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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 pandemic.This,in turn,had a knock-on effect on other industries around the globe.Sustaining the impact of the disruption posed a major challenge for the industry.This 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 pandemic.Fifteen drivers were identified based on an extensive literature review and a survey conducted with experts working in the Oil and Gas industry.Multi-criteria decision-making methodologies were used to analyze these drivers.The 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 importance.Furthermore,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 calculations.This study can support the governmental institutions in benchmarking the Oil and Gas industry based on its sustainability index.Additionally,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 disruption.This 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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Evaluating innovation ecosystem resiliency using agent-based modeling and systems dynamics

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Journal of Safety Science and Resilience 2024年第2期5卷 204-221页

作者： Soheila Abdi Mehdi Yazdani Esmaeil Najafi department of industrial engineering Science and Research BranchIslamic Azad UniversityTehranIran department of industrial engineering Qazvin BranchIslamic Azad UniversityQazvinIran

Evaluating the resilience of the innovation ecosystem to maintain its performance,in the sense of resistance to disruption and recovery after it,has recently received more attention.Several studies have been conducted to model different ecosystems and evaluate their resilience.However,modeling the innovation ecosystem from a holistic perspective and performing a quantitative assessment of its resilience have received less attention.This paper models the innovation ecosystem holistically and evaluates its resilience index using a quantitative approach through five main steps.In the first step,a case study related to the innovation ecosystem of Iran's Ministry of Energy,called the Power Innovation Ecosystem,is modeled by combining system dynamics and agent-based modeling.Upon validating the model in the second step,the disruption of the loss of experts is investigated in the third step,and all possible actions to recover each actor are analyzed.In the fourth step,the performance of the ecosystem is simulated before and after the disruption using the data gathered in the previous steps.Finally,resilience is calculated in two different ways in the fifth step.Several improvement solutions are also suggested when considering that the resilience index of the innovation ecosystem is at a medium level.This research may assist policymakers in observing the resilience level of the innovation ecosystem based on the proposed model.By applying strategic changes to this model,they can determine the effects of their policies and make the most appropriate decisions to increase the resilience of the innovation ecosystem.

关键词： Resilience index innovation ecosystem system dynamics Agent-based modeling

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Improve the industrial digital transformation through industrial Internet platforms

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Frontiers of engineering management 2024年第1期11卷 167-174页

作者： Ran LIU Xiaolei XIE department of industrial engineering&management Shanghai Jiao Tong UniversityShanghai 200240China department of industrial engineering Tsinghua UniversityBeijing 100084China

1 Introduction 1.1 Definition and stakeholders of the industrial Internet The industrial Internet is a novel network technology system that applies the Internet of Things(IoT)to the manufacturing and industrial sectors.It facilitates the connection of various sensors,devices,systems,factories,and enterprises,enabling the sharing and exchange of data to improve production efficiency,reduce costs,enhance product quality,and enable smart manufacturing.The industrial Internet serves as a crucial cornerstone and essential support for the Fourth industrial Revolution,offering specific approaches for industrial digital transformation.Through the comprehensive interconnection of people,machines,and things,the industrial Internet analyzes various data from intelligent feedback,fostering the development of a new manufacturing and service system.

关键词： industrial digital transformation industrial Internet platform manufacturing big data

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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 research.This article presents a perspective on how resilience could be quantitatively assessed through a set of indices.It starts with a brief explanation of resilience in the context of supply chain and a quick summary of existing quantitative measures of resilience.It 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 cycle.In particular,it is proposed that resilience should be evaluated according to different time periods,i.***.before,during and after a disruption has occurred.Four dimensions of resilience,namely reliability,robustness,recovery and reconfigurability,can then be used to make up a set of indices for resilience.For numerical illustration,these indices are computed based on recovery data arising from Hurricane Sandy in October 2012.Finally,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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Design of a large-scale model for wind tunnel test of a multiadaptive flap concept

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Chinese Journal of Aeronautics 2024年第2期37卷 58-80页

作者： Mürüvvet Sinem SICIM DEMIRCI Rosario PECORA Metin Orhan KAYA Aeronautical engineering department Istanbul Technical UniversityIstanbulTurkey industrial engineering department University of Naples Federico IINapoliItaly

The design and application of morphing systems are ongoing issues compelling the aviation industry.The Clean Sky-program represents the most significant aeronautical research ever launched in Europe on advanced technologies for greening next-generation aircraft.The primary purpose of the program is to develop new concepts aimed at decreasing the effects of aviation on the environment,increasing reliability,and promoting eco-friendly mobility.These ambitions are pursued through research on enabling technologies fostering noise and gas emissions reduction,mainly by improving aircraft aerodynamic performances.Within the Clean Sky framework,a multimodal morphing flap device was designed based on tight industrial requirements and tailored for large civil aircraft applications.The flap is deployed in one unique setting,and its cross section is morphed differently in take-off and landing to get the necessary extra lift for the specific flight phase.Moreover,during the cruise,the tip of the flap is deflected for load control and induced drag reduction.Before manufacturing the first flap prototype,a high-speed(Ma=0.3),large-scale test campaign(geometric scale factor 1:3)was deemed necessary to validate the performance improvements brought by this novel system at the aircraft level.On the other hand,the geometrical scaling of the flap prototype was considered impracticable due to the unscalability of the embedded mechanisms and actuators for shape transition.Therefore,a new architecture was conceived for the flap model to comply with the scaled dimensions requirements,withstand the relevant loads expected during the wind tunnel tests and emulate the shape transition capabilities of the true-scale flap.Simplified strategies were developed to effectively morph the model during wind tunnel tests while ensuring the robustness of each morphed configuration and maintaining adequate stiffness levels to prevent undesirable deviations from the intended aerodynamic shapes.Additionally,a simplified design was conceived for the flap-w

关键词： Morphing structures Smart aircraft Morphing flap Adaptive systems Finger-like ribs Wind tunnel tests Large-scale morphing archi-tectures Variable camber airfoil

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A novel low-cost visual ear tag based identification system for precision beef cattle livestock farming

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Information Processing in Agriculture 2024年第1期11卷 117-126页

作者： Andrea Pretto Gianpaolo Savio Flaviana Gottardo Francesca Uccheddu Gianmaria Concheri department of Civil Environmental and Architectural EngineeringUniversity of PaduaItaly department of Animal Medicine Production and HealthUniversity of PadovaItaly department of industrial engineering University of PadovaItaly

The precision livestock farming(PLF)has the objective to maximize each animal's performance while reducing the environmental impact and maintaining the quality and safety of meat production.Among the PLF techniques,the personalised management of each individual animal based on sensors systems,represents a viable option.It is worth noting that the implementation of an effective PLF approach can be still expensive,especially for small and medium-sized farms;for this reason,to guarantee the sustainability of a customized livestock management system and encourage its use,plug and play and cost-effective systems are needed.Within this context,we present a novel low-cost method for identifying beef cattle and recognizing their basic activities by a single surveillance camera.By leveraging the current state-of-the-art methods for real-time object detection,(i.e.,YOLOv3)cattle's face areas,we propose a novel mechanism able to detect the ear tag as well as the water ingestion state when the cattle is close to the drinker.The cow IDs are read by an Optical Character Recognition(OCR)algorithm for which,an ad hoc error correction algorithm is here presented to avoid numbers misreading and correctly match the IDs to only actually present IDs.Thanks to the detection of the tag position,the OCR algorithm can be applied only to a specific region of interest reducing the computational cost and the time needed.Activity times for the areas are outputted as cattle activity recognition results.Evaluation results demonstrate the effectiveness of our proposed method,showing a mAP@0.50 of 89%.

关键词： Precision livestock farming Deep learning Cattlei dentification Low-cost sensors Computer vision

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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 industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To 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 schemes.To 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 proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The 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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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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A study of the effect of local scour on the flow field near the spur dike

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Theoretical & Applied Mechanics Letters 2024年第2期14卷 98-105页

作者： Yu-Tian Li Jie-Min Zhan Wing-Hong Onyx Wai department of industrial Design School of Industrial Design and Ceramic ArtFoshan UniversityFoshan 528000China department of Applied Mechanics and engineering Shenzhen Campus of Sun Yat-sen UniversityShenzhen 518107China department of Civil and Environmental engineering The Hong Kong Polytechnic UniversityHong Kong 999077China

The flow field near a spur dike such as down flow and horseshoe vortex system(HVS)are susceptible to the topographic changes in the local scouring process,resulting in variation of the sediment transport with time.In this study,large eddy simulations with fixed-bed at different scouring stages were conducted to investigate the changes in flow field.The results imply that the bed deformation leads to an increase in flow rate per unit area,which represent the capability of sediment transportation by water,in the scour hole.Moreover,the intensity of turbulent kinetic energy and bimodal motion near the sand bed induced by the HVS were also varied.However,the peak moments between the two sediment transport mechanisms were different.Hence,understanding the complex feedback mechanism between topography and flow field is essential for the local scour problem.

关键词： Spur dike Local scour Large eddy simulation Down flow Horseshoe vortex system

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Rhodium-catalyzed Doyle-Kirmse rearrangement reactions of sulfoxoniun ylides

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Chinese Chemical Letters 2024年第4期35卷 363-366页

作者： Ying-Di Hao Zhi-Qian Lin Xiao-Yu Guo Jiao Liang Can-Kun Luo Qian-Tao Wang Li Guo Yong Wu Key Laboratory of Drug-Targeting and Drug Delivery system of the Education Ministry and department of Medicinal Chemistry Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial TechnologyWest China School of PharmacySichuan UniversityChengdu 610041China

Doyle-Kirmse rearrangement reactions have received continuous attention as an important method for constructing complex chemical structures. Herein, we disclosed an efficient rhodium-catalyzed DoyleKirmse rearrangement reaction, which can simultaneously construct C–C bonds and C–X(X = S/Se) bonds using sulfoxonium ylides as starting materials to obtain sulfur-or selenium-containing compounds. This strategy is characterized by the safer and greener carbene precursor, high yields and broad substrate scope, possessing a wide range of application.

关键词： Sulfoxonium ylides Rhodium(Ⅱ)-catalyzed Carbene Rearrangement reactions One-pot process

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