Article
Construction & Building Technology
Sitsofe Kwame Yevu, Emmanuel Kingsford Owusu, Albert P. C. Chan, Samad M. E. Sepasgozar, Vineet R. Kamat
Summary: This study demonstrates the importance of digital twin (DT) applications and real-time carbon emissions monitoring in prefabrication supply chain (PSC) through mixed-method analysis.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Business
Martin Beaulieu, Omar Bentahar
Summary: The healthcare supply chain lags behind other industries in terms of digitalization and best practices. This article proposes a roadmap centered on hospitals for implementing digitalization initiatives to address the challenges in the healthcare supply chain. Digitalization proposals are structured in terms of priority and can help improve supply chain and clinical flows.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Article
Chemistry, Multidisciplinary
Dongmin Lee, SangHyun Lee
Summary: This study developed a digital twin framework that integrates IoT, BIM, and GIS technologies for real-time logistics simulation in modular construction projects, aiming to predict potential logistics risks and accurate module arrival time.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Interdisciplinary Applications
Cunbo Zhuang, Tian Miao, Jianhua Liu, Hui Xiong
Summary: Digital twin (DT) technology provides a novel, feasible, and clear implementation path for smart manufacturing and cyber-physical systems (CPS). DT is applied to various stages of the product lifecycle, including design, production, and service, with shop-floor digital twin (SDT) serving as a digital mapping model of the physical shop-floor. Challenges exist in building and applying SDT, particularly in the production phase.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Article
Computer Science, Information Systems
Bin Hu, Hui Guo, Xiongjie Tao, Yingyi Zhang
Summary: The current stereo warehouse in the cold chain logistics industry faces problems such as high product loss rate, severe temperature deviations, and low level of informatization. To address these issues, this study focuses on operational scenarios and designs a five-dimensional digital twin model for cold chain logistics warehouses. By integrating data from multiple sources, it achieves real-time visualization and monitoring of warehouse elements and proposes a system-linked decision-making optimization strategy. The digital twin system reduces the loss rate of fresh vegetables by 25-30% and offers new possibilities for improved packaging and ensuring food quality and safety in cold chain logistics warehouses.
Article
Agronomy
Marius Drechsler, Andreas Holzapfel
Summary: This paper investigates planning problems in the supply chain of small and medium-sized companies in the horticultural market. It highlights the challenges faced by the sector and the need for data-driven decision support systems. Expert interviews and a literature review are conducted to explore the practical planning problems and identify research gaps. The paper contributes to an understanding of planning problems and decision-making in horticultural supply chains and provides an overview of the current research status and future research directions.
Article
Computer Science, Interdisciplinary Applications
Praveen Vijaya Raj Pushpa Raj, Sunil Kumar Jauhar, M. Ramkumar, Saurabh Pratap
Summary: Timely payment is crucial for efficient supply chain management. Traditional manual payment processes are inefficient and error-prone. This study proposes a blockchain-based smart contract solution that enables decentralized authorization, process automation, and information sharing between supply chain stakeholders. The proposed solution reduces payment risk for suppliers, improves delivery performance for buyers, and lowers costs for third-party logistics providers.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Business
Xue-Feng Shao, Wei Liu, Yi Li, Hassan Rauf Chaudhry, Xiao-Guang Yue
Summary: While industry 4.0 has gained some traction, smart supply chains are still in their early stages with limited research on implementation issues at the supply chain level. This study takes an exploratory approach to examine the implementation of industry 4.0 concepts across multiple tiers of the supply chain and proposes a multistage implementation framework.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Article
Computer Science, Interdisciplinary Applications
F. Coelho, S. Relvas, A. P. Barbosa-Povoa
Summary: This study proposed a simulation-based decision support tool for analyzing in-house logistics activities in distribution and production facilities towards logistics 4.0. Two simulation models were developed using Simio, which were verified and validated based on real-world operations. The models are representative of reality and can be applied in different in-house logistics settings for operations improvement without disruption.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Business
Eleonora Di Maria, Valentina De Marchi, Ambra Galeazzo
Summary: Industry 4.0 technologies are expected to contribute to better circular economy outcomes by improving integration levels within the supply chain and within firms. Smart manufacturing technologies have a stronger impact on circular economy results compared to data processing technologies.
BUSINESS STRATEGY AND THE ENVIRONMENT
(2022)
Article
Economics
Manimuthu Arunmozhi, V. G. Venkatesh, Sobhan Arisian, Yangyan Shi, V. Raja Sreedharan
Summary: This paper investigates how Artificial Intelligence and Blockchain-based Smart Contracts can enhance sustainable supply chain operations. By developing a novel design element to obtain reliable predictive analytics results and testing the concept, reductions in energy wastage and hidden financial transactions were observed.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Engineering, Industrial
Alessandra Cantini, Mirco Peron, Filippo De Carlo, Fabio Sgarbossa
Summary: This paper aims to assist managers and practitioners in determining how to design their spare parts supply chains and adopt the appropriate manufacturing technology through the development of a decision support system. The authors propose a user-friendly decision tree that allows comparison of total costs between different levels of centralization and between additive manufacturing and conventional manufacturing for spare parts.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Sonia Cisneros-Cabrera, Grigory Pishchulov, Pedro Sampaio, Nikolay Mehandjiev, Zixu Liu, Sophia Kununka
Summary: Industry 4.0 technologies, process digitalisation, and automation can facilitate the formation of supply chain collaborations in manufacturing, enabling independent companies to collaborate to seize new business opportunities. With the support of assistive processes and technologies, collaborative teams can be quickly formed, increasing the chances of successfully bidding for projects.
COMPUTERS IN INDUSTRY
(2021)
Article
Construction & Building Technology
Weisheng Lu, Xiao Li, Fan Xue, Rui Zhao, Liupengfei Wu, Anthony G. O. Yeh
Summary: This study introduces a framework utilizing smart construction objects as blockchain oracles, successfully developing and validating a blockchain-enabled construction supply chain management system, with a specific focus on the operation of four smart contracts.
AUTOMATION IN CONSTRUCTION
(2021)
Review
Construction & Building Technology
De-Graft Joe Opoku, Srinath Perera, Robert Osei-Kyei, Maria Rashidi
Summary: Digital twin (DT) technology, with its potential to transform the construction industry and address its challenges, has attracted significant attention and is rapidly developing. This study comprehensively reviewed and analyzed the current state of DT applications in the construction industry, providing a theoretical basis for the widespread adoption of this technology in the industry.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Management
Toni Greif, Nikolai Stein, Christoph M. Flath
Summary: Supply chains in the construction industry are less efficient due to the lack of accurate, up-to-date information. A value of information analysis was conducted on a leading supplier of building materials to guide future investments in costly sensors for silo fill-level monitoring. The optimal purchase level of information for different hardware costs and service levels was determined, resulting in approximately 50% sensor-equipped silos for medium and high annual sensor costs. These findings on the use of information technology are relevant for suppliers aiming to improve decision making and stand out with service guarantees.
INFORMS JOURNAL ON APPLIED ANALYTICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Francesco Pistolesi, Michele Baldassini, Beatrice Lazzerini
Summary: More than one in four workers worldwide suffer from back pain, resulting in the loss of 264 million work days annually. In the U.S., it costs $50 billion in healthcare expenses each year, rising up to $100 billion when accounting for decreased productivity and lost wages. The impending Industry 5.0 revolution emphasizes worker well-being and their rights, such as privacy, autonomy, and human dignity. This paper proposes a privacy-preserving artificial intelligence system that monitors the posture of assembly line workers. The system accurately assesses upper-body and lower-body postures while respecting privacy, enabling the detection of harmful posture habits and reducing the likelihood of musculoskeletal disorders.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Xavier Boucher, Camilo Murillo Coba, Damien Lamy
Summary: This paper explores the new business strategies of digital servitization and smart PSS delivery, and develops conceptual prototypes of smart PSS value offers for early stages of the design process. It presents the development and experimentation of a modelling language and toolkit, and applies it to the design of a smart PSS in the field of heating appliances.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Dieudonne Tchuente, Jerry Lonlac, Bernard Kamsu-Foguem
Summary: Artificial Intelligence (AI) is becoming increasingly important in various sectors of society. However, the black box nature of most AI techniques such as Machine Learning (ML) hinders their practical application. This has led to the emergence of Explainable artificial intelligence (XAI), which aims to provide AI-based decision-making processes and outcomes that are easily understood, interpreted, and justified by humans. While there has been a significant amount of research on XAI, there is currently a lack of studies on its practical applications. To address this research gap, this article proposes a comprehensive review of the business applications of XAI and a six-step framework to improve its implementation and adoption by practitioners.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Francois-Alexandre Tremblay, Audrey Durand, Michael Morin, Philippe Marier, Jonathan Gaudreault
Summary: Continuous high-frequency wood drying, integrated with a traditional wood finishing line, improves the value of lumber by correcting moisture content piece by piece. Using reinforcement learning for continuous drying operation policies outperforms current industry methods and remains robust to sudden disturbances.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Luyao Xia, Jianfeng Lu, Yuqian Lu, Wentao Gao, Yuhang Fan, Yuhao Xu, Hao Zhang
Summary: Efficient assembly sequence planning is crucial for enhancing production efficiency, ensuring product quality, and meeting market demands. This study proposes a dynamic graph learning algorithm called assembly-oriented graph attention sequence (A-GASeq), which optimizes the assembly graph structure to guide the search for optimal assembly sequences. The algorithm demonstrates superiority and broad utility in real-world scenarios.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Mutahar Safdar, Padma Polash Paul, Guy Lamouche, Gentry Wood, Max Zimmermann, Florian Hannesen, Christophe Bescond, Priti Wanjara, Yaoyao Fiona Zhao
Summary: Metal-based additive manufacturing can achieve fully dense metallic components, and the application of machine learning in this field has been growing rapidly. However, there is a lack of framework to manage these machine learning models and guidance on the fundamental requirements for a cross-disciplinary platform to support process-based machine learning models in industrial metal AM.
COMPUTERS IN INDUSTRY
(2024)