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

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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

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

A systematic framework of constructing surrogate model for slider track peeling strength prediction

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Science China Technological Sciences 2024年第10期67卷 3261-3274页

作者： DONG XingJian CHEN Qian LIU WenBo WANG Dong PENG ZhiKe MENG Guang State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University KEIPER Seating Mechanisms Co. Ltd. Department of industrial Engineering and management Shanghai Jiao Tong University

Peeling strength can comprehensively reflect slider track safety and is crucial in car seat safety assessments. Current methods for determining slider peeling strength are primarily physical testing and numerical simulation. However, these methods encounter the potential challenges of high costs and overlong time consumption which have not been adequately addressed. Therefore, the efficient and low-cost surrogate model emerges as a promising solution. Nevertheless, currently used surrogate models suffer from inefficiencies and complexity in data sampling, lack of robustness in local model predictions, and isolation between data sampling and model prediction. To overcome these challenges, this paper aims to set up a systematic framework for slider track peeling strength prediction, including sensitivity analysis, dataset sampling, and model prediction. Specifically, the interpretable linear regression is performed to identify the sensitivity of various geometric variables to peeling strength. Based on the variable sensitivity, a distance metric is constructed to measure the disparity of different variable groups. Then, the sparsity-targeted sampling(STS) is proposed to formulate a representative dataset. Finally, the sequentially selected local weighted linear regression(SLWLR) is designed to achieve accurate track peeling strength prediction. Additionally, a quantitative cost assessment of the supplementary dataset is proposed by utilizing the minimum adjacent sample distance as a mediator. Experimental results validate the efficacy of sequential selection and the weighting mechanism in enhancing localization ***, the proposed SLWLR method surpasses similar approaches and other common surrogate methods in terms of prediction performance and data quantity requirements, achieving an average absolute error of 3.3 kN in the simulated test dataset.

关键词： slider track peeling strength surrogate model sensitivity analysis data sampling local weighted linear regression

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eQUEST Based Building Energy Modeling Analysis for Energy Efficiency of Buildings

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Energy Engineering 2024年第10期121卷 2743-2767页

作者： Saroj Lamichhane Roseline Mostafa Bhaskaran Gopalakrishnan Dayakar G.Devaru Regional Mechanical Field AmazonWeb ServicesHerndonVA 20170USA industrial and management Systems Engineering West Virginia UniversityMorgantownWV 26505USA industrial and Production Engineering JSS Science&Technology UniversityMysuru570006India

Building energy performance is a function of numerous building *** this study,sensitivity analysis on twenty parameters is performed to determine the top three parameters that have the most significant impact on the energy performance of *** data from two fully operational commercial buildings were collected and used to develop a building energy model in the Quick Energy Simulation Tool(eQUEST).The model is calibrated using the Normalized Mean Bias Error(NMBE)and Coefficient of Variation of Root Mean Square Error(CV(RMSE))*** model satisfies the NMBE and CV(RMSE)criteria set by the American Society of Heating,Refrigeration,and Air-Conditioning(ASHRAE)Guideline 14,Federal Energy management Program(FEMP),and International Performance Measurement and Verification Protocol(IPMVP)for building energy model *** values of the parameters are varied in two levels,and then the percentage change in output is *** factorial analysis on eight parameters with the highest percentage change in energy performance is performed at two levels in a statistical software *** building A,the top 3 parameters from the percentage change method are:Heating setpoint,cooling setpoint and server *** fractional factorial design,the top 3 parameters are:heating setpoint(p-value=0.00129),cooling setpoint(p-value=0.00133),and setback control(p-value=0.00317).For building B,the top 3 parameters from both methods are:Server room(pvalue=0.0000),heating setpoint(p-value=0.00014),and cooling setpoint(p-value=0.00035).If the best values for all top three parameters are taken simultaneously,energy efficiency improves by 29%for building A and 35%for building B.

关键词： Energy efficiency eQUEST energy consumption building energy modeling

Can the integration between urban and rural areas be realized?A new theoretical analytical framework

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Journal of Geographical Sciences 2024年第1期34卷 3-24页

作者： WANG Yi LU Yuqi ZHU Yingming Research Base of Jiangsu industrial Cluster School of Economics and ManagementNanjing University of Science and TechnologyNanjing 210094China School of Geography Nanjing Normal UniversityNanjing 210023China

Urban-rural integration is an advanced form resulting from the future evolution of urban-rural ***,little research has explored whether urban and rural areas can move from dual segmentation to integrated development from a theoretical or empirical *** on the research framework of welfare economics,which offers an appealing paradigm to frame the underlying game between cities and villages,this study clarifies the ideal state of urban-rural *** then proposes a series of basic assumptions,and constructs a corresponding objective function and its ***,it assesses the possibility of seeing the transmutation from division to integration between urban and rural areas with continuous socio-economic *** authors argue that the ideal state of urban-rural integration should be a Pareto-driven optimal allocation of urban-rural resources and outputs,and the maximization of social welfare in the entire *** on a systematic demonstration using mathematical models,the study proposes that urban and rural areas can enter this ideal integrated development pattern when certain parameter conditions are *** general,this study demonstrates the theoretical logic and scientific foundations of urban-rural integration,enriches theoretical studies about urban-rural relationships,and provides basic theoretical support for large developing countries to build a coordinated and orderly urban-rural community with a shared future.

关键词： urban-rural integration development ideal state parameter conditions welfare economics theoretical framework

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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 *** 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 *** industrial Internet serves as a crucial cornerstone and essential support for the Fourth industrial Revolution,offering specific approaches for industrial digital *** 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

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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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

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