A traceability system for primary packaging materials is compulsory by law for the food- and beverage industry. With a good traceability system an organisation is able to quickly recall unsafe products to protect consumers health. This research aims to analyse and improve the traceability of the primary packaging materials at Heineken Netherlands. A second focus of this paper is to reduce the impact of a potential recall on packaging materials. This research is performed based on the method called the five-stage-of-a-prescriptive-model. Using this model results in a step-wise development of an improved design. A literature study, a problem analysis and the customer requirements will be the input of this design. Analysing the current traceability systems showed traceability issues as unregistered in- and outgoing flows of packaging materials at pallet level and registration issues as double scanning. Another issue that is observed is lot segregation at different breweries, at different production lines and on different production dates. The lot segregation will cause that in times of a recall an organisation has to withdraw significantly more products. Using a Multi Criteria Analysis and the Ease and effect method results in a final design based on organisational changes, periodic evaluations, barcode technology and RFID technology. Implementing this design guarantees the traceability since all the incoming and outgoing flows are registered at pallet level and the registered data is periodically evaluated. By procedure adjustments at the supplier and at Heineken also results that the impact of the recall volume can be reduced.

Ballast water, routinely taken on by ships for stability and structural integrity can contain thousands of mi- crobes, algae and animals. When discharging this ballast water holding these organisms in a non-native ecosystem, new invasive aquatic species can be introduced. This can have to devastating consequences for the local ecosystem. To prevent further disruption of different ecosystems across the globe, the Ballast Water Management Convention (BWM) was adopted by the IMO in 2004. NIBC has a wide portfolio of vessels which will have to comply with the IMO BWM convention. However, the possible solutions and the actual impact of this regulation is still unknown to the bank. Ship owners expect a significant impact on the shipping industry and it is suggested that a lot of vessels will have to be scrapped due to the high investment cost. This research is conducted for ship owners and banks and will reveal the actual impact of the BWM convention. This is realised by calculating the impact on the internal rate of return (IRR) for each specific vessel. It provides the bank with a tool to monitor what effect the BWM convention will have on their clients. In addition, the tool is able to identify high risk vessels with an internal rate of return below 9%.

The Haga hospital in The Hague demands a more structured approach for their patient planning in outpatient clinics. Five clinics have been observed and analysed using the Delft Systems Approach and system requirements were established using three main stakeholders: Patient, Doctor and Hospital. Main conclusion is that current coordination lacks for many requirements; the main focus lies on financial-, not service parameters. A control structure is proposed considering all system requirements. The structure consists of new KPI’s and standards, and a number of interventions for every clinic that allow for more accurate KPI steering. An MCDA is used to determine the preferred planning strategy, and a simulation tool is added to assist clinic managers in making ground schedules

Autonomous sailing is considered by many to be the next big thing in the shipping sector. Many companies, including Rolls Royce and DNV are investing heavily in research that helps in the development of autonomous shipping. Most research is currently being done regarding autonomous navigation, communication and cyber security. What is often neglected in these studies is the need for maintenance within the engine room. With all ships having multiple crew members solely dedicated to keep the engine room going, their absence will have a big impact on the design of engine rooms. This paper aims to find what equipment will become a weak point in engine rooms once these are no longer occupied and maintained by crew members, and how these weak points can be eliminated. With the absence of reliability data that corrects for maintenance and crew interference, this paper tries to find these weak points by analysing crew member behaviour. It is assumed that if a crew members spends more time on equipment, or deals with it more frequently, then that piece of equipment is less reliable. In order to find what equipment can be seen as a weak point, a redundancy reduced risk index was created. This index is a combination of the frequency index, which states how often engineers spend time on equipment, the severity index, which lists the consequences of failure for equipment, and the redundancy index, which is dependent on the level of redundancy of components. The redundancy reduced risk index is split into three levels: low, medium, and high risk. Medium and high-risk components were considered weak points, while low risk components were not. For all high risk and for most medium risk components, solutions were generated which will reduce the risk index of the components or system overall. For some components, the risk was deemed acceptable, as any solutions would be too costly to justify the risk reduction. Solutions were split into two categories: specific solutions, which were all catered to specific components, and a bulk solution, which was the installation of a second drive train. A second drive train would include a second main engine, gearbox, propeller and rudder. With the solutions found, the two categories were subjected to a financial analysis to see if they are commercially viable. The solutions were applied to ships of four different sizes, ranging from a 6,000 GT feeder to an 85,000 GT capesize bulk carrier. For these ships, the OPEX were calculated and divided into four categories: Operational costs, fuel costs, capital costs and crew costs. The initial investment for the machinery plant was also calculated. This was the basis to finding the increased cost for solutions found in this paper. Using these specific solutions, the machinery plants will become roughly 50% more expensive, while adding a second drive train will increase the machinery cost by 110%. It is assumed that these solutions will eliminate the need for a crew and therefore eliminate all crew costs. Using these figures, it was found that the specific solutions will lead to a potential yearly savings of $600,000.– for all ship sizes, and adding a second drive train will lead to a potential yearly savings of $500,000 – for the small ship and $163,000.– for the larger ships. With both the specific solutions and the second drive train, the machinery plant is deemed reliable enough for continuously unmanned operation, which proves the technical feasibility of continuously unmanned engine rooms.

As a consequence of globalization and developing economies becoming more mature, airports face increasing passenger numbers. It is the case that large airports are energy intensive buildings with an electricity consumption ranging between 100 - 300 GWh anually. Within ATBs (Airport Terminal Buildings) the BHS (Baggage Handling System) is categorized as a high energy consuming system. As for the BHS, conveying equipment is the main consumer of energy (55% to 70%). From the perspective of a designer it is very hard to predict energy consumption in evaluation of conceptual designs and therefore energy consumption is often not given the attention it deserves at this stage of design due to the fact that baggage handling performance is dependent on many dependent variables and dynamically changing demands. As a consequence the use of dynamical models is necessary. In this research a generic simulation model has been created to investigate energy consumption. The applicability of the model has been tested on two conceptual design lay outs.

The Heineken supply chain goes from the production units, through local distribution centers, to the wholesale and retail customers in the market. Heineken Netherlands Supply is interested in bypassing the distribution center in Germany when possible. It is expected that these so-called direct deliveries have the potential to save on transport-, handling- and storage costs. A system analysis defined the Direct Delivery model, and showed that there are sixteen future scenarios, based on choices for the contacting party, supply model, degree of pallet handling and carrier party. All sixteen scenarios were evaluated against several qualitative impact parameters, i.e. customer satisfaction, order complexity, warehouse complexity, and carrier performance. Also a case study was performed to calculate the quantitative impact parameters, i.e. supply chain costs. It was found that the supply chain cost savings are marginal, and that none of the sixteen scenarios have no expected decrease in quality. More detailed case studies are required to determine direct delivery feasibility.

The growing pressure on tank storage terminals is pushing the terminals to find ways to accommodate more vessels by increasing the efficiency of the vessel handling process. This research looks at the possibility of implementing forward planning at such a terminal by simulating multiple strategies and testing the impact on the seaside performance of the terminal. The current process is a reactive one due to the first come first serve rule that is enforced. This causes an unpredictable arrival distribution of vessels and a low level of information and collaboration. The simulation results are promising and show that a proactive planning strategy could drastically increase terminal seaside performance by allowing the terminal to control vessel arrival distributions and preventing certain interrupts that often occur within the process. In the best case, the terminal seaside performance increased from the current state performance of 55% to 92%.

This thesis contains the model development of a simulation model, to aid the selection of a heavy lift vessel for a North Sea decommissioning project. The model considers fixed steel platforms with maximum topside weight of 1.400 [tons].

To plot the roadmap for the oil & gas sector, it is essential to do the market demand analysis and research the influencing mechanism of oil price on the offshore projects market and offshore equipment market. The equipment market of IHC IQIP is primarily the market of offshore structures installation. This project is combing the technology research and the market research of offshore installation equipment.

Problem statement - Damen Shipyards (Damen) wants to use Big Data analysis to gain new market insights and forecast vessel demand. These insights are valuable because Damen keeps standardised vessels in stock in order to significantly reduce delivery times. This concept gives Damen a competitive advantage, but is not without risk since they must speculatively build vessels beforehand. As a case, Damen wants to improve the current forecasting methods for the thriving offshore wind market - for which they supply vessels - based on data derived from the Automatic Identification System (AIS). AIS data includes among others information about identification, location, speed, date and time of approximately 200.000 vessels worldwide. Made Smart Group (MSG) is an information service provider specialised in nautical information, and maintains the world’s largest AIS database. MSG and Damen joined forces for this research. Objective - The objective of this research is to determine if and how Big Data analysis can be used to model (future) demand for Crew Transfer Vessels (CTV) being used for Crew Transfer Operations (CTO) in the offshore wind industry. Methodology - Almost 45 million AIS location reports of 39 CTVs servicing 263 turbines in 3 offshore wind farms throughout 2016 are analysed to derive key figures of the executed CTOs. Key figures are e.g. the weather window, and the number of executed CTOs per hour. The CTV demand is modelled based on these key figures, and three wind farm specific input parameters: number of turbines, distance between wind farm and port, and the sea state distribution. Results - The CTO demand of the 263 analysed wind turbines was on average 113 per year in 2016. This average CTO demand has a variation of almost 50% between turbine types. With an accuracy of 4%, it is modelled that a yearly average of 12.4 CTVs are needed to service these 263 turbines. Furthermore, the CTV demand decreases on average with 11% in the three analysed wind farms if the CTO limit can be increased from 1.5 m to 2.0 m mean significant wave height. This result in a potential cost saving around € 5.1 million on a yearly basis for these three wind farms alone. Implications - AIS data can be used to model vessel demand and gain insight into the market size. The accuracy of the developed model can be improved by adding: more wind farm specific variables; and/ or data of more CTVs/ wind farms. The gained knowledge about using Big Data analysis to forecast the CTV market size is useful and important for the introduction and future development of commercial AIS based data analysis. Furthermore, it provides insights into the operational profile of CTVs. This can be used to develop better vessels, better service the market and ultimately help to lower the cost price of offshore wind energy. It is believed that the maritime sector could profit from AIS data analysis.

Amsterdam UMC is an academic hospital where high level research is applied in practice. One of the outpatient clinics of location VUmc is the radiotherapy department. Radiotherapy utilises X-ray radiation to damage cancer cells. During their treatment period, cancer patients visit the department once a day to receive a radiotherapy treatment. Before the radiotherapy treatment can start an extended preparation process is executed. Improving the patient order flow in the radiotherapy preparation process is the subject of this research. The preparation process is a complex process: Many different process steps are necessary to prepare the radiotherapy of a patient. Due to the presence of a waiting queue before each of the process steps, the flow is restricted and errors occur in the corresponding information flow. Often, the reason is the limited insight in the other process step. No overarching control is available to control the flow between the different sections. Interventions occur, but does not rely on organized control structure. The available control is only taking into account the own process step. The fact that the radiotherapy department is too much functionally organised is the main reason for the existence of these problems. The functional design is a requirement for the radiotherapy system. However, within the outline of the functional design, improvements are possible. These improvements have to create an improved flow of patients with a transparent and coordinated execution. The main solution for the problem is the design of control structure based on the matrix organisation theory. The functional control structure remains and a patient order control structure is designed. The functional control structure is elaborated by the measure of the length of the waiting queue of the previous process step. The patient order control structure controls the flow of the patient orders throughout the preparation process. This control is executed on the basis of the date of the start of the radiotherapy treatment. The start of the radiotherapy treatment is the end of the preparation process. This date is determined earlier in the process and the different process step due times will be adapted according to that date. ewline The solution is able to improve the transparency in the department. The patient order progress is monitored during the preparation process and the different process steps will have more insight in the upcoming flow. Especially the patient order control structure is able to coordinate the flow based on the determining of the date of the start of the treatment in an earlier phase. For the examination of the effect of the proposed patient order control structure, a simulation model is built. The simulation model shows the positive effect on the flow of the patient orders through the department: The variation in the waiting queue length is reduced, the variation in the process time is reduced and the variation in the number of patients who will start their treatment on a certain day is reduced.

This paper discusses improving the Customer Service & Logistics department, CS&L, at Heineken Zoeterwoude. An analyses is made of CS&L, leading to the conclusion that there is a lack of real-time information from the packaging department. A proposed solution is to create a delivery overview for the operators, which displays the upcoming an ongoing deliveries. This enables the operators to schedule the task of loading of containers by supplying real-time information from packaging. A simulation test the effect of the proposed solution. Concluding that the proposed overview has a positive effect on the performance of the system. However it also identifies hurdles in creating the overview in practise, as the needed information is not present

The last decade has marked a rapid and significant growth of the global market of warehouse automation. The biggest challenge lies in the identification and handling of foreign objects. The aim of this research is to investigate whether a usable relation exist between object features such as size or shape, and barcode location, that can be used to robustly identify objects in a bin. A deep convolutional neural network (CNN) is built in MATLAB and trained on a labeled dataset of thousand product images from various perspectives, to determine on which surface of a product the barcode lies. Training results show that while the training set accuracy reaches 100%, a maximum validation accuracy of only 45% is achieved. A larger dataset is required to reduce overfitting and increase the validation accuracy. When sufficient classification accuracies are reached, smart picking strategies can be implemented to efficiently handle products.

There is a never-ending quest to search for better ways of planning and controlling projects. Currently the majority of all projects are planned with the critical path method and controlled using earned value management. This way of planning and controlling projects has been used for decades now and can be seen as traditional project management (PM). This current PM paradigm does not work well enough for one-off projects. Risk assessment and risk management are not sufficiently covered in most standard PM methods. This thesis looks at the potential of critical chain project management (CCPM) in combination with extensive risk management techniques for improving project performance. The thesis will cover the development of a risk-based critical chain project management (RCCPM) methodology and its application to case studies at a shipyard. The study concludes that RCCPM is a viable alternative for traditional PM in the maritime industry. Improvements include, amongst others, a reduction of the lead-time, more effective monitoring and controlling, and improved dealing with risks and uncertainties.

Several different kinds of Miracoli Dinner kits are produced on Line 4 in Oud-Beijerland. The current method of planning of production is not sufficient in terms of product availability and planning nervousness. A new method of Most-Urgent-First planning is proposed and a simulation is run to measure the performance in order to see if another method of planning is preferable.

The production system is redesigned to cope with the increase in cake handling. The Delft Systems Approach is used to analyse and design the functions of the cocoa processor. Silo design principles are used to design the mass flow cake silos for the process. The redesigned production system is capable of increasing the powder output to meet the future demand of powder.

Digital platforms are on the rise and have affected strategic conduct and market structure in industries. The impact of digital platforms on the heavy lift shipping industry is not clear to Jumbo and they, as a supplier in this industry, need a digital strategy in order to seize the new opportunities and to defend their position against the threats in their industry that are driven by digital platforms. This research provides a strategic advice to Jumbo, by the analysis of the impact of digital platforms on the heavy lift shipping industry and by addressing the opportunities and threats to Jumbo based on their position in the by digital platforms affected market space. A framework is developed by literature research into the impact of digital platforms on industries that can be applied to the heavy lift shipping industry. The market structure and strategic conduct in the heavy lift shipping industry are explored by a market analysis and Jumbo's strategy and performance in the industry are explored by a company analysis. The types, value adding processes, effects and strategic implications of digital platform in the heavy lift shipping industry are addressed by the application of the framework to the market characteristics from the market analysis. The meaning of digital platforms to Jumbo is deduced from Jumbo's position in the heavy lift shipping industry and their potential approach. Strategic options for Jumbo are developed and assessed and finally a strategic advice is provided to Jumbo.

Within this research the impact of system configurations is examined for a parcel sorting system. Currently, the impact of the configurations on the performance is currently unknown while no performance analysis exists which includes the whole system configuration with the expected parcel characteristics. Therefore, this research firstly involves a system analysis with the functional limitations. Hereupon, a simulation model has been developed obtain insight in the impact of the system configuration on the performance.