Unmanned autonomous cargo ships may change the maritime industry, but there are issues regarding reliability and maintenance of machinery equipment that are yet to be solved. This article examines the applicability of the Reliability Centred Maintenance (RCM) method for assessing maintenance needs and reliability issues on unmanned cargo ships. The analysis shows that the RCM method is generally applicable to the examination of reliability and maintenance issues on unmanned ships, but there are also important limitations. The RCM method lacks a systematic process for evaluating the effects of preventive versus corrective maintenance measures. The method also lacks a procedure to ensure that the effect of the length of the unmanned voyage in the development of potential failures in machinery systems is included. Amendments to the RCM method are proposed to address these limitations, and the amended method is used to analyse a machinery system for two operational situations: one where the vessel is conventionally manned and one where it is unmanned. There are minor differences in the probability of failures between manned and unmanned operation, but the major challenge relating to risk and reliability of unmanned cargo ships is the severely restricted possibilities for performing corrective maintenance actions at sea.
This report presents the AEGIS roadmap for automated waterborne transport and is the result of the work related to Task 2.5 Roadmap for waterborne logistics redesign as defined in the AEGIS Grant Agreement. The task was to collect the results of the AEGIS work package 2 and 6, and the AEGIS use cases, to provide a publicly available roadmap for the redesign of more sustainable waterborne transport. Furthermore, the main AEGIS solutions that can be used to realize the redesign were to be identified, and benefits and possible costs were to be described, exemplified by future transport systems, including intercontinental transport. Furthermore, the focus was to be on unitized cargo (ie, containers and ro-ro trailers).
The report is based on the AEGIS use cases and outlines one logistics redesign for short sea shipping where the cargo is containers, and one for inland waterways shipping where the cargo is roro trailers. Intercontinental transport was not studied in detail within the AEGIS project, as it was not in scope. This means that no study investigating the applicability of AEGIS solutions for intercontinental transport has been done, and thus the background for creating a roadmap for intercontinental transport is missing. Instead, intercontinental transport is briefly discussed in a separate section of the report. Furthermore, even though the AEGIS solutions do not target the deep sea leg of intercontinental transport, they are highly applicable to the distribution and consolidation of cargo in the hinterland. For this part of intercontinental transport, the short sea and inland transport roadmaps are directly applicable.
For each of the two segments short sea and inland waterways, the bassline "as-is" scenarios are discussed to provide insight into current challenges and areas with potential for improvements. Then a redesign is introduced, where the AEGIS innovations and concepts are used to gain efficiency benefits and zero emission transport systems. As part of the redesign discussion, the gaps towards realization are also discussed and identified. These are related to immature technology, certain issues that are currently not addressed and need both research and development, and issues related to uptake and investment risk. Next, one roadmap for short sea shipping and one for inland waterways is presented, and discussed in terms of short term, medium term and long term phases and what advancements need to be made (ie, what gaps need to be closed) within each of these periods. Finally, policy support and actions are discussed in terms of what will be required to realize the roadmaps.
The two roadmaps presented in this report include discussions for the short-, medium- and long-term periods. The roadmaps are structured this way to facilitate a discussion around which aspects are mature, and which require more research and has a longer expected horizon to market. The roadmaps are written with the purpose of allowing the implementation of the new transport systems in the short, medium and long term, and a discussion is made around the sustainability of the transport system at each maturity level.
In this article, we develop a deep neural network model to estimate the wave added resistance. The required data to train the model is generated using strip theory calculations over a wide range of hull geometries and operational conditions. The model is efficient as it only requires the ship’s main particulars: length, beam, draft, block coefficient, and slenderness ratio. In addition, we present an application of this model in a vessel performance framework. This will be used for predicting propulsion power and analyzing the degree of biofouling on ships from the company Ultrabulk2. The study shows that the developed deep neural network model produces reliable results in predicting the added wave resistance coefficient in comparison to strip theory calculations. Also, the developed ship propulsion and biofouling analysis display satisfactory output for monitoring hull performance under actual ship operational conditions.
With the rise of ‘new’ state capitalisms, control over transport infrastructure has returned to the forefront of competition in the global economy. This article investigates how different state capitalisms interact to enable economic developments in ports. It tracks the relationship between state-owned firms in the shipping and ports sectors through a case study of the port of Valencia in Spain and COSCO shipping group. The article identifies state capitalisms as variegated and relational to analyze the ways in which qualitatively different state capitalist dynamics interact at different scales. The article identifies two state capitalist dynamics which have been dominant in determining relations between Spanish and Chinese state capitalisms: 1) A commercial dynamic of maximizing Spanish ports profits by establishing new relationships with Chinese firms; and 2) an expansionary dynamic of increasing market share of Chinese state-owned firms in European shipping markets. These two dynamics are synergistic and have contributed to the competitiveness of Spanish ports and Chinese shipping firms by providing new capital to the port of Valencia and expanding the port's profile as a hub in the eastern Mediterranean, while also further solidifying COSCO's position in European shipping markets and its internalization and vertical integration strateg
With the current revolution in Shipping 4.0, a tremendous amount of data is accumulated during vessel operations.
Data quality (DQ) is becoming more and more important for the further digitalization and effective decision-making
in shipping industry. In this study, a practical DQ assessment method for raw data in vessel operations is proposed.
In this method, specific data categories and data dimensions are developed based on engineering practice and existing
literature. Concrete validation rules are then formed, which can be used to properly divide raw datasets. Afterwards,
a scoring method is used for the assessment of the data quality. Three levels, namely good, warning and alarm,
are adopted to reflect the final data quality. The root causes of bad data quality could be revealed once the internal
dependency among rules has been built, which will facilitate the further improvement of DQ in practice. A case study
based on the datasets from a Danish shipping company is conducted, where the DQ variation is monitored, assessed
and compared. The results indicate that the proposed method is effective to help shipping industry improve the quality
of raw data in practice. This innovation research can facilitate shipping industry to set a solid foundation at the early
stage of their digitalization journeys.
With the current revolution in Shipping 4.0, a tremendous amount of data is accumulated during vessel operations.
Data quality (DQ) is becoming more and more important for the further digitalization and effective decision-making
in shipping industry. In this study, a practical DQ assessment method for raw data in vessel operations is proposed.
In this method, specific data categories and data dimensions are developed based on engineering practice and existing
literature. Concrete validation rules are then formed, which can be used to properly divide raw datasets. Afterwards,
a scoring method is used for the assessment of the data quality. Three levels, namely good, warning and alarm,
are adopted to reflect the final data quality. The root causes of bad data quality could be revealed once the internal
dependency among rules has been built, which will facilitate the further improvement of DQ in practice. A case study
based on the datasets from a Danish shipping company is conducted, where the DQ variation is monitored, assessed
and compared. The results indicate that the proposed method is effective to help shipping industry improve the quality
of raw data in practice. This innovation research can facilitate shipping industry to set a solid foundation at the early
stage of their digitalization journeys.
The literature on liner shipping includes many models on containership speed optimization, fleet deployment, fleet size and mix, network design and other problem variants and combinations. Many of these models, and in fact most models at the tactical planning level, assume a fixed revenue for the ship operator and as a result they typically minimize costs. This treatment does not capture a fundamental characteristic of shipping market behavior, that ships tend to speed up in periods of high freight rates and slow down in depressed market conditions. This paper develops a simple model for a fixed route scenario which, among other things, incorporates the influence of freight rates, along with that of fuel prices and cargo inventory costs into the overall decision process. The objective to be maximized is the line’s average daily profit. Departing from convention, the model is also able to consider flexible service frequencies, to be selected from a broader set than the standard assumption of one call per week. It is shown that this may lead to better solutions and that the cost of forcing a fixed frequency can be significant. Such cost is attributed either to additional fuel cost if the fleet is forced to sail faster to accommodate a frequency that is higher than the optimal one, or to lost income if the opposite is the case. The impact of the line’s decisions on CO2 emissions is also examined and illustrative runs of the model are made on three existing services.
Using evidence from 25,250 records of vessels entering and clearing the rivers of the Chesapeake Bay, this article demonstrates that intercolonial trading captains and crews significantly reduced the number of days their vessels spent in port in Virginia between 1698 and 1766. This contraction reflected a quantifying ethos in shipping that emerged during the early age of sail as the result of mutually reinforcing legal requirements and management practices. Responding to these productivity pressures, captains embraced practices that limited sailors’ freedom and turned to enslaved sailors to guarantee their maritime labor force. Embracing unfreedom aided captains to realize the dispatch goals that helped guarantee their investors’ returns.
Green Liner Shipping Network Design refers to the problems in green logistics related to the design of maritime services in liner shipping with a focus on reducing the environmental impact. This chapter discusses how to more efficiently plan the vessel services with the use of mathematical optimization models. A brief introduction to the main characteristics of Liner Shipping Network Design is given, as well as the different variants and assumptions that can be considered when defining this problem. The chapter also includes an overview of the algorithms and approaches that have been presented in the literature to design such networks.
The rapid growth of e-commerce applications has promoted the establishment of shipping e-commerce channels by many liner companies in addition to their existing traditional Non-vessel operating common carrier (NVOCC) channel. Unlike NVOCC channels, shipping e-commerce channels guarantee shippers the availability of contracted container slots. However, some problems arise, including the competition with NVOCC channels, shipping slot sales’ risk, and the increasing liner companies’ costs. Therefore, this paper addresses optimal sales strategy selection in the liner transportation industry, including a single traditional NVOCC channel (TN) strategy, and a dual channel with both e-commerce and NVOCC channels (EN) strategy. Two contract scheme models are constructed considering the channel competition on canvassing ability, overselling behavior, demand fluctuation, and the limited liner vessel capacity. Findings show that the impact of overselling behavior on the profit under the EN and TN is not always negative, which is related to the shipping capacity and probability of the high canvassing ability. Comparative analyses reveal that the EN is dominant if the unit overselling compensation cost varies small. Meanwhile, the TN is profitable if the unit overselling compensation cost increases and the canvassing cost of e-commerce channel exceeds a certain value. Otherwise, the selection of sales strategy relies on the arrival rate, the canvassing cost of the e-commerce channel and shipping capacity. The results offer new insights to both theoretical research on container slot sales and the practical selection of sales strategy since shipping e-commerce has changed the slot selling mode in the container shipping industry, which could also enhance the competitiveness of liner companies in the container shipping industry.