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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]

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]

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]

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]

In this paper, the maritime industry’s commitment to green supply chain has been analyzed. The objective of this study is to show that the reuse of empty containers not only adds value to a firm, but leads to waste reduction in the supply chain. The novelties of this article include (i) empty and laden containers are treated in accordance with a shipping company’s green effort; (ii) both the volume and weight of containers are introduced to indicate a potential constraint on green effort; (iii) empty container storage costs are included as a value-added component which stem from green effort. [ABSTRACT FROM AUTHOR]

Although long-haul intermodal container transportation combines multiple transportation modes including shipping, the most critical aspect of enabling door-to-door service is container port drayage operation. Container port drayage connects customers and container ports and provides an effective solution to the first/last-mile problem faced by the container logistics industry. Therefore, container port drayage has a significant impact not only on the economic advantages of the long-haul intermodal container transportation chain, but also the management, environment and social benefits of the stakeholders involved. In this paper, we comprehensively review the existing literature on container port drayage studies from different methodological angles (e.g., model development and algorithm design) and technological angles (e.g., autonomous truck and blockchain). Moreover, with the shifting of industrial focus from traditional operations and management of container port drayage towards e-commerce platforms, we identify potential issues for future research directions. • Critically review the studies on container port drayage from the perspective of operations and management. • Systematically examine the interactions between main stakeholders of container port drayage services. • Identify future research focuses and directions of container port drayage operations and management. [ABSTRACT FROM AUTHOR]

The shipping industry is fairly volatile pertaining to shipment pricing. To handle this volatility, two types of pricing strategies are employed in the shipping sector, contract market pricing and spot pricing. The contract market offers a fixed shipment price for a known cargo task over a set period, with secured booking space in periods of high demand. The spot market has a fluctuating shipment price, where one can benefit from lower prices than contract rate shipment prices in the low season, but face escalating shipment prices and less certainty of being able to secure a booking on a particular vessel in peak season, as space is reserved for contracted customers. However, both the pricing strategies followed have no relationship between current shipment demand and available shipping capacity and shipment prices are quoted based on predefined price lists (hard copy). This paper addresses the research gap of optimal spot shipment price calculation based on current shipment demand and available shipping capacity. To do so, we have developed a model that utilizes historical data to calculate spot pricing for container shipments. The proposed model is capable of calculating shipment spot prices based on shipment demand and capacity. Data from various sources was gathered to generate a shipping dataset for three years (i.e. from 2016 until 2018). Regression and correlation analysis are used to quantify research outcomes. Results have shown that the proposed model significantly increases the correlation between shipment price and shipment demand from 0.33 to 0.88 and available capacity from − 0. 12 to 0.35 respectively. [ABSTRACT FROM AUTHOR]

• Modified cost-sensitive classification strategy for an industrial problem. • Decision rule for going through or skipping elements of last quality control stage. • Trade-off problem between cost and quality. • Modified strategy can also be applied on problems without an associated cost. In the current era of Industry 4.0, sensor data used in connection with machine learning algorithms can help manufacturing industries to reduce costs and to predict failures in advance. This paper addresses a binary classification problem found in manufacturing engineering, which focuses on how to ensure product quality delivery and at the same time to reduce production costs. The aim behind this problem is to predict the number of faulty products, which in this case is extremely low. As a result of this characteristic, the problem is reduced to an imbalanced binary classification problem. The authors contribute to imbalanced classification research in three important ways. First, the industrial application coming from the electronic manufacturing industry is presented in detail, along with its data and modelling challenges. Second, a modified cost-sensitive classification strategy based on a combination of Voronoi diagrams and genetic algorithm is applied to tackle this problem and is compared to several base classifiers. The results obtained are promising for this specific application. Third, in order to evaluate the flexibility of the strategy, and to demonstrate its wide range of applicability, 25 real-world data sets are selected from the KEEL repository with different imbalance ratios and number of features. The strategy, in this case implemented without a predefined cost, is compared with the same base classifiers as those used for the industrial problem. [ABSTRACT FROM AUTHOR]