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41st International Symposium on Automation and Robotics in construction, ISARC 2024

作者： Rangasamy, Veerakumar Yang, Jyh-Bin Graduate Institute Program of Construction Engineering and Management Department of Civil Engineering National Central University Taiwan

ISBN: (纸本)9780645832211

Digital Twin (DT) is a virtual replica that mirrors physical objects, systems, or entities. In the construction sector, DTs play a crucial role in building management, optimizing energy usage, predicting maintenance, and enhancing building lifecycle management. Although effectively integrated into traditional construction practices, its application in the prefabricated construction (PC) field remains relatively limited. Despite its potential to transform the PC, a significant research gap exists in comprehensive literature addressing the approaches, challenges, and requirements specific to this field. This study aims to bridge this gap through a mixed-method research approach that includes bibliometric analysis and systematic review. Publications related to PC and DT are collected from the Scopus database, followed by bibliometric analysis to offer a quantitative insight into the current research trends, prolific authors, and geographical distribution. Furthermore, this study conducts a systematic review that qualitatively analyzes the objectives of DT applications in PC, explores its methodological approaches, identifies challenges and recommendations for practitioners and researchers, and suggests future needs. The findings highlight the pressing need for standardization, robust data management, and scalable solutions to navigate the complexities. Conclusively, this paper presents a comprehensive conceptual framework to facilitate the application of DT in various phases of PC. The critical limitation is the reliance on the publications on the Scopus database and its potential biases. Excluding the need to expand on more emergent publications, discussing empirical DT studies in PC to highlight interoperability and standardization needs is also required for future research. © 2024 ISARC. All Rights Reserved.

关键词： Cyber Physical System

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Generative Design for Prefabricated Structures using BIM and IoT applications – Approaches and Requirements 40

Generative Design for Prefabricated Structures using BIM and...

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40th International Symposium on Automation and Robotics in construction, ISARC 2023

作者： Rangasamy, Veerakumar Yang, Jyh-Bin Graduate Institute Program of Construction Engineering and Management Department of Civil Engineering National Central University Taiwan

ISBN: (纸本)9780645832204

Building Information Modeling (BIM) has demonstrated a wide range of merits over traditional and modern constructions. The integration of generative design (GD) with BIM in the construction industry has become an interesting topic, even though the concept is not very new. Prefabricated construction (PC) offers several advantages over traditional construction and has recently advanced to a new level of study because of the usage of BIM. The synchronization of BIM with PC is becoming simpler to create automatic design solutions in its early phases, thanks to the current breakthroughs in the internet of things (IoT) and its applications. There has been an increase in research interests that are mostly focused on examining tools and applications. However, there are not many studies that have looked at methodological relationships and other factors, which has led researchers to focus more on GD-BIM-based investigations. This study provides a preliminary critical analysis of the software, skill, and methodological requirements for current GD-BIM integration methodologies. The publications are pulled from web of science platform and thoroughly examined in statistical and systematic methods to give a fresh viewpoint on objective-oriented and skill-driven GD-BIM development for PC. New guidance to improve skill learning for GD-BIM development is recommended in this study. The analysis and recommendations might aid the researchers and designers in comprehending the situation and paying attention to future requirements. © ISARC 2023. All rights reserved.

关键词： Internet of things

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Efficient Utilization of Metaheuristic Techniques for Profit Maximization in Combinatorial Production Planning: A Comparative Study 3

Efficient Utilization of Metaheuristic Techniques for Profit...

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3rd IEEE International Conference on Control, Instrumentation, Energy and Communication, CIEC 2024

作者： Mukherjee, Arijit Mukherjee, Surojit Future Institute of Technology Deptartment of Electrical Engineering Kolkata India Great Lakes Institute of Management Post-Graduate Program in Management Chennai India

ISBN: (纸本)9798350313703

Efficient production planning requires well-structured models compatible with metaheuristic and other optimization techniques. This study compares three established metaheuristic methods - sanitized-teaching-learning-based optimization (s-TLBO), Particle Swarm Optimization (PSO), and Differential Evolution (DE) with a termination criterion of equal number of functional evaluations - for profit-maximizing production planning. The focus is on a single-level problem involving complex constraints, non-linear costs, budget and raw material limitations. The paper presents two solution strategies: a penalty-based and a correction-based approach. Analyzing 300 unique instances of the problem reveals that s-TLBO implemented with correction-based approach consistently outperforms the other methods in devising optimal production plans for two Saudi Arabian petrochemical industries with 24 products, 54 processes, and three raw materials for plant 1 and two raw materials for plant 2. © 2024 IEEE.

关键词： Combinatorial optimization

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Optimal Integration of Metaheuristic Techniques with Correction-Based Approaches for Profit Maximization in Combinatorial Production Planning: A Comparative Analysis 3

Optimal Integration of Metaheuristic Techniques with Correct...

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3rd IEEE International Conference on Control, Instrumentation, Energy and Communication, CIEC 2024

ISBN: (纸本)9798350313703

To enhance production planning efficiency, it's crucial to have well-structured models that align with metaheuristic and other optimization techniques. This research conducts a comparative analysis of three unique metaheuristic methods: sanitized-teaching-learning-based optimization (sTLBO), Particle Swarm Optimization (PSO), and Differential Evolution (DE) with a termination criterion of equal number of functional evaluations. The primary focus lies on profit-maximizing production planning within a single-level framework, encompassing intricate domain constraints, nonlinear costs, budget limitations and raw material constraints. The paper introduces three correction-based solution approaches. Upon evaluating 300 distinct instances of the problem, the study reveals that s-TLBO integrated with correction-based approach 1 and 3 consistently outperforms the other methods when it comes to devising optimal production plans for a Saudi Arabian petrochemical industry. This industry scenario involves 24 products, 54 processes, and three raw materials. © 2024 IEEE.

关键词： Combinatorial optimization

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Identification of benefits, challenges, and pathways in E-commerce industries: An integrated two-phase decision-making model

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Sustainable Operations and Computers 2023年第1期4卷 200-218页

作者： Gupta, Srikant Kushwaha, Pooja.S. Badhera, Usha Chatterjee, Prasenjit Gonzalez, Ernesto D.R. Santibanez Department of Operations and Decision Sciences Jaipuria Institute of Management Jaipur India Department of Business Analytics Jaipuria Institute of Management Indore India Department of Business Analytics Jaipuria Institute of Management Jaipur India Department of Mechanical Engineering MCKV Institute of Engineering West Bengal 711204 India Post-Doctoral Fellow Management Graduate Program Universidade Paulista Indianópolis Campus Brazil Department of Industrial Engineering and CES 4.0 Faculty of Engineering University of Talca Curico Chile

The e-commerce industry has seen significant growth over the past decade as it focuses on convenience and accessibility, leading to a surge in online shopping with more and more consumers opting for it. At the same time, the e-commerce industry faces various challenges. In order to fully harness the potential of this industry, it is important to identify its benefits and challenges and focus on pathways to mitigate the challenges and harness its growth. This study utilizes the Delphi approach and involves experts from the e-commerce domain to get their opinions to identify the top ten benefits, challenges, and pathways for the e-commerce industry. Analytic Hierarchy Process (AHP) and Criteria Importance Through Intercriteria Correlation (CRITIC) methods are subsequently, employed to prioritize the identified factors. Results of the study revealed that factors such as affordable advertising & marketing;availability and product variety;and Global reachability are the most important benefits, while technological upgradation;returns or refunds;and counterfeit products posed the greatest challenges for the industry. Government compliance check;better relationship with delivery partners;and strong data privacy and online security policies emerged as the best pathways. This study also provides valuable insights to businesses, policymakers, and researchers in the e-commerce industry on how to navigate the benefits, challenges, and pathways of this rapidly growing sector. © 2023

关键词： Electronic commerce

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Smart Fuel Supply Pumps and the Possibilities of Reducing Losses in Time and Costs 12th

Smart Fuel Supply Pumps and the Possibilities of Reducing Lo...

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12th International Conference on Information Systems and Advanced Technologies, ICISAT 2022

作者： Majid, Zaid Latfi Ulutagay, Gözde Institute of Graduate Studies Engineering Management Program Istanbul Gedik University Istanbul Turkey Industrial Engineering Department Engineering Faculty Istanbul Gedik University Istanbul Turkey

ISBN: (纸本)9783031253430

This research depends on the development of the marketing of gasoline for cars in a simplified way, with an explanation of the stages of development of fossil fuels and the nature of its extraction and consumption, as well as the production processes of this fuel with knowledge of the damages of fossil fuels and ways to reduce these damages, as well as ways to raise the efficiency of gasoline. Low-octane gasoline and alcohol Selling multiple octane fuels from a single outlet, and this has many benefits, which we will explain during our search. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Ethanol Fuel smart pumps High octane fuel Smart fuel marketing

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Preliminary Plan for Data Collection on Stakeholder Information Interdependence in Area-Business Continuity management: A Case Study of Flood management in Thai Industrial Zones 23

Preliminary Plan for Data Collection on Stakeholder Informat...

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23rd International Symposium on Communications and Information Technologies, ISCIT 2024

作者： Arayachookiat, Penpitcha Saengtabtim, Kumpol Kodaka, Akira Leelawat, Natt Tang, Jing Watanabe, Kenji Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Chulalongkorn University Disaster and Risk Management Information Systems Research Unit Bangkok Thailand Graduate School of System Design and Management Keio University Kanagawa Japan International School of Engineering Chulalongkorn University Faculty of Engineering Bangkok Thailand Graduate School of Social Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (纸本)9798350353952

The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness. © 2024 IEEE.

关键词： Area-Business Continuity management Flood Index of Item-Objective Congruence Information Interdependence

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Atmospheric Meteorological Effects on Forecasting Daily Lightning Occurrence at Cape Canaveral Space Force Station

Atmospheric Meteorological Effects on Forecasting Daily Ligh...

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2023 Congress in Computer Science, Computer engineering, and Applied Computing, CSCE 2023

作者： Saul, Jon Wagner, Torrey Mbonimpa, Eric Langhals, Brent Graduate School of Engineering and Management Air Force Institute of Technology Data Analytics Certificate Program Wright-Patterson AFBOH United States

ISBN: (纸本)9798350327595

As the Cape Canaveral Space Force Station and Kennedy Space Center increase their launch rate, any process that could assist in the automation of the currently-manual lightning forecast would be valuable. This work examines the possibility of machine-learning assistance with the daily lighting forecast which is produced by the 45th Weather Squadron. A dataset consisting of 34 lightning, pressure, temperature and windspeed measurements taken from 334 daily weather balloon (rawinsonde) launches in the timeframe 2012-2021 was examined. Models were created using recursive feature elimination on logistic regression and XGClassifier algorithms, as well as Bayesian and bandit optimization of neural network (NN) hyperparameters. The modeling process was repeated after eliminating 13 features related to windspeed. The best performing models on both datasets were the optimized NN models, with an F1 metric of 0.79 on the full dataset and 0.66 on the reduced dataset. For comparison, a model that predicted randomly achieved F1 = 0.47 on this dataset. The addition of 13 windspeed-related features more than doubled the complexity of the 21-feature no-wind model while increasing model performance by 13 percentage points. A notable inference from the statistical modeling is that the most important feature from both datasets was the Thompson convective index, which is related to temperature, dewpoint, relative humidity and lapse rate. © 2023 IEEE.

关键词： launch operations lightning forecast lightning indices neural network

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Comprehensive Geometric Modeling of the Sibayak Geothermal Field

Comprehensive Geometric Modeling of the Sibayak Geothermal F...

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2024 International Conference on Applied Sciences and Material Applications, ICASMA 2024

作者： Qarinur, M. Silitonga, E.M.R. Alvan, S. Ogata, S. Kinoshita, N. Yasuhara, H. Civil Engineering Study Program Universitas Negeri Medan Medan20221 Indonesia Construction Management Study Program Universitas Negeri Medan Medan20221 Indonesia Division of Global Architecture Graduate School of Engineering Osaka University Osaka565-0871 Japan Department of Civil and Environmental Engineering Ehime University Matsuyama790-8577 Japan Department of Urban Management Kyoto University Kyoto615-8540 Japan

Geothermal reservoirs are significant sources of renewable energy. Accurate geometric modeling of these reservoirs is essential for understanding the distribution of heat and fluid dynamics within them. This study aims to develop a geometric model of the Sibayak geothermal field using borehole data. Borehole data provide detailed geological information, which is crucial for constructing a realistic geometric model. The methodology of this research involves several key steps: the collection of borehole data from the Sibayak geothermal field, the construction of a 3D geometric model of the reservoir using COMSOL Multiphysics based on the borehole data, and the validation of the model through comparison with field data and previous research findings. The results indicate that the developed geometric model successfully identifies zones with high geothermal potential and provides an accurate depiction of the reservoir's boundaries and characteristics. Modeling the geometry of geothermal reservoirs using borehole data offers profound insights into the internal dynamics of the reservoir and can serve as a valuable tool for planning and optimizing geothermal energy exploitation. © 2024 institute of Physics Publishing. All rights reserved.

关键词： Geothermal fields

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Machine-learning-based sampling inspection under OQC capacity for real-time quality monitoring in the TFT-LCD industry

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International Journal of Production Research 2025年第6期63卷 2090-2113页

作者： Shih, Ming-Sung Chen, James C. Chen, Tzu-Li Chiang, Chih-Hsiung Hsu, Ching-Lan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu Taiwan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan Graduate Institute of Intelligent Manufacturing Technology National Taiwan University of Science and Technology Taipei Taiwan Division of Quality Control AUO Corporation Taichung Taiwan

In the thin film transistor-liquid crystal display (TFT-LCD) industry, the competition is fierce, and the external failure cost is high. To improve the quality of released products, sampling inspection under outgoing quality control (OQC) is conducted before products are released. Owing to the variety and complexity of inspection items, the task must be carried out manually while realising automation is difficult. Traditional random sampling inspection is limited by sampling quantity, manpower, and material resources. To effectively improve acceptable quality levels, this paper proposes a quality predictive monitoring framework tailored to the production and inspection characteristics of the TFT-LCD industry. This framework includes real-time automatic quality monitoring based on an optimal machine learning prediction model with two-phase feature creation, and it also addresses OQC inspection capacity constraints. Experimental results show the prediction performance based on proposed model is better than the traditional random sampling process. In practice, superior average outgoing quality improves by more than 70% at the same sampling level. In addition, the features of the process can be further controlled and managed based on the prediction model to monitor the key parameters in real time and respond to abnormalities quickly, thereby further improving the quality of released products. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Liquid crystal displays

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