of losses and unsupplied energy of network subscribers has been reduced significantly. Also, by coordinating the reconfiguration with tap transformers and the power factor of distributed generation resources, the loss reduction rate can be made more effective. The results obtained are compared with the genetic algorithm and the results show the superiority of the dragonfly optimization method.

Multi-Objective Feeder Reconfiguration Using Discrete Particle Swarm Optimization

Electric power distribution systems have been heavily engaged in evolutionary changes toward effective usage of distribution networks for dependability, quality, and improvement of services delivered to customers throughout the years. This was accomplished via a procedure known as reconfiguration. Several strategies have been offered by various authors for successful distribution feeder reconfiguration with a novel optimization method. As a result, this work developed a Discrete Particle Swarm Optimization (DPSO) method to address the issue of distribution system feeder reconfiguration during both steady-state and dynamic power system operations. In a dynamic state, the power demand and generation required are continually changing over time, and the DPSO algorithm finds a new set of solutions to fulfill the power demand. Many network topologies are investigated for the dynamic operation. The feeder reconfiguration single-objective optimization problem was transformed into a multi-objective optimization problem by taking into account both real power loss reduction and distribution system load balancing. The suggested technique was verified using various IEEE 16, 33, and 69 bus standard test distribution systems to determine the efficiency of the developed DPSO algorithm. The simulation findings reveal that DPSO outperforms other optimization algorithms in terms of actual power loss reduction and load balancing, while solving multi-objective distribution system feeder reconfiguration.

Dealing with Communication Channels within IEC61499 Component-Based Systems

Traditional approaches for developing automation systems consider system itself hardly can be changed. Current challenges in automation applications include the need of autoreconfiguration in response to process changes or event triggering. In order to face these requirements, new automation methodologies are necessary. Component-based technologies, initially defined for achieving efficient, structured and reusable designs can also be used to achieve adaptation. In this work, an IEC 61499-based framework that uses the concept to deal with reconfiguration issues is presented. The final output of the framework is a distributed system IEC61499 compliant. A new concept, the communication channel, is introduced providing a new abstraction layer to deal with communication between components. The joint use of automation components and communication channels allows defining complex automation systems in an easy way.

The fuel consumption analysis for satellite formation reconfiguration based on three-impulsive approach

Currently micro/nano satellites have become the protagonists in most formation flying missions, and there is an urgent demand to propose a reliable approach for quick fuel estimation of multiple-impulsive scheme on-board to achieve formation reconfiguration problems. This paper presents an optimal control approach based on multiple impulses for satellite formation in-plane reconfiguration issue in near circular orbit. Based on initial small deviation in the cylindrical coordinates system, a relative orbit motion expression is investigated, and a time-varying propagate system without perturbation is presented in this paper, which is suitable to calculate the solution of relative orbital maneuver by multiple impulses. The formation reconfiguration problem of this relative orbit motion is considered, and orbital motion equations with initial deviations are presented for relative orbital transfer calculation. Through different combinations of method from normal four-impulsive solution, the optimal three-impulsive method for relative orbital transfer in plane is obtained by analysis solution based on graphical and numerical way. In the end of paper, the effectivity and optimality of method is validated, and fuel consumption is analyzed through simulations of assumptive different formation reconfiguration missions.

Adaptive multi-objective service composition reconfiguration approach considering dynamic practical constraints in cloud manufacturing

Dynamic uncertainty factors such as equipment faults are common in practically implemented cloud manufacturing (CMfg) environments, often causing the manufacturing service to be invalidated. In that case, efficient reconfiguration of the original service composition under practical constraints is critical; however, existing research scarcely focuses on it. This paper proposes a dynamic service composition reconfiguration model to bridge the gap by considering practical constraints (DSCRPC) in a real-life cloud manufacturing environment. Based on the constraints considered in this study, the DSCRPC model redefines three objectives: time (T*), cost (C*), and product service quality (Q*S*). To optimize the DSCRPC model, this study developed an adaptive multi-population multi-objective whale optimization algorithm (AMPOWOA) based on the Pareto strategy. The algorithm adopts four balancing strategies and adaptively optimizes and adjusts the key parameters under various balancing strategies through well-designed reinforcement learning models. Finally, we conduct numerical experiments and actual application case tests to compare the performances of AMPOWOA and other algorithms (MOWOA, MOHHO, NSGA-II). The results show that DSCRPC can continuously tackle the cloud manufacturing service composition (CMSC) reconfiguration issue with constraints until an order is completed. Moreover, AMPOWOA is superior to the other algorithms optimizing the DSCRPC model. This significantly enhances the robustness of service composition reconfiguration in real-life CMfg.

Attributes of Land Forces for Approaching Future Full Spectrum Operations

Abstract At present, the current strategies used to address security issues are increasingly changing, this constant being founded mainly on the volatility of behaviors of different target audiences. In the same direction, the various military services, including Land Forces, supporting national and allied strategies, are looking for solutions that can continuously improve the military response, targeting both operational and force reconfiguration issues. Therefore, the present study aims, firstly, to highlight the attributes of Land Forces for addressing future operations, and secondly, to clarify the future framework of the FSO where the organic military structures will have to operate to fulfill the required tasks and missions.

A Theoretical Approach to Modern American History and Literature: An Issue of Reconfiguration and Re-representation by W. Lawrence Hogue

A Theoretical Approach to Modern American History and Literature: An Issue of Reconfiguration and Re-representation by W. Lawrence Hogue

Cyber-physical production systems: enhancement with a self-organized reconfiguration management

The frequency of changes in production requirements is continuously increasing due to economic volatility, shorter innovation cycles and product life cycles. Therefore, a prediction of all goals of a production system at development time is impossible, which is leading to an increased reconfiguration demand during operation. Currently, there are still some weaknesses concerning the reconfiguration of production systems, which are highlighted in this article. The future of industrial automation will be dominated by Cyber-Physical Production Systems, which offer many promising potentials. Hence, this contribution discusses the Cyber-Physical Production Systems and some of their potentials regarding the reconfiguration issues. Corresponding concepts are required to utilize these theoretical potentials. Therefore, this research provides a basic concept for self-organized reconfiguration management.

Enhancing the Reconfigurability Issues of Machine Tool for Reconfigurable Manufacturing System (RMS)

This paper presents a novel concept to enhance the reconfigurability issues (i.e. convertibility, flexibility, etc.) of a small-scale reconfigurable machine tool (RMT) by combining multiple modules (both basic and auxiliary parts) and manufacturing operations on a single workstation. The proposed reconfigurable machine will reduce the overall space, transport time, ramp up time, reconfiguration time and interim storage space. Further, various characteristics of reconfigurability (such as scalability; convertibility, flexibility, etc.) and enablers of the machine tool have been discussed. The proposed design is illustrated with a figure, which is designed on a 3D design tool (solid-works software platform).This machine tool will perform six major cutting and finishing operations, namely, hacksaw cutting, milling, drilling, grinding, buffing and lathe operations on a single work platform.

A three-dimensional group search optimization approach for simultaneous planning of distributed generation units and distribution network reconfiguration

This paper deals with the simultaneous distributed generation (DG) planning and distribution network reconfiguration (SDGNR) issue. The problem is formulized as an optimization model which includes three types of variables, i.e. DGs location as the integer variables, DGs operating point as the continuous ones and switches open\\close state as the binary variables. A new approach entitled three-dimensional group search optimization (3D-GSO) method is also introduced to cope with such a problem. The proposed method is a general optimization scheme applicable to all types of optimization problems which deal with an integer, continuous, and binary variables at the same time. The revised approach is successfully applied to the SDGNR problem with the objective of total loss reduction in power distribution systems. Power flow criteria, as well as operation constraints, are all together accommodated in the process of optimization. Five different scenarios at three load levels are also considered to cover all possible conditions. The validity of the proposed 3D-GSO approach in handling SDGNR problem is assured through comprehensive simulation studies on 33-bus and 69-bus test systems.

Lazy Grounding for Dynamic Configuration

State-of-the-art ASP systems are 2-phased: first they ground the input program and then they solve the variable-free ground program. This may increase the size of the input program even exponentially, making ASP infeasible for many practical applications. Lazy grounding, as in the recent Alpha ASP system, interleaves grounding and solving to avoid this so-called grounding bottleneck. Alpha demonstrates, for the first time in lazy grounding, efficient solving capabilities also for larger problems. The DynaCon research project addresses issues of dynamic reconfiguration in cyber-physical systems, a novel emerging application domain of ASP. Alpha is a promising start for such large-scale systems that need continuous reconfiguration to adapt to a changing environment.

An autonomy-oriented method for service composition and optimal selection in cloud manufacturing

Since the emergence of cloud manufacturing (CMfg), service composition and optimal selection (SCOS) has been focused on as the core issue of service reconfiguration and supply-demand joining. In view of limitations of existing centralized mode, this paper studies autonomy-oriented SCOS method in CMfg. At first, initiative-based service operation procedures are specified and followed by the definition of correlation-aware composition strategy. Then, service responses are integrated with their trust to produce execution prospects which is the trustworthy basis of SCOS. Fuzzy soft set-based decision making method enhanced with volatility analysis is proposed. After trust-based service filtration, flexible and balanced optimal selection is carried out based on level soft sets and with volatility analysis improving discrimination. A numerical case illustrates the method of this paper, and discussions of key means are given at last.

Technical and economic issues of reconfiguration of a coal-fired district heating source

District heating technologies should comply with forthcoming strict regulations on emissions and energy effectiveness. The majority of the communal district heating systems in Poland still produce heat in coalfired boilers that are in many cases worn out and operated with low efficiency, which particularly occurs during off-season time. The paper deals with possible solutions for improving efficiency of coal-fires heat generating plants due to its reconfiguration by applying new heat generating facilities or new fuels - alternative to coal. The work concerns repowering the existing conventional heat generating plant according to chosen scenarios of the plant configuration meeting technical and environmental requirements forecasted for the year of 2035. The maximum demand for heat of the system supplied by the plant is 185 MW. Annual load of the particular units in analyzed plant, including cogeneration facility based on IC-engines and gas or steam turbines have been projected and interfacing of the units has been analyzed and discussed. Taking into account different technical configurations on one side, and different energy and fuel prices on the other side, the comparative cost-benefits analysis of the assumed scenarios has also been made.

Dynamic configuration management of a multi-standard and multi-mode reconfigurable multi-ASIP architecture for turbo decoding

The multiplication of connected devices goes along with a large variety of applications and traffic types needing diverse requirements. Accompanying this connectivity evolution, the last years have seen considerable evolutions of wireless communication standards in the domain of mobile telephone networks, local/wide wireless area networks, and Digital Video Broadcasting (DVB). In this context, intensive research has been conducted to provide flexible turbo decoder targeting high throughput, multi-mode, multi-standard, and power consumption efficiency. However, flexible turbo decoder implementations have not often considered dynamic reconfiguration issues in this context that requires high speed configuration switching. Starting from this assessment, this paper proposes the first solution that allows frame-by-frame run-time configuration management of a multi-processor turbo decoder without compromising the decoding performances.

Simultaneous control of magnetic topologies for reconfigurable vortex arrays

The topological spin textures in magnetic vortices in confined magnetic elements offer a platform for understanding the fundamental physics of nanoscale spin behavior and the potential of harnessing their unique spin structures for advanced magnetic technologies. For magnetic vortices to be practical, an effective reconfigurability of the two topologies of magnetic vortices, that is, the circularity and the polarity, is an essential prerequisite. The reconfiguration issue is highly relevant to the question of whether both circularity and polarity are reliably and efficiently controllable. In this work, we report the first direct observation of simultaneous control of both circularity and polarity by the sole application of an in-plane magnetic field to arrays of asymmetrically shaped permalloy disks. Our investigation demonstrates that a high degree of reliability for control of both topologies can be achieved by tailoring the geometry of the disk arrays. We also propose a new approach to control the vortex structures by manipulating the effect of the stray field on the dynamics of vortex creation. The current study is expected to facilitate complete and effective reconfiguration of magnetic vortex structures, thereby enhancing the prospects for technological applications of magnetic vortices.

A Study of Advanced Wireless Networks Technology Implementation

There is a rapid advancement in wireless communication technology providing the network services anytime and anywhere. 4G communication systems are being developed to solve the various problems the current communication systems (3.5G, 3G, and 2.5G). The increasing dependency of people on telecommunication resources is pushing even more current technological developments in the mobile world. Within the wide range of issues related to 4G wireless networks, due to the scope of the ISSTA conference, in this presentation we highlight some segments of wireless networks that will be based on spread spectrum (including UWB) physical layer and mainly discuss only network adaptability and reconfigurability issues.

Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies

In this study, an approach to re-planning the multi-stage supply chain (SC) subject to disruptions is developed. We analyze seven proactive SC structures, compute recovery policies to re-direct material flows in the case of two disruption scenarios, and assess the performance impact for both service level and costs with the help of a SC (re)planning model containing elements of system dynamics and linear programming. In the result, an explicit connection of performance impact assessment and SC plan reconfiguration issues with consideration of the duration of disruptions and the costs of recovery has been achieved.

Smart automated distribution system considering plug-in hybrid electric vehicle

By rapid growth in the technology of the electric vehicles (EVs), the new smart power grids will include millions of these devices in the near future. The high penetration of EVs especially in the form of plug-in hybrid EVs (PHEV) can result in new challenges in the optimal operation and management of the systems. The charging behavior of PHEVs in a typical system is affected by a number of uncertain parameters which makes the overall charging behavior of PHEVs uncertain. Therefore, this paper makes use of a newly introduced smart model for charging demand of PHEVs to assess their effect on the reconfiguration issue as a precious and significant strategy in the smart automated distribution systems (ADS). In this regard, two different charging modes including charging at the public station and in a local residential community are investigated. Also, a sufficient scenario- based stochastic framework is proposed to model the uncertainties associated with the PHEVs on the reconfiguration problem. The proposed stochastic framework employs the roulette wheel mechanism in conjunction with a modified evolutionary-based optimization technique to deal with the targets. The feasibility and effectiveness of the proposed method is investigated on the 69 bus IEEE distribution system.