Smart Logistics Research Articles

Enhancing brewery logistics with smart kegs: A simulation study

Background: Supply chain optimisation is critical for companies in today’s globalised world. Efficient supply chains ensure product quality and freshness in the food industry. For products like beer, efficiency extends beyond transportation and includes the management of logistics containers such as returnable kegs.Objectives: This study investigated the impact of tracking logistics data on the efficiency of container logistics in a small regional brewery. The focus was reducing fleet size, processing times and pick-up distances.Method: A simulation of a small brewery was used to analyse the impact of tracking logistics data. The study examined how kegs equipped with real-time tracking technology could improve logistics operations.Results: The simulation showed that tracking logistics data significantly improved logistics processes. It led to a reduction in the fleet size, turnaround times and pick-up distances for empty kegs. These improvements were attributed to better resource allocation and more efficient management of reusable containers.Conclusion: The study showed that smart kegs could reduce logistical inefficiencies in the brewing industry. The use of smart technologies in container logistics improves operational efficiency and sustainability.Contribution: This research provides insights into how smart technologies can transform traditional logistics models. The results suggest that smart containers can revolutionise supply chains with efficient resource allocation, real-time tracking and automation. This shift towards smart logistics aligns with the broader adoption of the Industrial Internet of Things, offering a blueprint for future innovations in supply chain management. The implications extend beyond brewing, highlighting the potential for greater sustainability and a positive reduction in environmental impact in global supply chains.

Coupling Coordination and Data Management for Additive Manufacturing Systems Based on Smart Logistics

Additive Manufacturing (AM) has rapidly advanced due to its benefits in reducing material consumption and resource requirements, offering significant opportunities for energy-efficient and environmentally friendly production. As manufacturing technologies evolve, there is growing interest in smart manufacturing, prompting both academia and industry to explore ways to enhance efficiency and sustainability. Effective logistics management plays a crucial role in this context, requiring precise data prediction and optimization. This article introduces a Smart Logistics service to foster dynamic coordination within the smart logistics ecosystem. The first step is to integrate smart logistics components that can communicate effectively and provide specific value-added services. This integration aims to support contemporary industrial and production environments by enhancing decision-making models. The second step involves applying the Coupling Coordination model to assess the development of logistics in conjunction with broader economic growth. This model helps in constructing a high-quality development index system for logistics, which is essential for evaluating the efficiency of logistics operations. The third step is to evaluate the coordination between the automotive, digitalization, and logistics sectors. This assessment provides insights into the overall development levels of cities and highlights the significant impact on sustainable growth within the automotive industry. The final step includes analyzing the progress of coupling coordination in Indian provinces, identifying the transition from minor imbalances to primary coordination, and forecasting that strong coordination will be achieved by 2025. This analysis underscores the potential for mutual growth and cooperation by elevating the logistics sector’s standards and strengthening inter-industry relationships.

Logistics Business Management of Provider in Thailand with Smart Logistics

The objective of this study is to validate the model fitness in Thailand for logistics business management related to the adoption of Smart Logistics (SLAPR) and its influence, in respect of service providers, thus coming up with a decision-making plan. The quantitative research was employed in the process, and the sample size is six large logistics service providers, 400 respondents in Thailand. The research instrument consisted of a five-section questionnaire with a total number of questions of 108. A number of statistical methods were employed for data analysis, including the usage of structural equation modeling (SEM). The model consists of four constructs: Smart Logistics: Administration and Management (SLA), Smart Logistics: People Management (SLP), Smart Logistics: Rooms and Working Space Management (SLR), and Performance (PSH). The model fits satisfactorily and is therefore appropriate for strategic use in large logistics firms in Thailand engaged in the provision of international logistics services including maritime and air freight, dangerous goods transportation, port services for exports, warehouse renting services, customs clearance, and supply chain management from upstream to downstream. This study identifies the performance outcomes: reducing errors, cost reduction, reducing complexity, labor reduction, and operational efficiency improvement. PSH is directly influenced by the SLA construct with a direct effect (DE) value of 0.82. The results of the above results explained that company executives have to implement Smart Logistics as soon as possible so that results are achievable in one year.

Circular supply chain transformation: leveraging evolving technologies for enhanced performance

ABSTRACT Circular supply chains (CSC) and evolving technologies work together to enhance supply chain performance. To assess this, we examine the integration of technologies, such as Industry 4.0, smart manufacturing, and smart logistics in a CSC setup. The study focuses on two product types: smart and normal (non-smart) products. Smart products feature sensing, connectivity, networking, and monitoring capabilities, while normal products lack these features. Using a multi-objective optimisation technique, we analyse the CSC network to estimate the benefits of evolving technologies. The study aims to maximise profits and minimise carbon emissions across the supply chain. Eleven models are examined based on varying demand percentages of smart and normal products. The gamultiobj algorithm (a variant of NSGA II) is used to generate Pareto frontiers. The findings show that a 2-5% increase in technology adoption costs can boost profits by 15-30% and reduce emissions by 20-30% for smart products.

Smart Logistics Facing Industry 5.0: Research on Key Enablers and Strategic Roadmap

While Industry 4.0 has played a significant role in advancing smart logistics, it has yet to provide adequate solutions for widespread concerns such as human centricity, sustainability, and resilience. The emergence of Industry 5.0 addresses and complements these shortcomings of Industry 4.0. However, there is currently a notable gap in the research regarding how Industry 5.0 can drive the transformation of smart logistics. To address this gap, this study develops a strategic roadmap that offers a solution to this issue. The research is initiated by conducting a comprehensive literature review with a focus on content, identifying 13 key enablers crucial for realizing smart logistics in Industry 5.0. Subsequently, this study establishes the hierarchical relationship among these key enablers through the application of the Fuzzy Interpretative Structural Model (FISM). Following this, the study employs the Matrices Impacts Croises-Multiplication Appliance Classement (MICMAC) to compute the driving force and dependence of each enabler. The results underscore the significant roles of “Active support from the government” and “Human-centric manufacturing and logistics” as the most critical enablers for Industry 5.0. The strategic roadmap, informed by expert opinions, provides valuable insights for policymakers and implementers while explaining the methods and strategies needed to drive Industry 5.0 transformation in smart logistics. Furthermore, it determines the impact relationship between enablers and the optimal development order, facilitating their synergistic alignment. Ultimately, this strategic roadmap serves as an actionable guide for the logistics industry, steering it toward achieving smart logistics and fortifying competitiveness in the industry 5.0 era.

Exploring the Mediating Role of Strategic Synergy between Supply Chain Agility and Smart Logistics at Jordanian Pharmaceutical Manufacturing Companies

Exploring the Mediating Role of Strategic Synergy between Supply Chain Agility and Smart Logistics at Jordanian Pharmaceutical Manufacturing Companies

Tracing the technological trajectories of smart logistics domain based on citation analysis and topic modelling

ABSTRACT The emergence and development of intelligent technology are triggering major changes in the logistics industry, and relevant scientific and technological research on smart logistics (SL) is emerging endlessly. However, there is no research that systematically explores SL from the technological perspective. Therefore, this article selects 47,253 documents retrieved from the Derwent Innovation Index for systematic analysis and provides a comprehensive understanding of the SL domain. We combine main path analysis (MPA) and LDA topic modelling approaches to identify technological evolution trajectories. Through three main paths, the key technologies and technological evolution directions in the SL domain are revealed. Through topic identification and topic correlation calculation, global topic popularity trends and local topic evolution paths are identified. Finally, this study summarises our findings, contributions, and limitations. This is the first attempt to detect key technologies in the SL domain through MPA and topic analysis, thereby guiding relevant researchers and enterprises.

Preface

These proceedings contain the peer-reviewed full papers presented at the joint conference ICMASS (the 6th International Conference on Maritime Autonomous Surface Ships) and MTEC (International Maritime Port Technology and Development Conference), held October 29th – 30th, 2024, in Trondheim, Norway. MTEC and ICMASS bring together academia and industry from around the world showcasing cutting-edge research and development within maritime technology, autonomous ships and port operations. https://www.ntnu.edu/mtec-icmass2024/home Trondheim, Norway’s hub for technological innovation, has utilized its rich maritime heritage to position itself at the forefront of maritime innovation. With the world’s first test area for autonomous ships, its strong position within academia and research, Trondheim has gained a leading position in the field of maritime innovation through collaboration between maritime stakeholders. This year’s conference topics include: • Green shipping and ports • Smart and autonomous ship and port operations • Maritime safety • Maritime digitalization, connectivity and cybersecurity The theme of this year’s conference, featuring contributions covering topics such as AI & autonomy, cybersecurity, onboard control, remote & shore control, smart ships as part of smart logistics, green shipping, safety evaluations, collision avoidance, regulatory & legal frameworks, as well as discussions on liability, etc. The papers, published in these proceedings contain theoretical contributions as well as reports on practical implementations in field labs and industry, and the conference will also have oral only presentation. Totally there will be more than 90 presentations, where more than 60 papers are invited. A conference such as this can only succeed as a team effort, and, as such, we thank the International Program Committee and the Reviewers for their excellent work in reviewing the papers as well as their invaluable input and advice. On behalf of the organizing committee, List of MTEC/ICMASS-24 Organizing Committee, International Programme and Management Committee and International Reviewers are available in this Pdf.

Evaluation of the Smart Logistics Based on the SLDI Model: Evidence from China

Smart logistics (SL) reflects the digital transformation of the logistics industry, which is key for economic development. Most evaluations are based on the application of technology in SL, and few studies have evaluated SL from a comprehensive perspective. The paper builds the SL development index (SLDI) model from five dimensions based on the driving force, pressure, state, impact, and response (DPSIR) model and identifies the indicator weight by the entropy weight technique. The paper employs the ETDK method, a combined quantitative approach that incorporates entropy weight (E), the technique for order preference by similarity to an ideal solution (TOPSIS) (T), the Dagum Gini coefficient (D), and Kernel density estimation (K), to calculate the closeness degree, analyze spatial-temporal differentiation, and explain the distribution characteristics using data from China spanning 2013 to 2021. The findings show that (1) The SL evaluation is multidimensional and cannot be evaluated only based on technical indicators. A comprehensive evaluation indicator system is necessary. (2) A combined quantitative approach can measure SL development from multiple perspectives and get a clearer picture of the characteristics and regional differences of SL. (3) Influenced by economic development, infrastructure, regional clusters, location, talent, etc., the overall SL development is improving yearly, but SL development in different regions is unbalanced and has different distribution characteristics. The SLDI model developed in this paper will provide a more scientific and reasonable tool for comprehensively evaluating SL. The findings are helpful in proposing suggestions and optimization approaches for subsequent research on SL evaluation and development.

PDAC-SL: A PUF-enabled drone access control technique for smart logistics

The conventional logistics’ paradigm is being replaced with smarter ways of supply chain management to readily serve the customers with quick modes of delivery in affordable operational costs. The weak infrastructure in rural terrain and congested roads in urban cities act as a big impediment in the successful accomplishment of last mile delivery down the lane across the complete chain of logistics. The traditional logistics has been evolved and improved in many respects, the last mile delivery is still plagued by security and privacy risks in logistics. The use of drones for package deliveries may offer promising gains in terms of efficiency. Nonetheless, drones undergo security and privacy risks besides physical threats for being deployed in public places communicating on open channels. Thus, more efforts are needed to secure the communication of inducted drones in delivery assignments. We propose a novel PUF-enabled drone access control mechanism PDAC-SL for smart logistics. By the careful employment of symmetric crypto-primitives, the contributed protocol not only supports low end devices but stands resistant to physical drone and other known threats besides preserving anonymity and untraceability features. The RoR model-based formal security analysis and performance analysis demonstrate distinct security properties and applicability of the PDAC-SL.

Implementation of AI in Smart Logistics Based on Mobile Technologies

Implementation of AI in Smart Logistics Based on Mobile Technologies

Artificial intelligence usage, incentives measurements, and operational mechanisms for smart logistics: Basis for improved customer service framework

Artificial intelligence usage, incentives measurements, and operational mechanisms for smart logistics: Basis for improved customer service framework

Editorial on Special Issue “3D Reconstruction and Mobile Mapping in Urban Environments Using Remote Sensing”

Both 3D reconstruction and mobile mapping are critical in supporting various applications in urban environments, including but not limited to autonomous driving, smart logistics, pedestrian navigation, and virtual reality [...]

The implications of smart logistics policy on corporate performance: Evidence from listed companies in China

Since the emergence of smart logistics as a vital paradigm, it has garnered significant interest from independent firms and governments worldwide, including China. This study aims to examine the relationship between Smart Logistics Policy (SLP) and firm performance both theoretically and empirically. Utilizing data from A-share companies listed on the Shanghai and Shenzhen stock exchanges between 2012 and 2017, this study analyzes the relationship between SLP and firm performance using Propensity Score Matching (PSM) and Difference-in-Differences (DID). The results indicate that SLP significantly enhances a firm's financial performance. Additionally, a heterogeneity test on financial performance reveals that the impact of SLP varies based on ownership and industrial sector. Unexpectedly, SLP has a negative impact on corporate social responsibility (CSR) performance. The heterogeneity test on CSR performance shows that the SLP effect on CSR exhibits no significant difference based on ownership. Furthermore, the impact of SLP on CSR is significantly greater for manufacturing firms compared to non-manufacturing firms. Consequently, this study offers theoretical support and empirical evidence regarding the effects of SLP on firm performance.

Role and applications of advanced digital technologies in achieving sustainability in multimodal logistics operations: A systematic literature review

Integration of advanced digital technologies along with ensuring environmental sustainability in the logistics sector is becoming the need of the hour novel multimodal transportation concept. The rapid technological development in the era of industry 4.0 can not only create new opportunities in achieving highly efficient, intelligent, and smart logistics systems but also enable new business models for value addition, additionally, this novel system will also avoid environmental degradation and use of scarce natural resources that contribute to climate change. This paper summarizes the research trends of these technologies in multimodal logistics systems since 2005 through a systematic literature review. The results revealed a mixed picture of the situation, starting from emerging technologies like artificial intelligence, machine learning, and blockchain becoming key technological concepts for multimodal logistics systems to government policy hurdles and lack of impact breakthroughs in the industry. However, the results show that adaptation to these technologies improves the overall environmental, economic, and social sustainability of the system.

The Role of Logistics and Infrastructure in Promoting International Trade

This study aims to explore the role of logistics and infrastructure in promoting international trade. Through systematic analysis of relevant theories and practical impacts, the research finds that logistics and infrastructure play key roles in reducing transaction costs, enhancing trade speed and reliability, and promoting market connectivity and integration. Specifically, an efficient logistics system can optimize transportation, warehousing, distribution, and inventory management, thereby improving the overall efficiency of international trade. Meanwhile, modern transportation, information and communication, and energy infrastructure provide robust support for international trade, facilitating efficient global supply chain operations and economic growth. However, the logistics and infrastructure sectors also face challenges such as infrastructure aging, cross-border logistics barriers, environmental issues, and sustainability concerns. In the future, smart logistics, green logistics, public-private partnerships, and international cooperation will become important development trends. Based on these findings, this paper proposes that governments should formulate supportive policies and improve infrastructure investment mechanisms, while enterprises should enhance logistics optimization and technological innovation. By conducting an in-depth study of the role of logistics and infrastructure in international trade, this research aims to provide theoretical support and practical guidance for policymakers and enterprises, promoting sustainable development in international trade.

Research on Smart Logistics Development Based on Blockchain Technology

Blockchain technology has been incorporated into the field of next-generation information infrastructure in China and is experiencing rapid development. Utilizing blockchain and other emerging technologies to develop intelligent logistics is essential for logistics enterprises to reduce costs, enhance efficiency, and improve quality. By analyzing and summarizing the issues within the development of China’s logistics industry, this paper discusses its growth from three perspectives: policy, technology, and industry.

Optimization of logistics cargo tracking and transportation efficiency based on data science deep learning models

With the digital transformation of the logistics industry, smart logistics algorithms have become a core technology to improve efficiency and reduce costs. This paper reviews the development history of traditional logistics technology and discusses the key role of technologies such as the Internet of Things, big data analysis, artificial intelligence, and automation in logistics technology innovation. It focuses on the application of intelligent logistics algorithms in path optimization, intelligent scheduling, data mining and prediction, and intelligent warehousing. To solve the problem of inconsistency between training and testing objectives, this paper proposes DRL4Route, a deep reinforcement learning-based path optimization framework, and designs the DRL4Route-GAE model. These research results provide important support to further promote the intelligent development of the logistics industry.

Multi-domain fusion for cargo UAV fault diagnosis knowledge graph construction

The fault diagnosis of cargo UAVs (Unmanned Aerial Vehicles) is crucial to ensure the safety of logistics distribution. In the context of smart logistics, the new trend of utilizing knowledge graph (KG) for fault diagnosis is gradually emerging, bringing new opportunities to improve the efficiency and accuracy of fault diagnosis in the era of Industry 4.0. The operating environment of cargo UAVs is complex, and their faults are typically closely related to it. However, the available data only considers faults and maintenance data, making it difficult to diagnose faults accurately. Moreover, the existing KG suffers from the problem of confusing entity boundaries during the extraction process, which leads to lower extraction efficiency. Therefore, a fault diagnosis knowledge graph (FDKG) for cargo UAVs constructed based on multi-domain fusion and incorporating an attention mechanism is proposed. Firstly, the multi-domain ontology modeling is realized based on the multi-domain fault diagnosis concept analysis expression model and multi-dimensional similarity calculation method for cargo UAVs. Secondly, a multi-head attention mechanism is added to the BERT-BILSTM-CRF network model for entity extraction, relationship extraction is performed through ERNIE, and the extracted triples are stored in the Neo4j graph database. Finally, the DJI cargo UAV failure is taken as an example for validation, and the results show that the new model based on multi-domain fusion data is better than the traditional model, and the precision rate, recall rate, and F1 value can reach 87.52%, 90.47%, and 88.97%, respectively.

From RAG/RAT to SAGE for Social Transportation: A CoT and New Perspective on Smart Logistics and Mobility

From RAG/RAT to SAGE for Social Transportation: A CoT and New Perspective on Smart Logistics and Mobility