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Analysis of Supply Chain Sustainability Drivers in the Oil and Gas Industry under Covid-19 Pandemic

Journal of systems Science and systems engineering 2024年第2期33卷 131-161页

作者： Sujan Piya department of industrial engineering and engineering management University of SharjahSharjahUnited Arab Emirates

The supply chain of many industries,including Oil and Gas,was significantly affected by the disruption caused by the Covid ***,in turn,had a knock-on effect on other industries around the *** the impact of the disruption posed a major challenge for the *** study contributes to the existing literature by identifying and analyzing the most significant drivers that affected the sustainability of the Oil and Gas supply chain during the Covid *** drivers were identified based on an extensive literature review and a survey conducted with experts working in the Oil and Gas ***-criteria decision-making methodologies were used to analyze these *** analysis from the fuzzy analytical hierarchy process found that the most important drivers for the sustainability of the Oil and gas supply chain during the pandemic were"Risk management capacity","Government regulation"and"Health and safety of employees".On the other hand,the driver"Community Pressure"was found to be of the least ***,the study integrated the results of the fuzzy analytical hierarchy process with the fuzzy technique for order of preference by similarity to ideal solution to calculate the supply chain sustainability index.A case example was demonstrated to rank the industries based on such *** study can support the governmental institutions in benchmarking the Oil and Gas industry based on its sustainability ***,the outcomes of the study will help industrial decision makers prioritize the drivers the company should focus and devise strategies based on the priority to improve the sustainability of their supply chain during severe *** will be crucial as the World health organization has cautioned that the world may encounter another pandemic in the near future.

关键词： Supply chain sustainability drivers Oil and gas supply chain Fuzzy analytical hierarchy process Fuzzy technique for order of preference by similarity to ideal solution Covid-19

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Resilience indices from a family of recovery functions

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Fundamental Research 2024年第1期4卷 13-20页

作者： Loon Ching Tang Lijuan Shen department of industrial systems engineering and management National University of Singapore117576 Singapore ETH Zurich Future Resilient SystemsSingapore-ETH Centre138602 Singapore

Defining and measuring resilience using a unified framework has been a topic of intense *** article presents a perspective on how resilience could be quantitatively assessed through a set of *** starts with a brief explanation of resilience in the context of supply chain and a quick summary of existing quantitative measures of *** then discusses how resilience could be quantified in a constructive manner so that the resulting metrics are representative of the performance throughout the system's life *** particular,it is proposed that resilience should be evaluated according to different time periods,***,during and after a disruption has *** dimensions of resilience,namely reliability,robustness,recovery and reconfigurability,can then be used to make up a set of indices for *** numerical illustration,these indices are computed based on recovery data arising from Hurricane Sandy in October ***,it is postulated that resilience will be the performance metric that complements productivity and sustainability as the third pillar for measuring success of organizations,and in turn,that of sovereign countries in their quests for developing smart cities.

关键词： systems resilience Recovery function Recovery index Robustness index Reconfigurability

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Generating synthetic as-built additive manufacturing surface topography using progressive growing generative adversarial networks

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Friction 2024年第6期12卷 1283-1298页

作者： Junhyeon SEO Prahalada RAO Bart RAEYMAEKERS department of Mechanical engineering Virginia TechBlacksburgVA 24061USA Grado department of industrial and systems engineering Virginia TechBlacksburgVA 24061USA

Numerically generating synthetic surface topography that closely resembles the features and characteristics of experimental surface topography measurements reduces the need to perform these intricate and costly ***,existing algorithms to numerically generated surface topography are not well-suited to create the specific characteristics and geometric features of as-built surfaces that result from laser powder bed fusion(LPBF),such as partially melted metal particles,porosity,laser scan lines,and ***,we present a method to generate synthetic as-built LPBF surface topography maps using a progressively growing generative adversarial *** qualitatively and quantitatively demonstrate good agreement between synthetic and experimental as-built LPBF surface topography maps using areal and deterministic surface topography parameters,radially averaged power spectral density,and material ratio *** ability to accurately generate synthetic as-built LPBF surface topography maps reduces the experimental burden of performing a large number of surface topography ***,it facilitates combining experimental measurements with synthetic surface topography maps to create large data-sets that facilitate,*** as-built surface topography to LPBF process parameters,or implementing digital surface twins to monitor complex end-use LPBF parts,amongst other applications.

关键词： additive manufacturing surface topography synthetic surface topography generative adversarial networks

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Deep Reinforcement Learning or Lyapunov Analysis?A Preliminary Comparative Study on Event-Triggered Optimal Control

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1702-1704页

作者： Jingwei Lu Lefei Li Qinglai Wei Fei-Yue Wang IEEE the department of industrial engineering Tsinghua UniversityBeijing 100084China The State Key Laboratory for management and Control of Complex systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter develops a novel method to implement event-triggered optimal control(ETOC) for discrete-time nonlinear systems using parallel control and deep reinforcement learning(DRL), referred to as Deep-ETOC. The developed Deep-ETOC method introduces the communication cost into the performance index through parallel control, so that the developed method enables control systems to learn ETOC policies directly without triggering conditions.

关键词： Deep letter enable

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Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

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Computer Modeling in engineering & Sciences 2024年第8期140卷 1459-1483页

作者： Hongliang Zhang Yi Chen Yuteng Zhang Gongjie Xu School of management Science and engineering Anhui University of TechnologyMa’anshan243032China Laboratory of Multidisciplinary management and Control of Complex systems of Anhui Higher Education Institutes Anhui University of TechnologyMa’anshan243032China department of industrial engineering School of Mechanical EngineeringNorthwestern Polytechnical UniversityXi’an710072China

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing *** DFJSP research only considers machine constraints and ignores worker *** one critical factor of production,effective utilization of worker resources can increase ***,energy consumption is a growing concern due to the increasingly serious environmental ***,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this *** solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling *** further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are *** strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto *** effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 *** results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.

关键词： Distributed flexible job shop scheduling problem dual resource constraints energy-saving scheduling multi-objective grey wolf optimizer Q-learning

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Review on the state-of-the-art and challenges in the MgB_(2)component manufacturing for superconducting applications

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Superconductivity 2024年第1期9卷 50-64页

作者： Fabiano Carvalho de Castro Sene department of industrial and systems engineering University of TennesseeKnoxvilleUnited States

Since the discovery of MgB_(2)as a superconductor,several research groups worldwide have studied the superconducting mechanisms due to the dual gap nature of MgB_(2),as well as attempted to produce such a compound in wires,tapes,bulks,and thin films for a plethora of *** MgB_(2)carries the promise of replacing Niobium‐based superconductors in low‐field applications,less‐than‐desirable performance and in‐operation stability has slowed down such a *** the properties and nature of the superconductivity of MgB_(2)are fairly known,the reproduction of its properties at manufacturing scales remains an unsolved ***,this manuscript presents a systematic review on fundamental properties,phase formation,growth kinetics,and superconducting properties of MgB_(2)‐based components such as multi‐and mono‐core wires,bulks,and thin ***,challenges,and shortcomings are utilized in consolidating research questions and directions pertaining to the manufacturing of MgB_(2)superconducting ***,we evaluate the technological readiness of MgB_(2)‐based devices for applications in fusion energy systems.

关键词： MgB_(2) Superconductor manufacturing Technology readiness Review Low‐Field applications

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A Multi-Objective Optimization for Locating Maintenance Stations and Operator Dispatching of Corrective Maintenance

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Computers, Materials & Continua 2024年第6期79卷 3519-3547页

作者： Chao-Lung Yang Melkamu Mengistnew Teshome Yu-Zhen Yeh Tamrat Yifter Meles department of industrial management National Taiwan University of Science and TechnologyTaipie106Taiwan department of industrial engineering University of Gondar Institute of TechnologyGondar196Ethiopia

In this study,we introduce a novel multi-objective optimization model tailored for modern manufacturing,aiming to mitigate the cost impacts of operational disruptions through optimized corrective *** to our approach is the strategic placement of maintenance stations and the efficient allocation of personnel,addressing a crucial gap in the integration of maintenance personnel dispatching and station *** model uniquely combines the spatial distribution of machinery with the expertise of operators to achieve a harmonious balance between maintenance efficiency and *** core of our methodology is the NSGA Ⅲ+Dispatch,an advanced adaptation of the Non-Dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ),meticulously designed for the selection of maintenance stations and effective operator *** method integrates a comprehensive coding process,crossover operator,and mutation operator to efficiently manage multiple *** empirical testing,including a detailed analysis from a taiwan region electronic equipment manufacturer,validated the effectiveness of our approach across various scenarios of machine failure frequencies and operator *** findings reveal that the proposed model significantly outperforms current practices by reducing response times by up to 23%in low-frequency and 28.23%in high-frequency machine failure scenarios,leading to notable improvements in efficiency and cost ***,it demonstrates significant improvements in oper-ational efficiency,particularly in selective high-frequency failure contexts,while ensuring substantial manpower cost savings without compromising on operational *** research significantly advances maintenance strategies in production environments,providing the manufacturing industry with practical,optimized solutions for diverse machine malfunction ***,the methodologies and principles developed in this study have pote

关键词： Corrective maintenance multi-objective optimization non-dominated sorting genetic algorithmⅢ operator allocation maintenance station location

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Research on Driver’s Fatigue Detection Based on Information Fusion

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Computers, Materials & Continua 2024年第4期79卷 1039-1061页

作者： Meiyan Zhang Boqi Zhao Jipu Li Qisong Wang Dan Liu Jinwei Sun Jingxiao Liao Harbin Institute of Technology School of Instrument Science and EngineeringHarbin150036China department of industrial and systems engineering The Hong Kong Polytechnic UniversityHong Kong100872China

Driving fatigue is a physiological phenomenon that often occurs during *** the driver enters a fatigued state,the attentionis lax,the response is slow,and the ability todeal with emergencies is significantly reduced,which can easily cause traffic ***,studying driver fatigue detectionmethods is significant in ensuring safe ***,the fatigue state of actual drivers is easily interfered with by the external environment(glasses and light),which leads to many problems,such as weak reliability of fatigue driving ***,fatigue is a slow process,first manifested in physiological signals and then reflected in human face *** improve the accuracy and stability of fatigue detection,this paper proposed a driver fatigue detection method based on image information and physiological information,designed a fatigue driving detection device,built a simulation driving experiment platform,and collected facial as well as physiological information of drivers during ***,the effectiveness of the fatigue detection method was *** movement feature parameters and physiological signal features of drivers’fatigue levels were *** driver fatigue detection model was trained to classify fatigue and non-fatigue states based on the extracted *** rates of the image,electroencephalogram(EEG),and blood oxygen signals were 86%,82%,and 71%,*** fusion theory was presented to facilitate the fatigue detection effect;the fatigue features were fused using multiple kernel learning and typical correlation analysis methods to increase the detection accuracy to 94%.It can be seen that the fatigue driving detectionmethod based onmulti-source feature fusion effectively detected driver fatigue state,and the accuracy rate was higher than that of a single information *** summary,fatigue drivingmonitoring has broad development prospects and can be used in traffic accident prevention and wearable dr

关键词： Driving fatigue information fusion EEG blood oxygen

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Vibration-assisted vat photopolymerization for pixelated-aliasing-free surface fabrication

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International Journal of Extreme Manufacturing 2024年第3期6卷 440-456页

作者： Han Xu Renzhi Hu Shuai Chen Junhong Zhu Chi Zhou Yong Chen Center for Advanced Manufacturing University of Southern CaliforniaLos AngelesCA 90007United States of America Daniel J.Epstein department of industrial and systems engineering University of Southern CaliforniaLos AngelesCA 90089United States of America department of Aerospace and Mechanical engineering University of Southern CaliforniaLos AngelesCA 90089United States of America department of industrial and systems engineering University of BuffaloBuffaloNY 14260United States of America

Mask image projection-based vat photopolymerization(MIP-VPP)offers advantages like low cost,high resolution,and a wide material range,making it popular in industry and ***,MIP-VPP employing liquid crystal displays(LCDs)has gained traction,increasingly replacing digital micromirror devices,particularly among hobbyists and in educational settings,and is now beginning to be used in industrial ***,LCD-based MIP-VPPsuffers from pronounced pixelated aliasing arising from LCD’s discrete image pixels and itsdirect-contact configuration in MIP-VPP machines,leading to rough surfaces on the 3D-printed ***,we propose a vibration-assisted MIP-VPP method that utilizes a microscalevibration to uniformize the light intensity distribution of the LCD-based mask image on VPP’s building *** maintaining the same fabrication speed,our technique generates asmoother,non-pixelated mask image,reducing the roughness on flat surfaces and boundary segments of 3D-printed *** light intensity modeling and simulation,we derived an optimal vibration pattern for LCD mask images,subsequently validated by *** assessed the surface texture,boundary integrity,and dimensional accuracy of componentsproduced using the vibration-assisted *** notably smoother surfaces and improved boundary roughness enhance the printing quality of MIP-VPP,enabling its promisingapplications in sectors like the production of 3D-printed optical devices and others.

关键词： additive manufacturing vat photopolymerization piezo vibration sub-pixel resolution aliasing

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Resilence Control of DC Microgrid Integrated with Multi-Nanogrids Considering Connected-Islanded States

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CSEE Journal of Power and Energy systems 2024年第2期10卷 786-796页

作者： Hossien Faraji Reza Hemmati Pierluigi Siano department of Electrical engineering Amirkabir University of TechnologyTehranIran department of Electrical engineering Kermanshah University of TechnologyKermanshahIran department of management&Innovation systems University of Salernoand also with the Department of Electrical and Electronic Engineering ScienceUniversity of JohannesburgJohannesburg 2006South Africa

In this paper, a DC microgrid (DCMG) integrated with a set of nano-grids (NG) is studied. DCMG exchanges predetermined active and reactive power with the upstream network. DCMG and NGs are coordinately controlled and managed in such a way the exchanged P-Q power with external grid are kept on scheduled level following all events and operating conditions. The proposed control system, in addition to the ability of mutual support between DCMG and NGs, makes NGs support each other in critical situations. On the other hand, in all operating conditions, DCMG not only feeds three-phase loads with time-varying active and reactive power on the grid side but also injects constant active power into the grid. During events, NGs support each other, NGs support DCMG, and DCMG supports NGs. Such control strategies are realized by the proposed control method to increase resilience of the system. For these purposes, all resources and loads in DCMG and NGs are equipped with individual controllers. Then, a central control unit analyzes, monitors, and regularizes performance of individual controllers in DCMG and NGs. Nonlinear simulations show the proposed model can effectively control DCMG and NGs under normal and critical conditions.

关键词： Control system DC microgrid nanogrid resilience

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