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This paper addresses the question whether energy consumption variables and the disaggregation of output matter in the context of efficiency analysis of container terminals. While it is obvious that the energy consumption of refrigerated cargo is higher than the energy consumption of non-refrigerated cargo, this work investigates whether those differences show in an overall efficiency analysis of terminals. This would point to a potentially important input for efficiency measures, to be considered in future productivity and efficiency analysis of terminals. Starting with a discussion on theoretical concepts and variable selection for measuring the energy dimension of terminal efficiency, this is the first paper that applies data envelopment analysis (DEA) comparing results with and without energy consumption, as well as differentiating productive outputs (dry and reefer container handling). The results reveal how the output disaggregation leads to substantially different efficiency scores and are a first step to show the relevance of output disaggregation and the inclusion of the energy variables as inputs in container terminal efficiency studies. [ABSTRACT FROM AUTHOR]

Operational efficiency is crucial in the container terminal industry to reduce costs, increase throughput, enhance customer satisfaction, optimize the supply chain, improve safety, minimize environmental impact, and ensure adaptability and resilience in a dynamic and competitive market. The article aims to estimate operational efficiency for CTOs by the Slacks-Based Measures (SBM) model when considering CO2 emissions and work accidents as undesirable outputs. In doing so, this paper adopted the cluster analysis to select homogeneous CTOs acting as Decision-making Units (DMUs). CTOs in the Cai Mep-Thi Vai port (the CMTV case) were then empirically studied to verify the validity of the suggested model. The results could have real-world applications for CTOs looking for managerial actions to boost operational efficiency and maintain high-quality growth. Additionally, the research model may provide an analytical reference for relevant port management applications. In particular, this study offers CTOs a scientific framework for evaluating the operational efficiency of CTOs located in a port. [ABSTRACT FROM AUTHOR]

This document is an editorial from the journal Maritime Policy & Management, discussing the issue of air emissions from the shipping industry and the need for green port technologies. The article highlights the significant amount of marine fuel consumed by shipping activities and the resulting emissions of sulfur dioxide, nitrogen oxide, carbon dioxide, and particulate matter. It emphasizes that most of these emissions occur within 400 km of the coastline, causing severe environmental problems. The editorial also introduces a special issue on "Green Port and Maritime Shipping," which includes research papers on topics such as internal truck renewal, berth and yard allocation, stocks allocation, environmental management systems, marine greenhouse gas emission control, container terminal competitiveness assessment, multi-criteria decision support frameworks, and maritime transportation research capability analysis. The article concludes by emphasizing the importance of improving the environmental performance of ports for their competitiveness and the need for collaborative actions to control marine greenhouse gas emissions. [Extracted from the article]

Deep neural network is an important computer operating system in China. It has made great breakthroughs in target recognition, image classification and other fields. It plays a key role in multi-system integration and intelligent manufacturing industry, such as training and testing. The purpose of this paper is to study the multi-system fusion of deep neural network and its application in intelligent manufacturing industry. By setting up experiments, the multi-system fusion of neural network is carried out, combining with big data and artificial intelligence to verify the efficient operation of neural network in multi-system fusion. Using the methods of mathematical analysis and big data fitting, the collected data are classified, the experimental data are collected and then analyzed. In this paper, the reliability of this method is verified by research; the application of multi-system fusion based on deep neural network in intelligent manufacturing industry can effectively integrate all systems, improve the comprehensive working efficiency of each system by about 20% and improve the multi-system fusion of deep neural network and its application in intelligent manufacturing industry by about 15%. Thus, as the terminal of the system, the deep neural network plays the leading role of multiple systems. It can effectively integrate the various systems and improve the comprehensive work efficiency of each system, which has guiding significance for the development of industry. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to explore how a start-up entering maritime logistics networks (MLNs) in the container shipping industry integrates resources underlying value cocreation patterns in these networks. Design/methodology/approach: The paper is based on a single case study of a technological start-up, providing tracking, tracing and other information services to MLN members using internet-based software. An interorganizational theory perspective informs the case study to unveil the resource integration for value cocreation in the network. Findings: The start-up holds multiple resource interaction roles and the start-up's involvement enables the creation of new knowledge resources, which facilitate new revenue streams and manage resource dependencies. Hence, the findings indicate that the start-up changes value cocreation patterns in the network by reconfiguring and integrating existing resources so that the service is customized for various customers, including shippers and freight forwarders. Practical implications: The results provide insights about how technological start-ups can unlock resources within MLNs. Originality/value: The study extends previous studies on resource roles in business networks and shows how start-ups can perform multiple roles simultaneously within these networks. In addition, the study contributes to the literature by studying information and knowledge as resources configured in different ways in a unique network setting. [ABSTRACT FROM AUTHOR]

This research is focused on the analysis of a container terminal common in industrial zones in urban areas, called the logistic services container terminal (LSCT), defined as a small to medium size inland terminal with no intermodal facilities. The main function of an LSCT is to provide services to a hinterland market. The material handling equipment used is limited to reach stacker cranes and front loaders, and ground transportation in and out is performed using trucks exclusively. Moreover, there are many operations related to servicing customers in special service areas within the yard. In this research, we explicitly recognize the limitations and features associated with the operations within LSCT yards, which means that the problems and solutions must be conceived and addressed in a very unique way, considering that services have to be coordinated with the strategies proposed for managing the movement of containers in and out. This paper characterizes the different aspects present in the treatment of an LSCT and proposes an adapted version of three known greedy decision rules for determining the location for an arriving container. We evaluate the performances of these rules using a discrete-event simulator: the min-max rule outperforms the other tested rules. These rules are also extended to consider the cost of moving relocating containers. The results show that using cost-aware rules while increasing the expected number of relocations reduces the total expected cost significantly. [ABSTRACT FROM AUTHOR]

Production control in the manufacturing industry involves complex circumstances and high demand for timeliness. Unlike traditional production control methods, the approach that integrates machine learning and industrial big data can enable manufacturing industries to dynamically adapt to the changing environment and respond in a timely manner to market changes due to production optimisation and improve economic benefits. In order to explore the relationship between production system optimisation and lean strategic planning based on machine learning and big data, the paper conducts an exploratory case analysis based on Suzhou GCL Photovoltaic Technology, a successful company in the photovoltaic industry in China. We sort and investigate the first-hand interview data and second-hand news and video data, and then use the qualitative research method. Based on the analysis and observation, we find that machine learning has a positive impact on quality management. Data, information, knowledge, intelligence collectively impact the performance of intelligence production systems. Our research provides valuable insights for practitioners to effectively accelerate the transformation to intelligent manufacturing. [ABSTRACT FROM AUTHOR]

Container-based virtualization is a popular technique, e.g., to realize microservice architectures. Recently, containers became popular in Industry 4.0 / IIoT systems, which typically consist of hundreds of (edge) devices and machines. In such setups, efficient management of containers is essential as offered by container orchestrators like Kubernetes. However, currently no specific overviews discussing orchestrator capabilities for Industry 4.0 are available. In this paper, we analyze nine open source container orchestrators for their application in Industry 4.0 or IIoT settings as a basis for future research and development. We contribute a systematic literature review to identify 23 basic orchestration requirements. We complement this by insights from an intensive requirements collection in a research project on intelligent industrial production, as well as selected features from a published generic orchestrator analysis. From these 66 requirements, we derive a requirements/feature taxonomy, which we use to analyze the nine open source orchestrators including Kubernetes. We show that there is, e.g., still a lack of support regarding edge devices, IIoT protocols, security mechanisms, and specialized resources for artificial intelligence. [ABSTRACT FROM AUTHOR]

Cyber-manufacturing Systems (CMS) have been growing in popularity, transitioning from conventional manufacturing to an innovative paradigm that emphasizes innovation, automation, better customer service, and intelligent systems. A new manufacturing model can improve efficiency and productivity, and provide better customer service and response times. In addition, it may revolutionize the way products are produced, from design to completion. Therefore, it is likely that this newmanufacturing model will become increasingly popular. By building new technologies on top of existing CMS, these systems will ensure that data exchange and integration between decentralized systems are reliable and secure. Recently published case studies from industry and the literature support this claim; some challenges remain to be overcome. In general, the use of CMS can revolutionize the manufacturing industry. This study comprehensively analyzes these systems and their potential applications and implications. An overview of the field is then given and various aspects of CMS are also explored with more details. A taxonomy of the most common and current approaches to CMS is presented, including networked cyber-manufacturing systems, distributed cyber-manufacturing systems, cloud-based cyber-manufacturing systems, and cyber-physical systems (CPS). Furthermore, our survey identifies several popular open-source software and datasets and discusses how these resources can reduce barriers to CMS research. In addition, we identify several important issues and research opportunities associated with CMS, including better integration between hardware and software, improved security and privacy protocols, communication protocols, and improved data management systems. In summary, this paper presents a comprehensive overview of current technology and valuable insights are provided for the potential impact of CMS on society and industry. [ABSTRACT FROM AUTHOR]

Automation in the construction industry has become more appealing in recent years. Although the industry fosters material mixing and structural application, automating quality control is not investigated broadly. The industry relies on manual inspection, leading to inaccuracy and lower productivity. This research focuses on the quality check of bolted steel members using automating ESP32 camera to detect missing bolts. Earlier studies focused on improving the quality of tightening the bolts. However, the major problem of missing bolts has not been extensively addressed. Inadequate bolting of steel members causes a considerable reduction in mechanical strength, and it may cause a structure to fail. Hence, this paper aims to detect missing bolts in assembling steel structures. The study was conducted by developing a system that utilizes an ESP32 camera module to capture the steel members in real-time. Captured video is processed in Visual Studio (C++ language), another approach carried out in the study is using a faster region-based convolutional neural network (Faster R-CNN) where it extracts the area of interest, the bolts, and holes in the steel members with the assistance of an image dataset and training. The trained model can be used to detect bolts and holes. The results showed that the developed system is reliable and can alter the user to any missing bolts, having TensorFlow object detection with the Faster R-CNN algorithm successfully provided desired results with 95% precision. This technique increases the efficiency of quality monitoring. Consequently, the steel manufacturing industry can rely on smart cameras to monitor the quality control of steel frames, leading to productive output. This also saves the workers time from performing the tedious task of inspecting every steel member and assists in maintaining the quality of the assembled steel structures. [ABSTRACT FROM AUTHOR]

The business world is becoming increasingly complex, disrupted, and uncertain. As Industry 4.0 (I4.0) takes shape, to endure this change and focus on growth, industries must learn to embrace change and move quickly; this is particularly so for the automotive industry, which is a major sector of any economy. Agility is needed to embrace this change and promote sustainability across every industry. To face these contingencies, it is essential to identify and understand the strategies that can aid industries in sustaining real‐time scenarios. In this paper, we aim to assess the agility indicators that bring resilience to the inclusion of I4.0 and sustainability in the automotive sector. The unexpected changes in the environment related to sustainability and technological disruptions of I4.0 require the identification of sustainable agile mitigation strategies to manage such situations. The fuzzy Delphi methodology assesses agility indicators based on a questionnaire for prioritization. Further, the fuzzy technique for order performance by similarity to ideal solution (TOPSIS) is utilized to prioritize these agility indicators with the agility strategies that manufacturing industries can deploy to enhance the sustainability of their operations. The fuzzy extension to the methodologies helps in incorporating vagueness and ambiguity in the decision‐making process. A fuzzy approach to prioritizing agile strategies as the industries are changing is helpful. The decision makers have only a few clear ideas about how best to integrate them. Among the agile strategies, "resilience," "technological capabilities," and "customer‐centric innovation" are the top strategies. By executing the strategies suggested in the study and understanding the agility indicators, practitioners can ensure resilience in the work systems and minimize the impact of the disruptions caused by the industrial revolution. Thus, this research has been underpinned by the organizational change theory and discusses all mitigation strategies concerning the rapid changes organizations are facing with the fourth industrial revolution. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to make a systematic study on the factors that hinder the development of China's intelligent automobile manufacturing industry; based on comprehensive understanding of these obstacles and by optimization means, ultimately, the healthy and sustainable development of intelligent automobile manufacturing industry in China can be promoted. Design/methodology/approach: Based on a questionnaire survey of intelligent automobile manufacturing listed companies in China, first, fuzzy semantic scale was adopted to collect respondents' choices, the fuzzy score function is used to calculate the fuzzy score value and these data are used as the basis for subsequent model analysis. Then, structural equation modeling (SEM) was adopted to analyze the causal relationship between influencing factors to explore the main hinder factors. Findings: It is found that, in the short term, the backwardness of technological industrialization is the main reason leading to low permeability of intelligent automobile; in the medium term, the imperfect industrial R&D ability and the insufficiency of infrastructure are major causes for high manufacturing cost and low competitiveness of intelligent automobile manufacturing industry; in the long term, the lack of national policy and industrial strategic planning is the main factors affect intelligent automobile manufacturing cost and the industry competitiveness. Practical implications: The research conclusion has important policy implications for promoting intelligent automobile manufacturing sustainable development. In recent years, China's intelligent automobile manufacturing industry has gradually stepped out of breeding period; therefore, the role of government should be gradually transformed from participants to managers and regulators. Considering the fact that intelligent automobile cost is very high, and still higher than the cost of fuel vehicle, government should focus on the issues such as improving R&D capabilities, infrastructure construction, policy framework system, legal system and technological industrialization. Specifically, in short-term planning, improving technological industrialization level is the key to development; in medium-term planning, policymakers should focus on the improvement of R&D capabilities and infrastructure; considering the long-term development, establishing appropriate national policies and dealing with the adverse impact of imperfect strategic planning are the most sensible choice. Originality/value: This paper analyzes the factors that hinder the development of China's intelligent automobile manufacturing industry for the first time, and provides the basic logic of integration factors at different levels with the development of intelligent automobile to reveal the uniqueness and facts of China's economic development. [ABSTRACT FROM AUTHOR]

Purpose: Support structures are often needed in additive manufacturing (AM) to print overhangs. However, they are the extra materials that must be removed afterwards. When the supports have many contacts to the model or are even enclosed inside some concavities, removing them is very challenging and has a risk of damaging the part. Therefore, the purpose of this paper is to develop a new type of tree-support, named Escaping Tree-Support (ET-Sup), which tries to build all the supports onto the build plate to minimize the number of contact points. Design/methodology/approach: The methodology is to first classify the support points into three categories: clear, obstructed and enclosed. A clear point has nothing between it and the build plate; an obstructed point is not clear, but there exists a path for it to reach the build plate; and an enclosed point has no way to reach the build plate. With this classification, the path for the obstructed points to come clear can be found through linking them to the clear points. All the operations are performed efficiently with the help of a ray representation. Findings: The method is tested on different overhang features, including a lattice ball and a mushroom shape with a concave cap. All the supports generated for the examples can find their way to the build plate, which looks like they are escaping from the model. The computation time is around one second for these cases. Originality/value: This is the first time truly realizing this "escaping" property in the generation of tree-like support structures. With this ET-Sup, it is expected that the AM industries can reduce the manufacturing lead time and save much labor work in post-processing. [ABSTRACT FROM AUTHOR]

Purpose: This paper explores the implications for higher education of the rapid development in technology used by the manufacturing sector. Higher education programmes change or new courses are introduced in attempts to match labour market demands. However, the pace of change in the manufacturing industry challenges the authors to reconceive how programmes and modules can and should be designed and delivered. Design/methodology/approach: This study is based on interviews with 26 senior management representatives from manufacturing companies in Ireland. The 26 senior managers and their companies represent the wide diversity of Ireland's manufacturing sector. All the interviews were face to face, complimented by a short questionnaire. Follow-up interviews focussed on the emergent findings were carried out to aid the writing of recommendations for the best practice in programme design and delivery. Findings: What emerges from this study is that the manufacturing industry needs skills at three distinct levels. The authors define and classify the skill requirements at entry, competent and expert level. The authors place an emphasis on upskilling as an aid to movement between the three levels. In addition, and significantly, the desired time frame for delivery of these skills and/or upskilling is very short. Originality/value: Accelerated reskilling programmes with faster, shorter bursts of work-based learning (WBL) and experiential training are required. With a growing demand for those at competent and expert level, it is necessary to promote WBL to facilitate the upskilling of those employed in manufacturing roles, particularly in small and medium-sized enterprises (SMEs). [ABSTRACT FROM AUTHOR]

Different transportation modes interrelate in intermodal transportation. Previous researches on intermodal transportation mainly investigate policy, network design, cargo routing or drayage operations. In order to explore the coordination between two connected transportation modes, this paper considers the connection between inland transportation and maritime container transportation. By making use of different container arrival patterns resulted from inland transportation, this paper focuses on liner ship scheduling with sailing speed optimization, as well as considering the container storage cost at each port. The studied problem is formulated as a mixed-integer nonlinear programming model, which is efficiently solved by using an outer-approximation method. Numerical results show that the optimal ship schedule varies with different container arrival patterns, and this influence is also related to the container storage cost and the bunker price. [ABSTRACT FROM AUTHOR]

The paper describes the glass manufacturing process, the process areas and their energy intensity. The implementation of an energy management system, its operation and participation in the decision-making chain as well as benefits from implementation are also described. The use of regression as a numerical technique for determining energy consumption is presented with reference to the historical experience of the glassworks and its developed trends on the example of gas consumption in the melting process in the glass furnace. The paper compared the deviation of actual energy consumption in the glass melting process to that calculated from linear regression variables for data before and after the implementation of the energy management system. The study confirmed the sensibility of implementing the described managing system. Constant observation and response to factors affecting the running process allows for its stabilization and optimization. [ABSTRACT FROM AUTHOR]

In recent years, the stability of supply chains has been undermined due to many disruptions. Although it is normal for the disruptions in supply chains to occur periodically, they have great impact on the rise of the costs and they create strong imbalances in business. For years, most world trade has been performed by maritime transport due its cost-effectiveness. The COVID-19 pandemic has disrupted the global supply chain like nothing before, and the Russian invasion of Ukraine has only deepened the crisis that is affecting the global supply chain. The focus of this paper has been placed on volatile freight rates in the maritime container industry due to the COVID-19 pandemic and the Russian invasion of Ukraine and the consequences of these crises on the changes of the prices of consumer goods in the European Union. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to explore and analyse the risks in container shipping operations from a logistics perspective. In the paper, risks associated with the three flows in logistics − information, physical, and payment flow are identified and analysed. Design/methodology/approach - The use of case study method was first explained and justified. Second, risk identification was started with supporting references, several interviews were then conducted to identify and validate the potential risks in container shipping operations. A questionnaire was deployed to collect related data; and the impacts of the risks were then assessed and ranked using the method of risk mapping. Findings - The paper has identified a total of 35 risk factors and classified them into different categories. The paper has also revealed that the risks associated with physical flows have more serious risk impacts than the other types of risks; however, one of the risk factors associated with information flow (shippers hiding cargo information) is the most significant one among all the factors. Originality/value - Although many studies have been conducted on container shipping operational risks, no studies so far have approached this issue from a perspective that inclusively examines all the possible risks and comprehensively evaluates the relative importance of each of them. This study has identified the risks in container shipping operations, and analysed and ranked the level of these risks. The research further "refines" the findings of some previous studies by placing the risk factors addressed therein in a full "risk picture" which was developed systematically. [ABSTRACT FROM AUTHOR]

After the collapse of Hanjin Shipping in 2016, Korea faced the task of reconstructing its container shipping industry by enhancing the competitiveness of its shipping companies in a rapidly evolving market environment. Responding to this need for policy design, this study first attempts to understand the industry based on the shipping ecosystem, which comprises the following four areas: shipping finance, collection of cargo, acquisition of ships, and partnership among carriers. Second, it lists the structural problems, along with the remedial policy alternatives, that were identified after conducting in-depth interviews with industry experts, which included mid-level managers. Third, it conducts an importance-performance analysis to classify problems according to their importance and performance, followed by an analytic hierarchy process analysis to define the priorities of policy alternatives. Finally, drawing on the empirical results, the paper concludes with suggestions on an integrated policy package for the container shipping industry. [ABSTRACT FROM AUTHOR]

This paper presents the idea of implementing the virtual Community of Practice for Product Innovation processes towards the establishment of intelligent enterprise. Since the fourth industrial revolution is passing through the developing phase, implementation of Cyber-Physical Production Systems require more realistic approach. Knowledge Management and Engineering plays an important role in manufacturing industries facing global competition. One of the most promising areas where Knowledge Management is studied and applied is product innovation. This paper explains the efficient and systematic methodology for Knowledge Management through Community of Practice for product innovation. Manufacturing industries can connect with similar industries at global level, sharing and using technical and experiential knowledge in decision making thus converting them into intelligent enterprises. [ABSTRACT FROM AUTHOR]

Due to imbalances in the global transport of containerised goods, liner shipping companies go to great lengths to match the regional supply and demand for empty containers by transporting equipment from surplus to deficit regions. Making accurate forecasts of regional empty container availability could support liner companies and other involved actors by making better relocation decisions, thus avoiding unnecessary transport costs of empty equipment. Previously proposed container availability prediction models are limited to the application in individual regions and typically characterized by a high degree of temporal aggregation. Against this background, this paper introduces two novel approaches based on machine learning and probabilistic techniques to predict the future weekly availability of empty containers for more than 280 locations worldwide. The machine learning and probabilistic prediction models are built by analysing a unique data set of more than 100 million events from past container journeys. These events represent different stages during the transport process of a container. Both models use a two-step forecast logic. First, the expected future location of a container is predicted. Second, the expected timestamp for arriving at that location is estimated. The machine learning model uses artificial neural networks and mixture density networks to forecast the movements of containers. The models are quantitatively assessed and compared to the actual availability of containers and two more conventional forecasting approaches. The results indicate that the probabilistic prediction approach can keep up with conventional approaches while the neural network approach significantly outperforms the other approaches concerning every evaluation metric. [ABSTRACT FROM AUTHOR]

Statistical techniques have a beneficial effect on measuring process variability, analyzing the variability concerning product requirements, and eliminating the variability in product manufacturing. Process capability indices (PCIs) are not only easy to understand but also able to be directly employed by the manufacturing industry. The process yield index offers accurate measurement of the process yield, and it is a function of two unilateral six sigma quality indices. This paper initiates to develop the confidence intervals of the process yield index by using joint confidence regions of two unilateral six sigma quality indices for all quality characteristics of a product. Then integrate these joint confidence regions to find the confidence intervals of the product yield index. All manufacturing industries can use these confidence intervals to make statistical inferences to assess whether the process capability of the product and all quality characteristics has reached the required level, and to grasp the opportunities for improvement. An illustrated example on driver integrated circuit of micro hard disk is provided. [ABSTRACT FROM AUTHOR]

Discontinuities and sharp curves commonly exist in the berth layout of container terminals. To cope with these layout characteristics, traditional studies proposed discrete or hybrid modeling approaches. However, the drawback of these approaches is the low berth space utilization. In reality, berth space is a very scarce resource and the development of which usually involves huge investments. Accordingly, a high space utilization approach is usually indispensable to a container terminal. In the literature, continuous berth layout modeling approach is sophisticated to be good in space utilization. However, its application is limited to continuous layouts, but not for discontinuities. In other words, it is not applicable to many container terminals in reality. To fill this gap, this paper studies an integrated berth allocation and yard planning problem with discontinuities berth layout. A novel multi-continuous berth layout approach and a mixed integer linear programming are proposed to deal with this new problem. In addition, a Guided Neighborhood Search (GNS) is proposed to enhance the optimization efficiency. Experimental results show that the GNS significantly reduce computational time enabling the proposed algorithm to be applied in reality. In addition, the proposed approach increases the berth space utilization, and consequently reducing the waiting time of incoming vessels. Furthermore, by simultaneously integrating the berth position and yard storage position, the total travelling distance of containers is being minimized. As a result, the overall performance of the terminal is improved. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to use a theoretical framework (i.e. resource-based view) to investigate causal relationships between the supply chain integration, market orientation, information technology (IT) application and firm performance of container shipping firms in Taiwan. Design/methodology/approach - The data are collected from 124 container shipping firms in Taiwan. The methodologies used in the paper are exploratory factor analysis, confirmatory factor analysis and structural equation modeling. Findings - The findings indicated that IT application and market orientation positively influence supply chain integration. It revealed that IT-based and market-oriented firms more easily integrate market information related to partners, departments and customers. Further, supply chain integration and market orientation have a positive effect on firm performance. Research limitations/implications - Such a result indicated a market-oriented firm quickly responds to market information and competitors' strategies; and thus, it would make effort to offer satisfactory customer services in dynamically fluctuating markets, and obtain better firm performance. Also, the integration provides higher operation efficiency and obtains an enhanced performance improvement. Practical implications - The results also indicated that firms are able to develop their market-oriented strategies through electronic information transmission and exchange platform. Based on the study's findings, managerial strategies are proposed to improve firm performance. Originality/value - This paper clarifies the concept of supply chain integration, market orientation and IT application in the context of container shipping, and investigates the inter-relationship between supply chain integration, market orientation, IT application and firm performance and develop a conceptual model in the context of container shipping. [ABSTRACT FROM AUTHOR]

One of the significant trends in smart manufacturing is the idea of industrial digitalization, which is enabled through the use of new information technologies, such as the Internet of Things, big data, cloud computing, and artificial intelligence. However, manufacturing industries can only be achieved by combining the physical manufacturing world and digital world, to realize a series of smart manufacturing activities, such as active perception, real-time interaction, automatic processing, intelligent control, and real-time optimization, etc. In this paper, a digital twin-driven approach combines with agent-based decision-making for real-time optimization of motion planning in robotic cellular is proposed, with optimizing the physical and virtual layer at the manufacturing facility. Accordingly, an architecture of the digital twin-driven facility is design, and its operational mechanisms and implementation methods are explained in detail. Moreover, qualitative analysis and a quantitative comparison based on a real robotic cell are provided. Several key findings and observations are generated relating to managerial implications, which are valuable for various users to make manufacturing decisions under the digital twin-driven environment. [ABSTRACT FROM AUTHOR]

At present sustainable development, assessment of sustainable manufacturing practices, and prioritisation of barriers, drivers, and indicators have become complex due to the involvement of existing benchmarks like social, economical, technical, and environmental. Literature review available on sustainable manufacturing practices assessment which considers all three dimensions is relatively limited. Recently, in sustainable manufacturing decision making, approaches to evaluate sustainable manufacturing practices have used both quantitative and qualitative data. This study aims to present a systematic review of multi-criteria decision making (MCDM) applications in sustainable manufacturing. In the present study papers available in the Scopus database were reviewed on the applications of different MCDM techniques in the sustainable manufacturing area. The study highlights how the manufacturing industries can benefit from MCDM techniques in decision making. This review article develops insights into various multi-criteria decision-making techniques progress made by considering the sustainable manufacturing applications over MCDM methods. An extensive review in the sphere of sustainable manufacturing has been performed by considering the Scopus database and utilising MCDM techniques. It is found that most of the studies available in the sustainable manufacturing (SM) area are based on fuzzy-based single model approaches. [ABSTRACT FROM AUTHOR]

The ITER WAVS (visible and infrared Wide Angle Viewing System) provides measurements of surface temperature for the plasma facing components by infrared thermography. One of its most important roles of WAVS is to protect the plasma facing components from damage. It also takes images of the plasma visible spectral range emission. The WAVS diagnostic consists of 15 views distributed in four equatorial ports (3, 9, 12 and 17), and it will contribute to Machine protection, Basic control and Physics analysis. The final design of the WAVS system in the equatorial port 12 (EP12) includes three lines of sight (LoS) that have to installed for ITER first plasma. This paper is focussed on the final design for the opto-mechanical ex-vessel components in equatorial port 12 (EP12). The most important function of the ex-vessel optics is to relay the image produced by the Port Plug optics at the vacuum window, up to the detectors placed at the backend of the optical chain in the Port Cell, while keeping the required performance. The image relays through the Interspace, Bioshield and Port Cell covers around 10 m in length before reaching the cameras. The ex-vessel optics is arranged in several optical modules, assembled on the EP12 support structures, i.e. Interspace Support Structure (ISS) and Port Cell Support Structure (PCSS). A detailed description of the opto-mechanical design that supports the optical modules, including the alignment capabilities, will be presented in the paper. Moreover, the assembly and alignment strategies planned for the ex-vessel subsystems, taking into account all constraints imposed on the site, are also described in the paper. [ABSTRACT FROM AUTHOR]

This paper explores the cultivation paths of innovation ecosystems in the digital age by constructing a theoretical framework consisting of innovators, elements of innovation, platforms and digital governance. Four cities in China, Shenzhen, Hangzhou, Xuzhou and Weifang, were selected for in-depth case studies. Findings revealed that: (1) regions with 'head enterprises' and a strong industrial base achieve a competitive advantage via the synergy of digital industrialisation and industrial digitalisation; (2) digital technology pioneer regions can adopt digital industrialisation; (3) regions with a strong industrial base and traditional manufacturing industries can prioritise industrial digitalisation and (4) manufacturing regions with a large number of small and mid-size enterprises (SMEs) who can combine industrial digitalisation and digital value. This study provides theoretical and practical value for the cultivation of regional innovation ecosystems. [ABSTRACT FROM AUTHOR]

Manufacturing industries are constantly identifying ways to automate machinery and processes to reduce waste and increase profits. Machines that were previously handled manually in non-standardized manners can now be automated. Converting non-digital records to digital formats is called digitization. Data that are analyzed or entered manually are subject to human error. Digitization can remove human error, when dealing with data, via automatic extraction and data conversion. This paper presents methodology to identify automation opportunities and eliminate manual processes via digitized data analyses. The method uses a hybrid combination of Lean Six Sigma (LSS), CRISP-DM framework, and "pre-automation" sequence, which address the gaps in each individual methodology and enable the identification and analysis of processes for optimization, in terms of automation. The results from the use case validates the novel methodology, reducing the implant manufacturing process cycle time by 3.76%, with a 4.48% increase in product output per day, as a result of identification and removal of manual steps based on capability studies. This work can guide manufacturing industries in automating manual production processes using data digitization. [ABSTRACT FROM AUTHOR]

The paper aims to emphasize the contribution that manufacturing industry can have to meet the Circular Economy (CE) scope related to the use of resources. First, we presented the CE concept and the framework in Europe, the monitoring framework and also, we noted some aspects of manufacturing industry related to CE. Then, we performed an analysis of the secondary raw material data, which is one of the representative indicators of CE, in order to see the state of circular economy related to the resources in European Union Member States. The results showed that the resource circularity is lowest in Europe, the states which can be remarked are Germany, Netherlands, and Belgium. Highlighting these aspects, some conclusions were formulated, the most evident is that the manufacturing industry has a very important role on the CE transition, consisting in the resources fact implicated. The manufacturing industry can choose to use secondary raw materials instead of virgin raw materials, can improve resource efficiency through the technologies used in production processes and can address the circularity of a product, being an important CE actor. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to explore, through a synthesis of the literature, the causes, benefits, constraints and ways for reducing the number of empty trips made by container trucks. Reduced empty truck trips contribute to sustainable transportation practices in the port territory.Design/methodology/approach To contribute in the current body of the literature, through a comprehensive synthesis of the studies, this study examines many perspectives surrounding the empty truck trips at container terminals. Hence different, but relevant operational aspects of empty truck trips are explored. This study adopts a content analysis as the research methodology.Findings Different perspectives, which are drawn from the reviewed literature, identify a research gap in published research in the area of transport collaboration (of supply chain collaboration) and coordination problems in hinterland transport chains (of maritime logistics), and the literature relating to backhauling (of vehicle routing problems with backhauls). To cover that research gap in the literature, this study attempts to highlight and synthesize the important empty-trips studies currently available into a coherent and understandable form.Practical implications As an integral part of encouraging collaboration in the container transportation industry, this research may be effective in persuading port authorities to evaluate and to help transport managers to reply to specific enquiries of truck-sharing arrangements.Social implications The utilization of available empty space of container trucks is a feasible option of increasing transport capacity and achieving sustainable transportation benefits.Originality/value This paper provides a contemporary lens to view the relationship between empty trips and their applications in the carrier industry, in order to resolve the perceived issues of non-sustainable transportation and their implications for the society. [ABSTRACT FROM AUTHOR]

This paper investigates an initial model for Zero Defect Manufacturing (ZDM) using a cost function where the operation and condition of a production process are reflected, and the quality of the output/product and the production process (as well as safety aspects) can be considered. The outset of the study is based on empirical data collected from five manufacturing companies, and proposes an initial model for ZDM with an Industry 4.0 perspective. The initial ZDM model has a generic setup for a real-life system and its replication as a digital twin using system models based on a representation of a generic production process with its connected control system, and potential interconnections between unit processes. It is based on concepts from system theory of dynamic systems and principles from condition monitoring and fault detection. In that way the model is deemed as highly generalizable for manufacturing and process industry companies as well as for some critical infrastructures with production and distribution systems. The proposed model with its cost function setup is analyzed and discussed in the context of ZDM. It is concluded that production processes in the manufacturing and process industry can be made more intelligent and interoperable using this approach. Improved sustainability, competitiveness, efficiency and profitability of companies are foreseen welcomed secondary effects. Finally, the proposed ZDM model further develops the ZDM by adding to it a systematic approach based on a solid mathematical foundation. [ABSTRACT FROM AUTHOR]

In the competitive environment of liner shipping, the ability to nimbly adjust shipping capacity to demand could mean the difference between a thriving shipping operation and one that will most likely fail. How quickly and effectively carriers adjust their capacity may depend on how their expectations regarding trade volumes and freight rates are formed. We find that if adaptive expectations prevail in the decision process, capacity deployment may suffer some degree of inertia but, compared to expectations that are formed rationally, capacity would be be relatively stable. On the other hand, if carrier expectations are rational, capacity deployment might be more likely to align closer and faster with demand. We seek to empirically test whether carriers' expectations of demand, aiming at deploying the right amount of capacity, can be characterized as adaptive or rational. We find that a) in most cases, adaptive expectations is the paradigm in container shipping; b) the way expectations are formed and the market structure of the liner shipping industry are two things not totally unrelated; and c) rational expectations point to more competitive markets (such as that of the Pacific), while adaptive expectations indicate higher concentration and thus imperfect competition (as is the case in the North Atlantic). Our findings have important regulatory implications in the sense that, if one accepts, as we do, that adaptive expectations are consistent with concentrated industries, while rational expectations suggest more competition, then our paper suggests that the 2008 abolition of the liner conference system from European trades has failed to improve the level of competition in the Europe – US liner shipping markets. [ABSTRACT FROM AUTHOR]

Purpose: The purposes of this study are first, to analyze why the process capability index (Cpk) for drop impact resistance (DIR) does not meet the specification or less than 1.33, and second, to find out what improvements should be made to make it meet the specification. Methodology/Approach: The methodology used was Statistical Process Control (SPC) through the PDCA cycle, supporting with Cause and Effect Diagram (CED), Nominal Group Technique (NGT) and "why, what, where, when and how (5W1H)" method. Findings: With the above methods, the result of the study was given a positive impact on the company. The average of DIR was increased from 20.40 cm to 25.76 cm, increased by 26.27% and the standard deviation was reduced from 1.80 to 1.48, and then the Cpk index was increased from 0.48 to 1.79 it means the process is in control and capable. Research Limitation/implication: This research was limited only on the twopiece can aluminum cans manufacturing process, no for three-piece cans manufacturing. SPC through PDCA cycle is an interesting method for continuous improvement of process capability in the cans manufacturing industry. Originality/Value of paper: This study highlights the area of future research SPC through the PDCA cycle to analyze and optimize process capability. Therefore, this research is considered to promote and adopt high-valued methodologies for supporting industry to achieve global competitive advantages. [ABSTRACT FROM AUTHOR]

Using a fractional-order replication dynamic equation to describe the process of learning and modifying strategies, this paper tries to develop a fractional-order game model of green and low-carbon (GLC) innovation evolution in manufacturing enterprises. The uniqueness, local stability, and global stability of the evolutionary dynamics are discussed to determine the evolutionary stable strategy (ESS) of the game. The discretized form of the fractional-order game model, the ESS of the discretized game, and the sensitivity analysis of parameters are studied. Then, the influence of variable parameters on the ESS is analyzed using phase diagrams and bifurcation diagrams. The results show that: manufacturing industry can develop into a stable situation where all enterprises adopt GLC innovative technologies if their incomes exceed their investment; decreasing the fractional order of the model, the convergence rate to ESS will increase, but the stability of the system will decrease. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to present issues and challenges faced during a firm’s facility relocation decision aimed at improving both cost and service performance in an innovative service context.Design/methodology/approach The reader is given background of the decision-making process behind single service facility relocation decision using a detailed case study. Key financial, operational and business data of the firm are collected, compiled and analysed. The solution methodology uses a combination of qualitative and quantitative analyses to choose the best among the three possible discrete location choices. For propriety reasons, some information has been disguised, and some data have been sanitized.Findings The factors that significantly influence relocation decision are proximity to high transaction customers, infrastructure and other input costs, customer service level requirements and extant regulations. Transportation has a direct impact on cost as well as service level. Most of the findings are in line with literature, but some of them differ too.Research limitations/implications The approach is focused on a single case study of a pooling container firm in the Indian context and thereby limits the ability to generalize the findings. Nevertheless, this study may serve as a significant starting point for future research.Practical implications Firms can create a rational, efficient and even-handed approach for relocation of facilities applying a mix of qualitative and quantitative models judiciously. It provides managers better understanding and insights and actions needed for single service facility relocation.Originality/value This work is perhaps the first on facility relocation in emerging economies covering actual interventions and experiences. It gives new insights to a limited literature of relocating single service facility reflecting both theoretical imperatives and practitioner requirements. [ABSTRACT FROM AUTHOR]

Shipping containers are known as a crucial equipment for global trade. Most of their lifespan containers are spending empty, being in process of repositioning or sitting in a yard. Increasing trade imbalances globally set up empty container logistics as one of the main concerns in container shipping industry. In line with that issue, this paper will analyse the roots of empty container imbalance and port congestion, emphasizing the importance of proper empty container management and challanges which appear along the way. Results of the research show that there is room for improvement while dealing with management of empty containers which primarly implies a cognition of the imbalance problem and long-term predictions as well as mutual cooperation of all parties involved. Furthermore, new solutions and higher level of digitalization will be required to succesully and efficiently handle today's challanging situations. Reducing empty container transport to a minimum is the key point, where foldable containers and container interchange between carriers can greatly contribute. Efficiency of empty container management must be reflected in increased environmental sustainability throughout the shipping process. [ABSTRACT FROM AUTHOR]

The significance of sustainability and environmental conservation is on the rise, garnering increasing attention from customers, businesses, industries, and regulatory authorities. To foster sustainable manufacturing practices, this research paper presents a comprehensive framework that integrates synergistic elements such as rework strategies, green technology, and carbon control policies. Imperfect quality items are being considered in the model which are proposed to be dealt with a dual approach: either salvaging or reworking them. The study also investigates the impact of carbon control policies on the manufacturing industry, focusing on sustainability and the equilibrium between environmental protection and economic growth. These policies aim to regulate carbon emissions by imposing penalties or incentives, thus encouraging companies to adopt practices that reduce their carbon footprint. Furthermore, investing in green technology offers environmental benefits, cost savings, a competitive advantage, and regulatory compliance. It helps in carbon reduction through which organizations can assess their cleaner practices and environmental efforts. The objective of the developed model is to maximize the expected profit by optimizing selling price, green investment, and production quantity. Analysis of the numerical results of the proposed study is being provided to demonstrate its validity and reliability. Results demonstrated that the utilization of the rework process yields superior outcomes compared to the scenario without rework. A closer evaluation reveals that the limited carbon policy with the rework process leads to significantly diminished levels of carbon emissions and augmented profitability in contrast to alternative policies. Importantly, this approach exhibits a remarkable 2.13% higher economic efficiency and an impressive 37.10% greater adherence to environmentally sustainable practices, thus highly favoring the adoption of such strategies. Consequently, the manufacturing industry can reduce greenhouse gas emissions while promoting economic growth and profitability through the implementation of carbon control policies and investment in green technology, particularly in conjunction with rework processes. [ABSTRACT FROM AUTHOR]

Purpose: The role of data analytics is significantly important in manufacturing industries as it holds the key to address sustainability challenges and handle the large amount of data generated from different types of manufacturing operations. The present study, therefore, aims to conduct a systematic and bibliometric-based review in the applications of machine learning (ML) techniques for sustainable manufacturing (SM). Design/methodology/approach: In the present study, the authors use a bibliometric review approach that is focused on the statistical analysis of published scientific documents with an unbiased objective of the current status and future research potential of ML applications in sustainable manufacturing. Findings: The present study highlights how manufacturing industries can benefit from ML techniques when applied to address SM issues. Based on the findings, a ML-SM framework is proposed. The framework will be helpful to researchers, policymakers and practitioners to provide guidelines on the successful management of SM practices. Originality/value: A comprehensive and bibliometric review of opportunities for ML techniques in SM with a framework is still limited in the available literature. This study addresses the bibliometric analysis of ML applications in SM, which further adds to the originality. [ABSTRACT FROM AUTHOR]

The study investigates the impact of opportunistic maintenance (OM) optimization on manufacturing industries, especially in Bangladesh, to reduce maintenance costs. To that end, OM strategies have been proposed and optimized for multi-unit manufacturing systems, whereas most of the existing research is for single- or two-unit systems. OM strategies in this research cover one of the three policies: preventive replacement, preventive repair, and a two-level maintenance approach. The proposed two-level maintenance approach is a combination of lowerlevel maintenance, known as preventive repair, and higher-level maintenance, known as preventive replacement. Simulation optimization (SO) techniques using Python were utilized to evaluate the strategies. Historical data from two of Bangladesh's most promising and significant sectors, the footwear and railway industries, was used as the case study. Compared to the currently utilized corrective maintenance approach, the two-level maintenance approach is the most effective for both case studies, demonstrating cost savings of 16.9 % and 22.4 % for the footwear and railway industries, respectively. This study reveals that manufacturing industries can achieve significant cost savings by implementing the proposed OM strategies, a concept that has yet to be explored in developing countries like Bangladesh. However, the study considered the proposed approaches for major components of the system, and more significant benefits can be achieved if it is possible to apply them to all critical components of the system. [ABSTRACT FROM AUTHOR]

Background: Improving the performance of marine terminals is one of the major concerns of both researchers and decision-makers in the maritime transportation sector. The problem of container storage planning and the berth allocation problem (BAP) are the two mainstays of optimizing port operations. Methods: In this work, we address these two issues, proposing two mathematical models that operate sequentially and are applicable to both static and dynamic cases. The first developed model is a mixed-integer linear problem model aimed at minimizing vessel traffic time in the port. The second model developed is a multi-objective optimization model based on goal programming (GP) to minimize both container transfer time and the number of storage areas (minimizing container dispersion). Results: The robustness of the proposed models has been proven through a benchmark with tests using data from the literature and real port data, based on the IBM ILOG CPLEX 12.5 solver. Conclusions: The two developed mathematical models allowed the both minimization of the transfer time and the number of used storage areas, whatever the number of operations handling companies (OHCs) operating in the seaport and for both static and dynamic cases. We propose, as prospects for this work, the development of a heuristic model to deal with the major instances relating to the case of large ports. [ABSTRACT FROM AUTHOR]

As a result of the intense changes occurring in port environment over the last decades, new models of competitiveness have been developed, where port authorities try to increase their attractiveness. In this context, one of the most debated issues in this area of research is still the role played by port authorities in defining port competitiveness. The aim of this paper is to provide a review of port choice literature enabling to identify the main port choice’s criteria in order to define the role played by Port Authorities and to point out future lines of research that should be undertaken to fully incorporate current ports’ environment and performance. The results show that although some studies point out the importance of geographical factors in port choice, a larger number of studies defend the increasing role played by port authorities in determining the competitiveness through investing in port infrastructure, improving port efficiency or hinterland accessibility. Despite the existing models contributing on this topic, there are still some gaps in terms of measuring the port performance, including port strategies and studying the port choice for specific industries. [ABSTRACT FROM PUBLISHER]

We analyse the value‐added creation effect of global value chain (GVC) participation activities of APEC member economies, using a fixed‐effects regression model analysis based on country–industry data from Organisation for Economic Co‐operation and Development (OECD) Inter‐country Input–Output Tables. We find that forward participation in GVCs is more desirable than backward participation for creating domestic value‐added and that the industry position in the middle stages of the production line creates higher domestic value‐added per output unit. These results hold regardless of the application of standard Ordinary Least Squares (OLS) or fractional logit for panel data and of the characteristics of the interconnected countries in GVCs (APEC member vs. non‐APEC member economies, Asian APEC vs. non‐Asian APEC members, developed vs. developing countries). This implies that the conventional firm‐ or product‐specific U‐shaped 'smile curve hypothesis' is not applicable at the economy‐wide, country–industry level. This finding suggests that depending on the product type, manufacturing industries can be a major driving force for less‐developed APEC member economies to climb the development ladder. Since GVC participation gains are diversified across industries and upgrading country–industry positions in GVCs are challenging for APEC member economies, we strongly recommend that they construct effective domestic value chains and coordinate with other members while upgrading their GVC participation. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to define the repositioning strategy of the Port of Adria, which is the leading container maritime port of Montenegro. The strategy is an integral reflection of the analysis of internal (competitive advantage and financial strength) and external (the potential of container maritime port industry and environmental stability) repositioning criteria. The case study in this paper is mainly accomplished through the definition of specific propositions that clarify the connections between these criteria and the repositioning strategy. Knowledge and attitudes of stakeholders are used with the purpose of modeling a marketing strategy, which is based on an inductive study. The paper proposes a model based on a specific maritime port case which can be applied to any other case of maritime port repositioning as well.

Developing an economic net-zero energy infrastructure for the manufacturing industry can play a critical role to achieve the goal of affordable, reliable, and sustainable clean energy paradigm for the next generation. However, it is quite challenging to develop such an infrastructure due to the uncertain demand of the manufacturing system, intermittent electricity generation from the renewable sources, time of use (TOU) pricing of electricity, and integrated operational planning for the long-term planning horizon. In this paper, a mixed-integer non-linear programming (MINLP) model is developed to economically design an onsite microgrid system considering the critical conditions and achieve a net-zero energy operation planning for the manufacturing industry. A linearization strategy is adopted to obtain the optimal design of the microgrid and the utilization of the resources. A numerical case study is conducted to evaluate the effectiveness of the model. [ABSTRACT FROM AUTHOR]

• We exam the social psychology of technology adoption in container trucking industry. • Our research includes contextualized behavior analysis and discrete choice model. • Risk tolerance positively moderates influence of the status quo on adoption. • Service-orientation negatively moderates influence of the status quo on adoption. Most extant literature in the transportation industry views innovation adoption as a rational choice process conducted on a cost-benefit calculation basis. This restricts our understanding of innovation decisions made by individuals embedded in a social-economic context. By investigating the underlying social psychology of the innovation adoption in the Chinese container trucking industry, this paper aims to answer the question as to 'why trucking operators postpone adopting the cargo-truck matching system during its early stage'. In order to achieve the research objective, a mixed methods research framework is proposed. First, we conduct four in-depth interviews using semi-structured questionnaires to investigate the contextualized behavior of individuals, based on which three hypotheses are developed. Second, based on the data collected from an online questionnaire survey covering 282 trucking operators in Ningbo, the proposed empirical hypotheses are tested using a discrete choice model. We find that risk tolerance positively moderates influence of the status quo on the innovation adoption decision, whilst the effect on it of service-orientation is negative. [ABSTRACT FROM AUTHOR]

Liner shipping plays an important role in international shipping. This article systematically reviews studies regarding liner shipping alliance management from three decision-making levels: strategic decision, tactical operations and management policy. These studies are addressed and summarized throughout the management process, including making an alliance, partner selection, cooperation mechanism design, synergy planning and performance appraisal. In order to make a scientifical classification, this paper further elaborates comprehensively on journals, research topics and modelling approaches of the studies and the relationships among them. At last, in terms of the gap between the practices of liner container shipping industry and existing academic studies, diversification and flexibility of cooperation modes, intelligent operations, multi-objective optimization, environmental protection and a sound supervision mechanism in liner shipping alliance management are expected to be covered in future research. The main purpose of this paper is to improve the understanding of the management concept and technology of liner shipping alliance, and encourage more research and application. ● Liner shipping alliance management from three decision-making levels is investigated. ● Problems to form a liner shipping alliance such as partner selection and cooperation design are discussed. ● Journals, research topics and modelling approaches of the studies are reviewed. [ABSTRACT FROM AUTHOR]

• Manufacturing is the only strategic key sector in terms of driving economic growth for most developing countries in all the period analyzed. • Manufacturing has lost its relative importance in developed and developing countries in terms of linkages. • Manufacturing still has a greater capacity to influence the per capita income growth rate. This paper aims to investigate how manufacturing affects economic growth over time, especially in developing countries. We apply Panel Vector Autoregression (PVAR) for fixed effects approach, and then we estimate impulse-response functions (IRF) and forecast-error variance decomposition (FEVD) for a sample of 115 countries from 1990 to 2011. Furthermore, we apply Hirschman-Rasmussen (HR)'s Index for 29 countries for 1995, 2000, 2005 and 2010 as well as Field of Influence for this group of countries for 1995 and 2010. The main results indicate that manufacturing industry can work as "engine of growth" in developing countries. Moreover, manufacturing is the only strategic key sector in terms of driving economic growth for most developing countries in all the period analyzed. However, manufacturing has lost its relative importance in developed and developing countries in terms of linkages. [ABSTRACT FROM AUTHOR]

The pharmaceutical industry is facing significant economic challenges due to measures aimed at containing healthcare costs and evolving healthcare regulations. In this context, pharmaceutical laboratories seek to extend the lifespan of their machinery, particularly fluid bed dryers, which play a crucial role in the drug production process. Older fluid bed dryers, lacking advanced sensors for real-time temperature optimization, rely on fixed-time deterministic approaches controlled by operators. To address these limitations, a groundbreaking approach taking into account Exploration Data Analysis (EDA) and a Catboost machine-learning model is presented. This research aims to analyze and enhance a drug production process on a large scale, showcasing how AI algorithms can revolutionize the manufacturing industry. The Catboost model effectively reduces preheating phase time, resulting in significant energy savings. By continuously monitoring critical parameters, a paradigm shift from the conventional fixed-time models is achieved. It has been shown that the model is able to predict on average a reduction of 50.45% of the preheating process duration and up to 59.68% in some cases. Likewise, the energy consumption of the fluid bed dryer for the preheating process could be reduced on average by 50.48% and up to 59.76%, which would result on average in around 3.120 kWh energy consumption savings per year. [ABSTRACT FROM AUTHOR]

The growth trend in the container industry has had a significant operational and infrastructural impact on the ports. In this context, the offshore port systems are expected to be an innovative port system in the effective use of mega container ships by offering operational and structural advantages. This study aims to guide the authorities on whether OCPS is worth investing in, in terms of investment costs. This article also highlights the financial feasibility of an OCPS that can allow countries with difficult nautical access to mega vessels to enter the global trade network. The data in this research were obtained from similar projects and studies with a series of industry assumptions. Overall, these results indicate that OCPS can compete with conventional ports in terms of investment costs, operating costs, and return on investment. Thus, a more sustainable container shipping network can be achieved with the advantages of OCPS. [ABSTRACT FROM AUTHOR]