Tummers Food Processing Solutions is an internationally operating company based in the Netherlands, that sells factory lines for processing tuberous products like potatoes. Before being processed into various products, the incoming tuber batches are always washed and cleaned from waste particles like clods, stones and haulm. For this purpose washing lines consisting out of different machines are used. Every processing application, customer and kind of input product results in different requirements regarding the machines, options and their configuration. Currently for every customer a tailor made machine line is designed, consisting out of customised machines based on the expertise of the corresponding sales agent and the engineer that designs the machines. This results in individually designed machines, friction between different departments and mistakes in drawings, parts lists, manufacturing, documentation and others. Once installed on site, the machine line is controlled by machine operators that keep the factory operational but are not optimising the performance and efficiency of the machine line nor conduct preventive maintenance. To tackle both the issues on the company and the customer side, the strategy for designing these tuber washing lines has to be turned into adaptive machine line design. Adaptive machine line design is a combination of modular design and smart factory engineering. Machine lines are customer specifically configured out of standardised modules and controlled by smart systems to optimize performance and efficiency and predict maintenance. Because potatoes are by far the most commonly processed product, followed up by carrots, this research focusses on potato washing lines with some specific side notes for processing carrots. Based on sales records and customer preferences, a set of standardised machine models and options is defined as the machine portfolio. This portfolio consists out of ten different machines, each available in different sizes, with waste and product streams to different directions and other standardised options. A jigsaw puzzle model can be made where this machine portfolio is build up as a set of puzzle pieces. For every different application a set of these puzzle pieces can be chosen from the portfolio and connected in different configurations. To determine which machines with which options to choose from the portfolio in which order, a model can be used. This model is based on a set of input- output relations and first set up as a decision scheme after which it is modeled in LabView as a basic machine line configurator. The model is then used to configure machine lines for five different examples. Each example is an existing order with differences in customer specific wishes, input and output characteristics and boundary conditions regarding factory layout and peripheral equipment. With help of these five examples the model is iteratively checked and improved after which the amount of customer specific engineering is determined that still needs to be performed after standardising of the machines. A first layer of a Digital Twin for smart control of the washing line is designed. This control strategy is based on the Key Performance Indicators of the washing line and their relations between them. Based on open or closed loop control, a set of control schemes is created for each machine that requires smart control. A thorough analysis of the costs and benefits of implementing a modular design strategy for the tuber washing lines shows that huge amounts of man hours can be saved after implementation. Next to these savings in labour, less mistakes will be made in the design and manufacturing of the machines which improves the professional image of the company and lowers friction between different departments and stress on the workfloor. Due to significant savings in replacing wear sensitive parts, reduced factory downtime, loss of product in waste streams and reduced operator wadges, installing a system for smart control can easily be earned back in the first year of operations. All and all changing the design strategy for tuber washing lines to adaptive machine line design is very promising for both the machine line manufacturer as for the customer.

An issue that arises during the execution of shipbuilding engineering projects at Royal IHC is an imbalance between the sum of all necessary engineering work, and all engineers that are employed who are available to execute the work. This research aims to develop a new method to help establish a proposal engineering work schedule forecast for all engineering work packages in custom trailing suction hopper shipbuilding projects at Royal IHC. To develop the input for the new method, regression analysis on usable historical engineering man-hour data was applied to develop models that quantify work, and curve fitting through the man-hour data was applied to develop models that determine the timing of work.

Heineken's goal with respect to safety is to reduce the number of accidents to zero. Such a drastic reduction can only be achieved by considering safety as early as in the design phase, when most impact can be made. Therefore, the purpose of this research is to enable the easy generation of different design concepts and evaluate them with regard to safety. Since most accidents currently occur in Heineken's warehouse loading areas, this is the area considered in this thesis. In order to evaluate the generated designs with respect to safety, safety has been quantified into a single value, the risk level. This risk level is the result of the possible consequence of an accident (the impact), the number of times an activity is expected to occur (the frequency) and the chance that this activity results in an accident (the probability). These values depend on the type of accident, or hazard, which is any unsafe condition or potential source of an undesirable event with potential for harm or damage. The hazards corresponding to the top three most occurring accidents have been identified and have been evaluated. For the generation and evaluation of design concepts, a parametric model has been developed. By changing parameters, designs with different operating processes, equipment types, layouts, and more, can quickly be generated and visualised for the designer. Also the movements that occur in the warehouse area can be simulated. The model counts the number of times a hazard occurs and determines the corresponding frequency score. The scores for the impact and probability are based on expert opinion. The risk level is subsequently calculated. Using the parametric model, the risk level resulting from the twelve most occurring hazards in the warehouse loading area of Heineken is evaluated for different scenarios. The findings show that the current method that is used to determine the frequency score is not suitable for activities that typically occur a lot, which is the case in the warehouse loading area. Therefore, an alternative method is proposed, which uses an exponential distribution to score the number of times that a hazard can occur. By analysing design choices regarding the type of picking process (directly from warehouse, using cross-docking or using pre-staging), the level of automation, the number of aisles, the distance between loading points and designing crossings on a different level, the preferred design choices are found.

The performance of a product is highly influenced by the users of the product. A Combined Performance Measurement Model of a Shared Rental Vehicle is created to analyse the influence of a user on the vehicle performance. A Performance Measurement model is created to analyse the performance of a Shared Rental Vehicle. User Profiling is used to create four user profile perspectives. These models are combined in a Combined Performance Measurement Model to analyse the relation. This Performance Measurement Model propose a shift in user population to gain optimal or target performance of the Shared Rental Vehicle.

In 20 years, from 1996 to 2016, global cumulative container port throughput had an average annual growth rate of 6.3%. Furthermore, the average global transshipment incidence increased from 11% in 1980 to a stable 27% in 2017. This change in transshipment market dynamics has led to opportunities for potential port investments or disinvestments. In this research, a tool is developed for Royal HaskoningDHV that improves transshipment forecasts. The developed tool calculates the optimal ports for transshipment, transshipment throughput volumes, fleet utilization, and optimal cost routes. This is done by means of minimizing the total transport costs, while meeting container demand requirements and port and vessel constraints. The most statistically significant factors affecting transshipment volumes are incorporated in the tool. By modifying input parameters, the tool facilitates calculations of optimal cost future transshipment port throughput volumes. This could provide key insights in lucrative port investment or disinvestment opportunities.

The present study was designed to gain a deeper understanding of RTI control and Supply Chain Coordination, with a specific focus on the practical challenges experienced in the reverse logistics by asset-owner and asset-users. A case study at EPS - an RTI owner - is performed and a practical problem has been addressed with a design science and TIL systems engineering approach. It was observed that a huge amount of deposit is allocated to a retailer's generic account. The current state analysis found that this problem is mainly due to inefficiency in the current identification process with physical SSCC labels. The design goal of minimising the "Delta" -the number of unidentifiable return packages- was defined. Ways to redesign the reverse logistics were determined with the aim that all return packages can be allocated to the retailer at shop level. Based on the future state requirements and the design goal, the concept of matchmaking is developed as a way to achieve the design goal. This thesis shows that a matchmaking system can improve the traceability of return packages and that it has the potential in bringing the Delta of return packages with missing shoplink to zero. The matchmaking system is defined as the framework that ensures matchmaking, which uses a "key" generated by the sender to represent the return package. If the receiver can find the key upon arrival of the return package at the depot, the sender can be identified. Seven matchmaking systems were considered. Five alternatives use unique tray identities as key. One alternative uses the load carrier as key and the last alternative uses the return package identity as key. The validation results show that an "all read" or "reading of all individual trays" is not a requisite for a working matchmaking system. By contrast, as long as a certain ratio of reading at two locations is reached, an all-read scenario can be mimicked. The assessment investigated the instances in which zero mismatch take place. Results show that the higher the data capture capability of both the sender and receiver, the higher the chance a match can take place and the smaller the chance of a mismatch. This thesis creates insights on requirements for enhancing traceability of RTI's in the return chain and developed a matchmaking concept that can address the practical problem of returns without traceability of shop origin. The developed matchmaking concept is the outcome of an analysis of the current state and makes use of data elements that are already being collected in the database, in the case of EPS. The study addresses how collected data can be leveraged for enhanced RTI management in the reverse logistics and may inspire practitioners to face challenges with a similar lean approach.

Prysmian Netherlands as a cable producer uses a cable drum to deliver products to their customers. However, these customers do not always participate in returning this returnable packaging material (RPM). Customer willingness and reverse supply chain (RSC) visibility are mentioned as the main contributors. The study aims to develop improvement strategies and assess their impacts through a discrete event simulation (DES). The strategies consider the approach from logistics system design, technological implementation, and compliance policy. The findings suggest that an RPM with a high product residual value such as drums promises a high financial return if recovered. However, maintaining the returned drum condition is of the utmost importance to ensure the recovery operations are fruitful. Moreover, a shorter RL cycle time does have a substantial effect on the RSC efficiency.

This paper deals with the food flow for intercontinental KLM flights. The aim of this research is to design a framework to optimize the processes of food assembly and subsequently apply the framework to increase the throughput time at the intercontinental department of KLM Catering Services. A discrete event simulation model is created to compare key performance indicators for different design alternatives. In this simulation model different amount of equipment is handled together with different settings for a robot. With the use of this simulation model a combination of design alternatives is proposed.

There is a significant historical link between maritime trade and economic activity. With the rapid growth of containerised trade over the past 60 years, a significant share of global trade is transported by container nowadays. This suggests there is a connection between container flows and economic activity. There is also a time delay between containers with goods being imported and the announcement of quarterly Gross Domestic Product numbers. With US container imports and exports being publicly available information, this leads to the research question of this thesis: Can loaded and/or empty container flows be used to predict economic activity?” If so, this could prove to be valuable information for economists, policy makers and, as this thesis highlights, professional traders working at investment banks or hedge funds. This thesis focusses on analysing transpacific containerised trade as a potential so-called forward indicator of US GDP. To measure these transpacific flows, an aggregate of US West coast port data is produced and de-seasonalised. The container flows are separated into Loaded In, Empty Out and Loaded Out flows. It is important to understand the dynamics of container trade and the variables influencing it on this route. Variables are identified that could possibly affect the supply-side of container shipping and therefore the transpacific container flows (the demand-side is seen as an expression of economic activity). After analysing the Cross Correlation Functions (CCF) of the identified, data based influencing variables, five different GDP growth prediction models are constructed. This is done by performing OLS single and multivariate regressions of the individual container flows (together with the influencing variables) on historical GDP growth data from 2000 to 2017. The resulting models are tested against an existing, commonly used forward indicator: the Purchasing Managers Index (PMI). The results show that three models, all using a form of loaded containers, outperform the PMI when predicting the direction of US GDP growth 3-months ahead over the 17-year time period of the dataset used. The probability of large prediction errors with these models are also smaller than the PMI benchmark model.

This Master Thesis document presents a research on trade-off analysis between security and efficiency factors during airport operations. Over the past few decades there has been an increase in security in the air transportation industry, with even more measures taken since 9/11. Besides affecting the operational costs of airports, the stricter controls also have been having an impact on the efficiency of the operations. Although that security and efficiency factors influence each other and on a frequent basis are being compared and considered in combination to take airport security operational decisions, the trade-offs made in order to take such decisions are not fully explicit. In order to make these security and efficiency trade-offs (which these decisions are based on) more explicit; a trade-off analysis formalized by Discrete Choice Modelling was conducted. Based on this analysis; implications were provided to evaluate, by the means of Agent-based Modelling, the effects of security and efficiency trade-offs made by airport security screeners on the operations of airports.

Traceability in complex ship design involves keeping track of the evolving relations between need, requirements and design. Such traceability is not fully developed in the current design process at DMO due to divisions in the design process and between design tools. This thesis proposes to use a single information model to facilitate traceability by connecting the need, requirements and design in a single database. Besides enabling traceability, such an information model can also be used to support modern modelling design tools. In the early design stage of naval vessels – the preliminary design phase – the capability, technical feasibility and affordability of a new ship are defined. Interactions between these three aspects are opaque and rely on the need for a new naval vessel and supporting requirements and preliminary design(s). Determining the need, requirements and design is in this thesis considered to be a ‘wicked problem’. In such problems, information gained by developing solutions helps define the problem itself. However, these solutions can only be determined with a certain interpretation of the initial problem. This results in many (evolving) interactions between the need, requirements and design in the ship design process as one is needed to define the other. With the help of Systems Engineering and Requirements Engineering information and relations in a ship design process can be determined and structured. These engineering fields are widely applied, and current technology enabled the development of computer aided approaches incorporating design theory, including computer aided traceability. One of the current developments in design approaches is the introduction of model-based approaches, which creates the possibility to actively manage more relations and interactions in the design process. Model based approaches such as the Design Structure Matrix are used to visualise relations between information, and Axiomatic Design enables the decomposition and creation of complex relations. A different approach to modelling in design processes is the use of Knowledge Based Engineering. Knowledge Based Engineering field aims to capture not only the relations and interactions between information in design processes, but also ‘knowledge’ about the ‘how’ and ‘why’ in these processes. Each of these model-based developments relies on, or enables, traceability of information. However, having a program capable of supporting an information storage to support these approaches remains difficult to achieve. For this purpose, Shipbuilder software was created to support transparent storage and management of information. In this thesis, theories for modelling approaches, Systems and Requirements Engineering and the DMO design process have been combined. This resulted in one information structure, applied in the Shipbuilder application, which enables traceability. To show that the proposed information model can model a ship and supports traceability, a case study has been performed. A small model of both an S- and L-frigate has been created to show how traceability can be performed in this information model.

To support Van Oord’s path towards a low-emission future fleet, this thesis has focused on the technical, environmental and economic impact of a methanol hybrid power plant design for new-build offshore working vessels (OWVs). These Dynamic-Positioning (DP) vessels are known for their large and dynamic power plants and have to limit their NOx emissions in order to comply with IMO Tier III regulation. The research objective has been to assess the cost-effectiveness of a methanol hybrid power plant solution to reduce CO2 emissions of new-build OWVs relative to other alternative fuel options. As alternative fuels, both bio-diesel and ammonia have been selected as benchmark options. Two models have been developed to find the cost-effectiveness of the methanol and benchmark power plant solutions to reduce CO2 emissions. These models are a power plant model (PPM) and a cost assessment model (CAM). The PPM consists of an engine model, a battery model and a power management model. For a specific engine type, the engine model determines the fuel consumption and emissions performance by using available engine data. Next, based on the principle of equal energy consumption and relative fuel characteristics, these fuel consumption and emission performance are adapted in order to represent methanol or one of the benchmark fuels in the selected engine type. The battery model is established in line with DP hybrid power plant requirements and the power management model acts as a connecting link to bring the engine model and battery model together on a power level. The CAM uses the PPM output to find the relationship between costs and CO2 reduction for each power plant solution. This is done by comparing the annualized Total Costs of Ownership (TCO) and the Life-Cycle (LCA) CO2 emissions of each solution with a diesel-based configuration. In this comparison, the annualized TCO consists of the yearly operational costs and annualized investments costs of each solution. The life-cycle emissions account for both well-to-tank (WTT) and tank-to-propeller (TTP) emissions of each fuel type. A case study considering the Bravenes, a flexible fallpipe vessel within the fleet of Van Oord, has been carried out to bring the developed models into practice and to provide a solution to the research objective. The technical details of this vessel have been used to create the methanol and benchmark power plant solutions which comply with both IMO Tier III and DP regulations. Next, a representative load profile of the vessel has been applied to simulate the performance of the different power plant solution for a duration of one year. Based on these simulation results, it has been found that the methanol solution has a CO2 reduction potential up to 99% and a CO2 price of 78 euro per ton CO2 reduction. This means that methanol is most cost-effective in comparison to both the bio-diesel and ammonia power plant solutions. Relative to methanol, the battery has a similar CO2 price of 79 [euro/ton CO2], but has a CO2 reduction potential of 8.5% only. To motivate Van Oord to invest in a methanol hybrid power plant solution for new-build OWVs, external or internal incentives are required to bridge the CO2 price gap between the methanol hybrid solution and a diesel-based configuration. As external incentives, the expected CO2 tax and / or subsidy for the use of advanced fuels are particularly interesting to consider for new-build investment decision in 2021 and beyond.

The aviation Maintenance, Repair and Overhaul (MRO) industry faces an enormous growth due to the increasing air traffic. To accommodate this growth and increase efficiencies of processes it is required to increase the transparency of demand in the Supply Chain (SC). Research into predicting demand in the MRO industry have mainly been focused on the spare part request (forward logistics). This results in a research gap regarding increasing transparency in the reverse SC. This paper investigates an approach to increase transparency in demand by prediction the arrival times of shipments in the reverse SC based on transport times. The transport times from two customers have been collected and analysed. The analysis showed the presence of different transport behaviour depending on the process which included inefficiencies and waste. Based on the analyses different methods to predict the transport time have been formulated and evaluated. The results show two methods superior to the others which are the median and decision tree. Furthermore, the research indicates the accuracy of predictions increases with more available data and stable processes. The results show to be insufficient to accurately predict the majority of the shipments and therefore require further research.

This study aims to develop a decision support tool which enables shipowners to select the most appropriate alternative fuel technology to comply with possible different imposed emission regulations while ensuring optimal business performance. In this context, most appropriate is defined as a fuel alternative which minimises required freight rate (RFR) while maximising overall performance on technological, environmental and other criteria. A decision support tool was devised combining a decision model based on the simple multi-attribute rating technique (SMART) with a financial model based on discounted cash-flow (DCF). Additionally, an optimisation model was implemented to optimise for minimal required freight rate through slow steaming. The decision tool provides shipowners with a quantified impact on their current business if they do not transition to alternative fuels under a 'market based measure' (MBM) regulatory scenario, as well as best-alternatives if their current fuels do not meet regulations under an 'emission cap' (EC) scenario. The decision tool is evaluated under optimistic, average and pessimistic scenarios in 2020, 2030 and 2050. Under an emission cap scenario, the results showed an overall preference for Fischer-Tropsch diesel (FTD) as the most promising alternative maritime fuel both in terms of SMART performance and required freight rate, followed by upgraded bio-oil (UBO). Nevertheless, the average difference in required freight rate of alternative fuels compared to HFO remains substantial, at 43% and 38% higher for Fischer-Tropsch diesel under a 'no regulation' scenario and 'market based measures' scenario, respectively. It is therefore evident that without regulatory intervention, heavy fuel oil is expected to retain dominance based on cost. Even under a market based measure (MBM) scenario, the average required freight rate of HFO increases only by 3.4% overall. For LNG, market-based measures lead to an average increase in RFR of 4.1%. These results suggest that in order for the maritime industry to transition towards sustainable alternative fuels, policymakers, governments, international organisations and lenders need to align their policies to collectively enable a more sustainable shipping industry - not only by enforcing stricter regulations, but also by providing the correct financial incentives.

A design framework for the initial design of a Shop Floor Planning and Control (SFPC)system for a Maintenance, Repair & Overhaul (MRO) component supply chain has beendeveloped. It combines proven design methods developed for the control challenges presentfor MRO processes and introduces an information requirement mapping that reaches beyondthe control boundary of the SFPC system. This is achieved by integrating these with thedesign criteria for current methods for production control design. The goal was to develop adeployable production control system in the component MRO organization.The study developed the criteria for an information integrated production control by exploringa generic MRO process control function and concluded that information must be regarded anintegrated part of the control design as it drives this process and stretches from supply chainlevel, down to the shop floor. The criteria are detailed with specific information requirementsof the process. System robustness and stability must be considered when evaluating thesecriteria and deal with the lack of validated design data in the initial design phase.The framework is developed for exploration of information quality and dependencies of theprocess. It calls for graphical representation of the logistic and information flows of theprocess, before configuring the entire production control with known methods. With theselected production control configuration, the control driving information can be characterizedand improved for robust and stable parameter design, using Taguchi’s approach.In a case study valid and functional designs were generated for production control systems ingeneral. These could, however not be deployed directly due to the lack of a validated modelfor the specific performance environment. Robust and stabilizing potential are significant butalso revealed a negative correlation.The study demonstrates the importance of information modelling within complex productionsystems. It presents a structure for information requirement integration into control designof control layers. It is recommended that the framework is subjected to validation studies forspecific environments. With a development such as Industry 4.0, control in component MROsupply chains should make use of an integrated approaches over the different control layers.

This research aims to determine the cost effectiveness of yacht emission reducing ret options through marginal abatement cost curves. A broad selection of five refit options is evaluated and implemented in the created tool. Using multiple scenarios by fluctuating fuel price and the implementation of hydrotreated vegetable oil (HVO), the effect of fuel price and type is evaluated on multiple ship lengths. The abatements are determined in global warming potential and external cost, as well the well to wake emissions of the fuels and refitted parts. A technology overview, implementation and capitol and operational cost overview is made of the implementation of solar panels, LED lights, SCR-units, cool water waste heat recovery systems and anti-fouling. It was found that a GWP reduction of 78% and external costs reduction of 70 % is possible at an increase of fuel consumption cost of 47 % for a 54 meter yacht. In this case the main contributing factor to GWP reduction is HVO and the main external cost decrease is due to the NOx removal of the SCR-unit. Furthermore increased cost effectiveness was seen at increased fuel prices.

Due to complex nature of aircraft heavy maintenance checks, achieving process stability is difficult. Literature suggests that this stability can be obtained by separating routine and non-routine work, and focusing on quick identification of non-routine tasks by completing inspection tasks early in the check. Current task planning methods show limitations in producing a feasible task planning, motivating the need for an advanced task planning model. This model combines the task elements of manpower, work order, and aircraft zone to find the minimum TAT given the task complexity-based heuristic. For this model, aircraft zones have been redefined, as the zones specified by Boeing are not suitable for task planning. An experiment using the advanced task planning model is conducted for the Inspection Phase tasks of the Boeing 777 C07 check. The target is to complete all tasks in 48 hours. Results show that it is feasible to perform all Inspection Phase tasks in 61.28 hours, where 99.51% of the tasks is completed in 48 hours. Completing all tasks takes 8 shifts, with a maximum of 31 technicians in a shift. The total TAT can be further reduced by identifying and lifting the constraints in the planning. One example shows how this can lead to an 8 hour reduction in total TAT for the best experiment scenario, bringing the TAT closer to the 48-hour goal. This demonstrates how the advanced task planning method can be used to stabilise aircraft heavy maintenance.

Within aircraft component MRO industry, companies providing availability contracts are challenged by inherently unpredictable demand patterns and complex time crucial operations. Most prevailing academic literature within the MRO industry has focused on availability models or operations management in repair shops in the past. This study focuses on one of the most critical, and often neglected parts of the MRO supply chain. The reverse logistic flow of aircraft components. A research methodology was constructed by integrating the adapted DMADE (Define, Measure, Analyse, Design, Evaluate) structure from Lean Six Sigma and a number of different business process improvement methodologies from the literature in combination with a simulation study. The aim of the study is to identify a methodology with practical design criteria on how to redesign the reverse logistical processes of a component MRO provider, in order to improve the performance from an integral supply chain perspective. For this purpose a case study is performed and the current state of the closed loop supply chain of KLM E&M was measured and analysed. By analysing this current state, design criteria for redesign are determined. A new automated logistic handling area is introduced by separating the physical and administrative handling operations. The proposed redesign is evaluated using discrete event simulation. Through optimisation modelling the optimal balance between inventory, resources and time required to handle the volatile demand pattern to achieve a desired service level, is determined. By optimising the capacity in handling the total time in the supply chain can be shortened. The redesign was evaluated using different levels of proactive repair order creation and skill configurations. Results from the case study showed the relationship between process efficiency, available capacity in terms of manpower, inventory, service level, and handling time. By separating the physical from the administrative flow, reducing handovers and transactions, generating repair orders in advance and shifting from inventory buffers to capacity buffers the reverse logistic flow of component MRO providers can be drastically improved.

The global temperature is rising as a consequence of the climate change. In order to stop the further increase of the global temperature, the international community has decided to aim at reducing global greenhouse gas (GHG) emissions in the near future. To achieve this ambition, various alternatives in shipping need to be explored including sailing on alternative fuels. This study investigates the consequences of sailing on alternative fuels. It is investigated which problems might occur when sailing on alternative fuels, which rules are mandatory when sailing on alternative fuels and as a consequence what the effects are on the cargo transport costs. The problems occurring when sailing on alternative fuels are caused by the lower energy densities of these fuels, the rules and requirements with regard to the storage of some of these fuels and the shape of the storage tanks for some specific fuels. The shape and requirements regarding the fuel storage tanks can make it necessary to replace cargo for storage tanks, which will result in increased transports costs. Furthermore, the lower energy density of alternative fuels result in more fuel weight, or volume as compared to conventional fuels. In order to transport the same amount of cargo, an extra bunker stop, or taking less fuel and reducing the sailing speed, can be an option. Another option to compensate for the increased weight, or volume of the alternative fuels, is to reduce the cargo taken on board. All options will result in higher transports costs as compared to sailing on conventional fuels. To investigate how these extra costs are composed a main question has been formulated: "In a situation where the transport costs are minimized, how do the transport costs compare when sailing on various fuels with different energy densities than conventional fuels?". To answer this main question, a model was developed. The model is suitable to calculate the transport costs in various situations. For this research, three vessel types on three operations, using seven fuel types have been analyzed. The analyzed vessels were a container vessel, an oil tanker and an ore carrier. The chosen voyages are common voyages. The analyzed fuels are fuels which are able to achieve the goal of reducing the CO2 emission with 70% per transport work in 2050 as compared to 2008. Heavy fuel oil was used as benchmark. Based on the simulations used in the developed model it was found that: the costs of alternative fuels are higher than those of conventional fuels. Batteries are too heavy, too large and too expensive to be considered as an option, for the researched vessels and operations. The capital costs of fuel cells make that the use of fuels in combination with a fuel cell is currently expensive at higher speeds. High fuel storage costs make hydrogen currently not competitive with conventional fuels. The transport using an oil tanker are the lowest for hydrotreated vegetable oil, second lowest for ammonia in combination with an internal combustion engine and the highest for battery electric.

Nowadays many companies still conceive their logistic operations as a simple material replenishment of the production plants and do not invest money and time in projects to structure their Supply Chain and bring more eciency to the production process. In addition, the high complexity of the automotive industry and the emerging uncertainties that are characterizing a more globalized, dynamic and interconnected world give companies a huge incentive to research and innovate the management of their supplier network. Over the last years, businesses have experienced several issues along their logistic flows. Unexpected events such as the pandemic and the semiconductor crisis have put companies in research for solutions that look to improve and strengthen the partnership with their suppliers. Digitization represents one of the most innovative and disruptive challenges in today’s Supply Chains. Indeed, the increasing amount of data retrievable from logistic and production processes today is yet not exploited enough in comparison with its potential benefits. Companies still work by silos and prefer to hide their information rather than sharing them with their partners. In this research paper, the role of data visibility is put under attention, in order to demonstrate its practical benefits in a complex automotive Supply Chain. By collaborating with Ferrari on a Supplier Relationship Management (SRM) project, this research presents the design of a Supply Chain control tower through Model Predictive Control. By simulating a MPC optimization model on a small part of Ferrari’s supplier network, the coordination, eciency and sustainability of the Supply Chain are assessed through a comparison with the current state and by evaluating the network’s performances in di↵erent logistic scenarios. Although this solution is presented as a decision-support tool, it is thought as a key technology for the future development of autonomous Supply Chain operations.