City logistics has changed fundamentally since the 1990s, driven by digitization, changing customer demands, and the urgency of environmental protection. Earlier approaches such as freight distribution centers could not cope with the challenges, leading to new concepts.

This presentation analyzes the changes in city logistics and examines why earlier approaches such as freight distribution centers failed. It highlights current conditions, including the impact of urbanization and changing consumer behavior. Furthermore, it introduces a transfer roadmap - a strategic instrument to help companies implement multi-level logistics networks including sustainable transportation. The roadmap aims to minimize risks and ensure the success of city logistics solutions.

With a focus on practical examples and best practices, this paper will highlight the relevance of city logistics in today's environment and provide approaches to how companies can effectively respond to the changing climate. The presentation at the conference will offer the opportunity to share key insights and experiences in the field of city logistics and to work together on sustainable solutions to urban freight transport problems.

Due to the required reduction of emissions, modern mobility concepts are rapidly evolving. Ridepooling is one of these concepts. Beside the reduction of emissions due to electric vehicles, ridepooling services promise to reduce traffic due to pooling and to increase mobility access especially in suburban areas. In practice, ridepooling services receive customer orders dynamically and thus have to integrate them in the vehicles’ tours. In this talk, we discuss an efficient procedure to insert new customer requests into given tours while incorporating possible future customers with the objective to serve as many customer requests as possible over the time horizon.

The aviation sector employs innovative technical involvements, applications, and operational practices. As a result, unmanned aerial vehicles that are remotely piloted from a ground station usher in the next phase of both passenger and freight transportation. This study is focused on freight transportation using drones. Although many studies in the past have focused on various drone delivery configurations, this study finds a critical research gap when evaluating the drone port location problem for a set of centralized ports where service is shared among multiple demand generators. Addressing the research gap, this study adapts the approach of continuous approximation (CA) in model development to find the optimum area allocated to a centralized drone port in an urban area. Findings indicate that the drone service range is a limiting factor for the optimal service area of the drone port. Furthermore, it was revealed that the optimal service area and the minimum total delivery operation cost have a low sensitivity to factors such as the shape of the service area, demand density and travel cost per unit distance.

Vans, cargo bikes, or even autonomous delivery vehicles are used in urban parcel delivery. A fleet consisting of these vehicles is called heterogeneous, differing in several technological dimensions including speed, range, as well as the impact on the delivery process. This research analyzes the operations of such a heterogeneous fleet in express urban parcel delivery. The heterogeneous vehicles are assigned to serve dynamically requesting customers within a delivery promise. We propose and analyze the strengths and weaknesses of selected policies assigning heterogeneous vehicles to serve customer requests in delivery districts with differing characteristics.

Heavy-duty battery electric commercial vehicles may be limited to short routes without a secondary power source. Therefore, concepts for commercial vehicles with fuel cell range extenders have been proposed. This paper presents an agent-based supply chain GIS model developed to simulate urban and regional freight distribution employing fleets of electric trucks equipped with fuel cell range extenders. The model was implemented in AnyLogic to simulate the transport of goods from regional distributors to urban stores. It solves a vehicle routing problem and identifies optimised routes by running a simulated annealing algorithm complemented by several heuristic methods. This model was used to optimise vehicle concepts for a particular freight distribution task. A reduction in battery capacity minimised costs directly related to the vehicles, whereas an increase in both battery and load capacity minimised fleet size. Additional power generation in the range extenders compensated for the reduction of battery capacity.

Resilience of critical infrastructure such as road networks is crucial to maintain provision of essential logistics services even and especially during disruptive events. This paper proposes a new method for assessing the resilience of urban road networks using shortest path analysis. The method is based on representative routes which connect selected Points of Interest with service providers. By comparing reachability and shortest path lengths for these routes in an intact road network with those in a compromised network, weakly connected areas are detected and the overall network resilience against the respective disruption analysed. To that end, the paper proposes the Robustness of Accessibil- ity index as a novel score for the resilience of critical infrastructure. To demonstrate the proposed method, a case study of flooding in Trier, Germany, provides insights into the vulnerability of the city’s road network in terms of potential response delays in emergency logistics. Such an analysis can help policymakers and planners improve the robustness and reliability of critical infrastructure and logistics processes.

Digitalization is playing an increasingly important role in the infor-mation flow of today’s supply chains. In particular, in logistics, the adoption of digital technologies such as the Internet of Things, cloud computing, block-chain, or machine learning offers the potential to increase data availability and quality. Using inter-organizational communication systems, private and public stakeholders can integrate their information flows. Within this paper, we ana-lyze with transport planning, tracking, and cargo monitoring three use cases for the adoption of decentralized systems focusing on maritime logistics. For this purpose, a software artifact was developed using the Design Science Research (DSR) approach. During the development process, four central design princi-ples could be identified: user orientation, interoperability, data security, and de-centralization. Based on these principles, a concept was developed for a decen-tralized information system that contributes to further automation and standard-ization of the information flow, while considering requirements such as confi-dentiality, neutrality, and accessibility.

The prediction of accurate vessel arrival times is essential and challenging at the same time to plan vessel arrivals with sufficient accuracy, coordinate berthing manoeuvres and monitor ship traffic efficiently. This paper investigates a new approach by using clusters consisting of deep artificial neural networks (DNNC). For this purpose, the considered coverage area of the Weser river was divided into geospatial domains. An also developed linear regression model (LNNC) served as a reference model, which was generated analogously to the machine learning approach on the clusters.

The estimated time of arrival prediction was evaluated at a distance of 50 kilometres between the estuary of the Weser river into the North Sea and the target industrial port. It could be shown that the mean deviation from the actual travel time at a distance of 50 kilometres is -19.8 minutes for the DNNC and 67.9 minutes for the LNNC. At a distance of 33 kilometres from the industrial port, the mean deviation of the DNNC decreases to 2.85 minutes and for the LNNC to 54.4 minutes. Furthermore, it has been observed that the shorter the distance to the destination port, the more accurate the predictions become.

Vessel delays and increased terminal call sizes negatively impact the ability to properly plan daily operations at seaport container terminals. Such traffic patterns lead to, among others, infrequent peak loads at the seaside of container terminals, complicating terminal operations. Thus, relying on annual or monthly statistics fails to account for these day-to-day fluctuations.

When container terminals are planned, be it a greenfield or brownfield terminal, these variations in operations need to be accounted for. The traditional formula-based approach to design terminals uses annual statistics.

In this study, it is first used to produce estimates for the required yard capacity for three existing exemplary container terminals. These are then compared to the results of numerical experiments using the synthetic container flow generator ConFlowGen. The findings reveal that yard capacity requirements fluctuate considerably depending on the timing of vessel arrivals and their call sizes. This dynamic modeling proved particularly beneficial for planning gateway traffic, offering more accurate storage capacity predictions. Suggestions are made for how to further develop ConFlowGen for handling transshipment traffic better in future versions.

With increasing concerns surrounding environmental impact in the renewable energy sector, this study delves into the analysis of carbon dioxide (CO2) emissions generated by maritime logistics operations within Offshore Wind Farms.

Automatic Identification System (AIS) data is collected from Crew Transfer Vessels (CTVs). The primary objective is to quantify the environmental impact of these operations and, consequently, contribute to the development of sustainable solutions that can be alternatively used. Using data science and software tools, utilizing AIS data and Python, NumPy, Pandas, and the nautical-calculations library, the authors calculated the total CO2 emissions produced by the sample Crew Transfer Vessel. This CTV sailed 60,000 nautical miles over 5 years.

Additionally, the authors will explore the feasibility of integrating hybrid or electric CTVs to curtail the overall CO2 emissions associated with wind farm operations. These findings collectively offer a pathway towards a greener and more sustainable offshore wind farm operations.

By incorporating machine learning models in the future, the framework can enhance the efficiency of routes used by the CTV, leading to reduced fuel consumption and further minimizing environmental impact.

Moreover, the integration of hybrid or electric CTVs presents an opportunity to not only reduce CO2 emissions but also decrease reliance on fossil fuels in offshore wind farm operations. Ultimately, implementing these findings can contribute to a more environmentally friendly and sustainable use of CTV in the Offshore Wind industry.

Ferry traffic is particularly dominant in inland seas such as the Baltic Sea, where it can exploit its advantage of high departure frequency and short journey times, thus enabling fast-moving traffic throughout Europe. Roll on/Roll off (RoRo) and Roll on/Roll off Passenger (RoPax) ports, however, are confronted with increasing competition for port expansion areas from various developments such as the rezoning to urban areas. Therefore, maintaining adequate access to RoRo/RoPax ports is becoming increasingly challenging and can only be achieved through the interaction of different stakeholders such as port authorities, ferry companies or city planners. In urban areas in particular, traffic situations increasingly occur that make it difficult for trucks or other vehicles to reach the port reliably and thus place a heavy load on terminal and shipping company resources.

After analysing the literature on simulation approaches with respect to truck arrival management in the RoRo/RoPax and the container terminal segment, the application of a pre-gate concept to the RoPax port Turku (Finland) in combination with a call-off structure was analysed by a simulation.

In the paper three different scenarios were compared regarding the positioning of pre-gate parking spaces according to the parameters: travel time, vehicle arrival time at the terminal and queue length at a prominent intersection.

The approach adopted offers a controllability that can be actively used by the terminal operators and stevedoring to make terminal operations and vehicle handling more efficient.

Transporting goods via inland waterways offers significant advantages over transport via road or rail. The inland waterway vessel is more environmentally friendly, reliable, and quieter than other transport modalities. This paper presents a framework based on this motivation to develop so-called MicroPorts to strengthen inland waterway transport and increase its attractiveness. MicroPorts are new small-scale transshipment facilities for inland waterways based on the conversion of existing infrastructure. Through this, the network of transshipment points on inland waterways can be expanded while keeping construction costs and impact on nature low and the transported goods closer to their destination, shortening the last few kilometers by road or rail. The MicroPorts framework was developed through several workshops with an inland shipping owner, pro-cess analysis at an inland waterway port and literature analyses. It comprises five elements: characteristics, operational requirements, technical requirements, loca-tion, and assessment parameters. Based on the framework, a method was derived to develop MicroPorts. The method contains four steps: 1. Identify potential loca-tions, 2. Selection of possible operational concepts, 3. Selection of possible tech-nical implementations, and 4. Evaluation of feasibility. The method can be used for the identification of new transshipment locations and planning of new Mi-croPorts. This paper also presents first developed MicroPorts concepts alongside an exemplary route.

Industry 4.0 represents a novel paradigm centered around digital factories, capa-ble of integrating information technologies and machines with intelligent prod-ucts. In this context, this article addresses the added monetary value resulting from adopting Industry 4.0 technologies in the development of a scraped surface heat exchanger equipment. This research aims to estimate the added value of a technology-based redesign of a food processing machine, considering the will-ingness to pay. The methodology employed to evaluate the integration of these technologies into the product is based on the Stated Preference (SP). The findings reveal a hierarchy among the enhancement opportunities that Industry 4.0 tech-nologies bring to the product. Consequently, in this case, incorporating features from Industry 4.0 that encompass the maintenance aspects contributes significant-ly to the product's value.

Digital twins play an essential role in manufacturing companies to adopt Industry 4.0. However, their uptake has been lagging, especially in European manufacturing firms. This can be attributed to the absence of automated methods for digitizing physical manufacturing resources and creating digital representations accessible and processable by both humans and computers. Our research addresses this challenge by automating the digitization of manufacturing resources captured on the shop floor. We employ object detection techniques on a set of images and align the results with an ontology that standardizes the semantic description of digital representations. This research aims to accelerate digital transformation for manufacturing companies, providing digital representations to their physical resources. The ontology-based digital representation fosters interoperability among diverse equipment and machines from various vendors. It enables the automated deployment of digital twins, improving the efficiency of planning and control of manufacturing systems.

The convergence of Value Stream Management with cutting-edge technologies represents a dynamic area of research, as underscored by recent studies. These studies reveal a growing emphasis on digitalization and share a common goal: proposing data-driven techniques to enhance and optimize conventional Value Stream Management struggling to adapt in rapidly changing environments. By the present paper, a digital Value Stream Map according to the Digital Twin (DT) concept is investigated. This Digital Value Stream Twin (DVST) is based on the orchestration of multiple DT, representing core elements of Value Stream Management such as material flowing through the value stream and related resources. Overcoming the fixed structure of the automation pyramid, business application systems and machine signals are merged as data sources into one model, verified by a business scenario, mainly carried out in an SAP S4/HANA (ERP - enterprise resource planning) test environment. In this context, the present study is built upon a validation using a digital value stream model according to the Digital Shadow (DS) approach. Conceptually, the expansion of the DS into a DT is described. From this, potentials regarding the value stream method are derived and investigated.

With the increasing popularity of Augmented Reality (AR) applications, especially for mobile devices, the technology supports several construction projects. Here, AR helps to communicate planned construction projects, as its visualization increases the immersion and is better understood than common approaches. However, these use cases are mainly outdoors, which pose special requirements. For most, the (geo-referenced) 3D models of planning projects must be aligned correctly in natural environments, which is a challenge, as many AR devices and standard methods are not working for (large) outdoor environments. For this reason, new research approaches based on different algorithms and sensors arise. This paper defines requirements for developing geo-referenced outdoor AR applications by a structured literature analysis and developing an application with the key requirements: accurate 3D model placement and integration. Creating the mobile outdoor AR application further provides insights for developing such systems. The application considers several outdoor activity requirements and addresses different approaches to geo-referencing with internal and external sensors. This paper also presents two model integration methods: a 2D and a 3D environment scan and algorithmic processing.

Shelf replenishment is a repetitive, manually executed, and time-consuming task in retail. This paper addresses this issue with an intelligent pointer unit that helps staff reduce the orientation time for small and similar products in the shelf replenishment process. The user wears a ring scanner to scan an article or its box, whereon the pointer unit illuminates the target shelf position received from a digital store model.

A comprehensive evaluation extracts the performance of the pointer unit within two user groups. The results show a reduction of the orientation time of \SI{88.5}{\percent} for beginners, respectively \SI{75}{\percent} for experienced staff members. Furthermore, accounting for the times needed for handling and alignment, a reduction of the overall search time of \SI{71.5}{\percent} for beginners, respectively \SI{22.5}{\percent} for experienced staff members, has been achieved.