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This paper aims to present the design and a prototype experiment of a robotic joint module for tokamak in-vessel manipulator-related research; the results will promote the adaptation of current in-vessel inspection manipulator to achieve full tokamak in-vessel environment compatibility.

A flexible metallic bellow-enclosed working chamber is used to protect the main servo drive components, the active cooling method for high temperature protection and the servo control structure simplification for high radiation endurance. A joint module prototype is manufactured and tested under a similar in-vessel environmental condition for extreme condition protection validation and basic servo control ability evaluation.

The joint module prototype successfully survived the similar in-vessel environment tests and proved good mobility via closed-loop servo control. A conceptual design of a serial linkage manipulator with joint module structure is proposed for future in-vessel inspection manipulator development.

The proposed joint module uses common industrial servo components to achieve its full extreme in-vessel environment compatibility. Different from traditional metallic bellow application in a vacuum environment to produce a linear movement result, the proposed joint module aims to achieve rotating movement directly from the metallic bellow structure, thereby reducing the joint structure space requirement, simplifying the vacuum environment movement transmission structure and increasing the vacuum environment compatibility degree.

This paper aims to present the design and experimental tests of an active circulating cooling system for the Experimental Advanced Superconducting Tokamak in-vessel inspection manipulator, which will help the current manipulator prototype to achieve a full-scale in-vessel high temperature environment compatibility.

The high-temperature effects and heat transfer conditions of the manipulator under in-vessel environment were analyzed. An active circulating cooling system was designed and implemented on the manipulator prototype. A simulative in-vessel inspection task in a high temperature environment of 100°C was carried out to evaluate the performance of the active circulating cooling system.

The proposed active circulating cooling system was proved effective in helping the manipulator prototype to achieve its basic in-vessel inspection capability in a high temperature environment. The active circulating cooling system performance can be further improved considering the cooling structure coefficient differences in different manipulator parts.

For the first time, the active circulating cooling system was implemented and tested on a full-scale of the in-vessel inspection manipulator. The experimental data of the temperature distribution inside the manipulator and the operating status of the circulating system were helpful to evaluate the current active circulating cooling system design and provided effective guidance for improving the overall system performance.

This paper aims to present a different cooling method (water cooling) to protect all the mechanical/electrical components for Tokamak in-vessel inspection manipulator. The method is demonstrated effective through high temperature experiment, which provides an economical and robust approach for manipulators to work normally under high temperature.

The design of cooling system uses spiral copper tube structure, which is versatile for all types of key components of manipulator, including motors, encoders, drives and vision systems. Besides, temperature sensors are set at different positions of the manipulator to display temperature data to construct a close-loop feedback control system with cooling components.

The cooling system for the whole inspection manipulator working under high temperature is effective. Using insulation material such as rubber foam as component coating can significantly reduce the environmental heat transferred to cooling system.

Compared with nitrogen gas cooling applied in robotic protection design, although it is of less interest in prior research, water cooling method proves to be effective and economical through our high temperature experiment. This paper also presents an energetic analysis method to probe into the global process of water cooling and to evaluate the cooling system.

Artificial intelligence (AI) and automation are technologies that make a global impact by optimizing manual and time-intensive processes using data analytics and robotics, thus making the task more efficient, effective and less time-consuming. This is represented in the cyber-physical context, in which humans and technologies are allowed to coexist and learn from each other.

The logistics and supply chain sector consists of numerous partners and stakeholders, and despite the limited inclusion of automation and AI within the sector, there are still many manual and repetitive tasks.

Stakeholders in the logistics and supply chain sector are creating awareness and slowly implementing AI and automation within their operations. The majority of shipping and logistics is done through the maritime sector, and this is expected to increase in line with the world’s population.

Research was limited to Jamaica and a few other countries in the Caribbean. Broadening the scope to include other regional shipping and logistics industry stakeholders would be helpful.

The removal of sometimes mundane and even more complex manual processes in the logistics supply chain will give rise to more efficiencies and possibly increased revenue.

Creating awareness in the Caribbean of international trends is a challenge. Empowering people to use automation and AI for the mitigation and adaptation of climate change and other disasters is yet to be fully realized. However, those who took part in the study did show a significant inclination toward the use of automation and AI in their every-day lives.

The purpose of this paper is to examine statistical data on the understanding of automation and AI within education, the port authority and major operators in the shipping and logistics sector throughout the Caribbean.

The purpose of this paper is to develop a new interdisciplinary methodology to estimate the life cycle cost (LCC) of complex business-to-business products in order to price different types of maintenance contracts and show the applicability of the method in a case study. LCC comprise of initial capital costs as well of operation costs including probabilistic costs (such as the costs of repairs and spare parts), which are directly linked to the maintenance characteristics of the product.

The paper proposes an integrated and practical methodology that applies different approaches from different disciplines. Therefore, exponential distributions for failure rates in subsystems, World Bank logistics factors for logistics costs of spare part handling, as well implied credit default probabilities for the counterpart risk in full service leasing contracts are applied. In order to validate the applicability of the proposed methodology to practical problems, the tool is applied in three case studies.

The results of the case studies show that this methodology can be applied to analyze LCC structures of engines operating in various regions with regard to different types of engine maintenance contracts. The results also highlight the interplay of technical as well as financial risks.

Because the literature in maintenance engineering so far either proposes general frameworks to calculate LCC or concentrates on specific aspects of LCC, the paper contributes to the literature in presenting a new interdisciplinary methodology to estimate the LCC.

The global economy is highly dependent upon international ocean shipping and important related industries, such as vessel brokerage and chartering. Maritime safety in today's international economic environment presents policy, management, and ethical dilemmas for global business managers, including those not directly involved with managing marine transportation. This paper presents some of these issues, calls for managerial attention to the ethical problems raised, and adapts an existing framework for ethical decision‐making for this purpose.

The purpose of this paper is to propose a new deep learning-based model to carry out better maintenance for naval propulsion system.

This model is constructed by integrating different deep learning algorithms. The basic idea is to change the connection structure of the deep neural network by introducing a residual module, to limit the prediction output to a reasonable range. Then, connect the Deep Residual Network (DRN) with a Generative Adversarial Network (GAN), which helps achieve data expansion during the training process to improve the accuracy of the assessment model.

Study results show that the proposed model achieves a better prediction effect on the dataset. The average performance and accuracy of the proposed model outperform the traditional models and the basic deep learning models tested in the paper.

The proposed model proved to be better performed naval propulsion system maintenance than the traditional models and the basic deep learning models. Therefore, our model may provide better maintenance advice for the naval propulsion system and will lead to a more reliable environment for offshore operations.

The purpose of this paper is to explore how change is brought about in quality governance of Baltic maritime oil transportation.

This qualitative case-study sought to understand the underlying mechanisms of quality governance. The paper analyzed versatile empirical material (including expert interviews) to uncover how a particular constellation of public and private, binding and voluntary, internal and external quality standards impacted the process of institution building for quality management in Baltic oil shipping.

The paper shows that emergence of quality practices in oil shipping is associated not only with the development of shipping industry as a whole, but also with the dynamics within the energy value chain. The findings suggest that alignment between rules and incentives is specific to a combination of given natural, political and economic contexts as well as physical infrastructure which set applied limitations upon the governance process and, eventually, impact the set of quality governance mechanisms available for use.

The paper shows that collective action is contextually-bound, thus the mechanisms of quality shipping governance can essentially differ from one locality to another. This implies that local solutions can be found to problems conventionally identified as global.

Paper’s findings question the applicability of “one-size-fits-all” approaches to policy-making and calls for more targeted regulation. The research also stresses the role of technical modernization in prompting actual change in regards to quality practices.

This research claims that transition to sustainable transportation systems requires institutions that are capable of linking actors and contexts in a way that balances supply and demand for quality.

The Joint European Torus (JET) is the flagship for European Fusion Research. This study seeks to address the issue of the need for remote handling in the process of recreating nuclear fusion as a limitless source of clean energy.

Describes in detail the JET remote handling system with its “man in the loop” approach providing the operator with “remote hands” inside the JET Torus.

Finds that the increase in requirement for remote operations has necessitated rationalization of task procedures and their associated paper work.

This paper opens the gates for increasing productivity, broadening the scope of remote handling procedures, increasing operating loads and reducing downtime.

The volumes of international containerized trade substantially increased over the past years. In the meantime, marine container terminal (MCT) operators are facing congestion issues at their terminals because of the increasing number of large-size vessels, the lack of innovative technologies and advanced handling equipment and the inability of proper scheduling of the available resources. This study aims to propose a novel memetic algorithm with a deterministic parameter control to facilitate the berth scheduling at MCTs and minimize the total vessel service cost.

A local search heuristic, which is based on the first-come-first-served policy, is applied at the chromosomes and population initialization stage within the developed memetic algorithm (MA). The deterministic parameter control strategy is implemented for a custom mutation operator, which alters the mutation rate values based on the piecewise function throughout the evolution of the algorithm. Performance of the proposed MA is compared with that of the alternative solution algorithms widely used in the berth scheduling literature, including a MA that does not apply the deterministic parameter control strategy, typical evolutionary algorithm, simulated annealing and variable neighborhood search.

Results demonstrate that the developed MA with a deterministic parameter control can obtain superior berth schedules in terms of the total vessel service cost within a reasonable computational time. Furthermore, greater cost savings are observed for the cases with high demand and low berthing capacity at the terminal. A comprehensive analysis of the convergence patterns indicates that introduction of the custom mutation operator with a deterministic control for the mutation rate value would provide more efficient exploration and exploitation of the search space.

This study does not account for uncertainty in vessel arrivals. Furthermore, potential changes in the vessel handling times owing to terminal disruptions are not captured.

The developed solution algorithm can serve as an efficient planning tool for MCT operators and assist with efficient berth scheduling for both discrete and continuous berthing layout cases.

The majority of studies on berth scheduling rely on the stochastic search algorithms without considering the specific problem properties and applying the guided search heuristics. Unlike canonical evolutionary algorithms, the developed algorithm uses a local search heuristic for the chromosomes and population initialization and adjusts the mutation rate values based on a deterministic parameter control strategy for more efficient exploration and exploitation of the search space.