J.W. Frouws
Please Note
32 records found
1
Maritime fuels of the future
A decision support tool for shipowners
Identifying and improving port call processes to enable Just-In-Time arrivals and services
A case study on MSC container shipping in the Port of Rotterdam
In recent years, a rapid development of the offshore wind power market has taken place. The growing demand for more offshore wind farms and the desire to make this technology more cost-effective has created many challenges for offshore contractors and their technology, particularly for turbine installation vessels. Currently, the most widely used equipment is the jack-up type crane vessels. These vessels have been optimised for turbine installation operations but are now starting to reach their limits in performance, based on the further improvement of the wind turbines, the fact that the wind farms located further and deeper at the sea. As a result, new designs may be better suited to the challenging requirements of the wind farm developers. In practical terms, it is difficult to predict whether a new concept will perform better another. Operational data from past turbine installation vessel operations can be used to identify important parameters that influence performance but is not practical when applied to unconventional designs such as the concept ship, “Wind Turbine Shuttle” designed by Huisman Equipment in the Netherlands. An extensive study is necessary requiring perhaps the development of new analysis tools. This study attempts to identify the major parameters that influence the operations of turbine installation vessels. It investigates with the use of different operational scenarios, how the procedure of installation and transportation of these vessels are influenced by their parameters such as the pre-assembly method of the wind turbine or the wind turbine sizes and their operating environment, using a market and technology review of the wind farm market, a sensitivity analysis of various design parameters and different case strategies investigating the performance of different turbine installation vessels operating in a predefined wind farm location. Because several strategies have shown that weather delays have a major effect on the workability of the vessel, the simulation model uses wave height time series data from measurements made in the North Sea. For the sensitivity studies of design parameters, results show that for any scenario, an optimal value for both significant wave height tolerance and transit speed can be found. The optimal parameters for the scenario designed in this study are similar to the specifications of the Wind Turbine Shuttle. Overall, results show a definite advantage of using a turbine installation vessel such as the Wind Turbine Shuttle over traditional jack-up vessels. However, as the model is based on many assumptions, the accuracy of the results would be significantly improved with additional real life data. Regardless of this, the study has demonstrated the advantage of opting for a systems approach containing various models that are connected to each other. This methodology has many possible future applications, not only for the evaluation of wind turbine installation vessels but for any vessel type employed in the offshore construction segment. ...
In recent years, a rapid development of the offshore wind power market has taken place. The growing demand for more offshore wind farms and the desire to make this technology more cost-effective has created many challenges for offshore contractors and their technology, particularly for turbine installation vessels. Currently, the most widely used equipment is the jack-up type crane vessels. These vessels have been optimised for turbine installation operations but are now starting to reach their limits in performance, based on the further improvement of the wind turbines, the fact that the wind farms located further and deeper at the sea. As a result, new designs may be better suited to the challenging requirements of the wind farm developers. In practical terms, it is difficult to predict whether a new concept will perform better another. Operational data from past turbine installation vessel operations can be used to identify important parameters that influence performance but is not practical when applied to unconventional designs such as the concept ship, “Wind Turbine Shuttle” designed by Huisman Equipment in the Netherlands. An extensive study is necessary requiring perhaps the development of new analysis tools. This study attempts to identify the major parameters that influence the operations of turbine installation vessels. It investigates with the use of different operational scenarios, how the procedure of installation and transportation of these vessels are influenced by their parameters such as the pre-assembly method of the wind turbine or the wind turbine sizes and their operating environment, using a market and technology review of the wind farm market, a sensitivity analysis of various design parameters and different case strategies investigating the performance of different turbine installation vessels operating in a predefined wind farm location. Because several strategies have shown that weather delays have a major effect on the workability of the vessel, the simulation model uses wave height time series data from measurements made in the North Sea. For the sensitivity studies of design parameters, results show that for any scenario, an optimal value for both significant wave height tolerance and transit speed can be found. The optimal parameters for the scenario designed in this study are similar to the specifications of the Wind Turbine Shuttle. Overall, results show a definite advantage of using a turbine installation vessel such as the Wind Turbine Shuttle over traditional jack-up vessels. However, as the model is based on many assumptions, the accuracy of the results would be significantly improved with additional real life data. Regardless of this, the study has demonstrated the advantage of opting for a systems approach containing various models that are connected to each other. This methodology has many possible future applications, not only for the evaluation of wind turbine installation vessels but for any vessel type employed in the offshore construction segment.
A comparison between the ’Smart-Stabiliser’ and a wider ship
The case of Jumbo Maritime
Maintenance and Repair
A Maintenance and Repair Management Performance Model for Tugs
Synergies in Liner Shipping
Integrating Quantitative and Qualitative Analysis in the Partnership Decision
Assessing port competition via a cost-based logistic chain model
A transparent and generic approach
Energy Efficiency - The Data-driven Decision Support System Perspective
A Case Study About Long Distance Towage for Boskalis
Factors affecting container transshipment volumes at ports:
A data driven holistic modelling approach
Requirements for Cargo Features on New Parcel Tankers
A Study for Stolt Tankers
Evaluating the potential of a mobile shiprepair facility
A feasibility study in the conceptual phase
Vessel's Performance Modelling
Developing a digital twin for the propulsion system, a Spliethoff group case
2020 IMO Sulphur Regulation
Impacts and Solutions for Fednav Limited
Economic feasibility of a hydrogen-fuelled marine transportation system
Case study of a bulk carrier at CMB
Towards a Roadmap of IHC IQIP
Oil & Gas Market Analysis
Ship Performance Management and the added value of a Ship Performance Monitoring System
A Spliethoff Group Case
During the research it is found that high data quality is of the utmost importance in order to accurately asses the performance of a vessel. A structured method for assessing the data collected by the performance monitoring is found and applied to the performance monitoring system as a verification. Data quality deficits such as the speed of the ETL processes, incorrect data blending and calculations are identified and corrected. This led to a near live, high quality data stream which can be used to asses and optimise the performance. Continual assessment and improvement of the data quality is recommended.
Suitable methods to analyse this data to create knowledge are determined. A form of hybrid modelling where simple theoretical models are fitted to the filtered data using regression is used to create baselines and give a clear overview of the effects of certain operational parameters on the performance of a vessel. These models can then also be used to increase the accuracy of tools such as the weather routing and voyage planning tool. Benchmarking between sister vessels or the baselines is seen as a good means to identify performance deficits. Visualising and analysing the data with the help of a BI tools is a good way to share the knowledge throughout the company.
The performance management in place at Spliethoff is assessed to form a baseline to improve upon. It became apparent that Spliethoff overall has a good idea how to optimise performance but it does not have the information or data needed to do so. Since there is no information about the gain in performance of certain tools they are not used correctly. Being able to show the performance gain from using these tools is an important benefit of the performance monitoring system. The communication and knowledge sharing throughout the company can also be improved with the use of the performance monitoring system. Poor follow up from upper management when performance deficits on top of this indicate that a lot of value can be created with an improved performance management plan which incorporates the performance monitoring system.
A new performance management plan based on ISO 50001 is proposed to realise this value. Due to the available data the management plan focuses on reducing fuel costs and optimising voyage planning.This is done by awareness creation through performance dashboards which also increase the information sharing between shore and vessel. A change in company culture to a more data based decision making and communicative culture is promoted and implemented through this plan.
To determine how much added value can be realised, the costs and value realisation potentials of the performance management system are specified. These are then used to determine the net present value of the performance management project for several scenarios. A large fleet and a small fleet implementation are researched. The total capital investment is either €543,000 when only the large consumers of the fleet are included (small fleet) or €1,310,000 when almost the entire fleet is included (large fleet). Only the direct monetary value is used to determine the net present value but indirect and non monetary values are also mentioned. The direct monetary value potentials are derived from operational cases where performance deficits have been identified. The resulting total added value (NPV) of the small fleet implementation ranges from €2,165,970 in a pessimistic scenario to €8,711,272 in an optimistic scenario after 11 years. €6,000,146 is the expected total added value realisation for the small fleet implementation after 11 years. For the large fleet the results are: €4,966,756 for the pessimistic scenario, €18,103,704 for the optimistic scenario and and expected added value of €12,805,994 after 12 years. Most scenarios have a pay back period of less than 2 years with the exception of the pessimistic scenario of the large fleet which has less than 3 years. All indirect and non monetary value is seen as a bonus on top of this meaning that there certainly is a lot of added value to be realised by implementing performance management which is supported by a performance monitoring system. ...
During the research it is found that high data quality is of the utmost importance in order to accurately asses the performance of a vessel. A structured method for assessing the data collected by the performance monitoring is found and applied to the performance monitoring system as a verification. Data quality deficits such as the speed of the ETL processes, incorrect data blending and calculations are identified and corrected. This led to a near live, high quality data stream which can be used to asses and optimise the performance. Continual assessment and improvement of the data quality is recommended.
Suitable methods to analyse this data to create knowledge are determined. A form of hybrid modelling where simple theoretical models are fitted to the filtered data using regression is used to create baselines and give a clear overview of the effects of certain operational parameters on the performance of a vessel. These models can then also be used to increase the accuracy of tools such as the weather routing and voyage planning tool. Benchmarking between sister vessels or the baselines is seen as a good means to identify performance deficits. Visualising and analysing the data with the help of a BI tools is a good way to share the knowledge throughout the company.
The performance management in place at Spliethoff is assessed to form a baseline to improve upon. It became apparent that Spliethoff overall has a good idea how to optimise performance but it does not have the information or data needed to do so. Since there is no information about the gain in performance of certain tools they are not used correctly. Being able to show the performance gain from using these tools is an important benefit of the performance monitoring system. The communication and knowledge sharing throughout the company can also be improved with the use of the performance monitoring system. Poor follow up from upper management when performance deficits on top of this indicate that a lot of value can be created with an improved performance management plan which incorporates the performance monitoring system.
A new performance management plan based on ISO 50001 is proposed to realise this value. Due to the available data the management plan focuses on reducing fuel costs and optimising voyage planning.This is done by awareness creation through performance dashboards which also increase the information sharing between shore and vessel. A change in company culture to a more data based decision making and communicative culture is promoted and implemented through this plan.
To determine how much added value can be realised, the costs and value realisation potentials of the performance management system are specified. These are then used to determine the net present value of the performance management project for several scenarios. A large fleet and a small fleet implementation are researched. The total capital investment is either €543,000 when only the large consumers of the fleet are included (small fleet) or €1,310,000 when almost the entire fleet is included (large fleet). Only the direct monetary value is used to determine the net present value but indirect and non monetary values are also mentioned. The direct monetary value potentials are derived from operational cases where performance deficits have been identified. The resulting total added value (NPV) of the small fleet implementation ranges from €2,165,970 in a pessimistic scenario to €8,711,272 in an optimistic scenario after 11 years. €6,000,146 is the expected total added value realisation for the small fleet implementation after 11 years. For the large fleet the results are: €4,966,756 for the pessimistic scenario, €18,103,704 for the optimistic scenario and and expected added value of €12,805,994 after 12 years. Most scenarios have a pay back period of less than 2 years with the exception of the pessimistic scenario of the large fleet which has less than 3 years. All indirect and non monetary value is seen as a bonus on top of this meaning that there certainly is a lot of added value to be realised by implementing performance management which is supported by a performance monitoring system.
Buoyancy Lifting of Offshore Platform Jackets
Modelling the economic viability of early stage design concepts