This article examines the theoretical and practical implications of artificial intelligence (AI) integration in supply chain management (SCM). AI has developed dramatically in recent years, embodied by the newest generation of large language models (LLM) that exhibit human-like capabilities in various domains. However, SCM as a discipline seems unprepared for this potential revolution, as existing perspectives do not capture the potential for disruption offered by AI tools. Moreover, AI integration in SCM is not only a technical but also a social process, influenced by human sensemaking and interpretation of AI systems. This article offers a novel theoretical lens called the AI Integration (AII) framework, which considers two key dimensions: the level of AI integration across the supply chain and the role of AI in decision-making. It also incorporates human meaning-making as an overlaying factor that shapes AI integration and disruption dynamics. The article demonstrates that different ways of integrating AI will lead to different kinds of disruptions, both in theory and practice. It also discusses the implications of AI integration for SCM theorizing and practice, highlighting the need for cross-disciplinary collaboration and sociotechnical perspectives.
This article develops a micro-level theoretical perspective of business influence in international negotiations. By drawing on organizational institutional theory, the article proposes that site-specific institutionalized norms can structure the nature and extent of business power. The article illustrates the value of this perspective through an illustrative case study of the International Maritime Organization (IMO) through interviews and participant observation of on-site dynamics during negotiations on environmental shipping regulation. The article shows how, in the case of the IMO, specific institutionalized norms and beliefs structure private actors’ possible influence and their claims to authority. In particular, strongly held beliefs about the nature of political deliberation in the IMO both constrain and enable business interests, sometimes overriding the general structural power of the shipping industry. This research implies that future scholarship of business power and lobbying should be attentive to specific institutionalized ideas structuring business actors’ range of legitimate activities, in particular in international institutions where individual negotiation sites can develop idiosyncratic norms and beliefs about the legitimacy of private actor participation.
In this study, we investigate the barriers and enablers companies face when they seek to establish a fully decarbonized supply chain from the ground up. While recent research on sustainable supply chain management has advanced our understanding of how existing supply chains can become more sustainable, there is less research on fully decarbonized supply chains that are designed carbon neutral to produce carbon neutral products. This research aims to expand that frontier by investigating the case of the emerging supply chain delivering fossil-neutral e- methanol to the shipping industry.
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Maritime spatial planning (MSP) needs tools to facilitate discussions and manage spatial data in collaborative workshops that involve actors with different types of backgrounds and expertise. Never the less, spatial tools in real-world MSP are only sparsely used. In the article it is argued that more knowledge about the use of GIS can support MSP is needed. It studies the use of GIS as a tool for collaborative MSP in five steps around development and testing of the prototype collaborative GIS, Baltic Explorer. The evaluation of the use found that the present functionalities of the system could support and facilitate the collaborative discussions in the MSP work. Still more research in the use of spatial data in the MSP process is needed.
Gathering real-world high-quality data from underwater environments is cost-intensive, as is labeling this data for machine learning. Given this, synthetic data represents a possible solution that delivers ground-truth training data. Nevertheless, rendering and modeling of underwater environments are challenging due to several factors, including attenuation, scattering, and turbidity. The focus of this study is on the creation of a simulated underwater environment constructed for the purposes of simulating marine growth on offshore structures. The main requirement is the creation of renderings of sufficient quality and quantity with respect to the representation of marine-species distribution and intra-class variation, and sufficiently accurate recreation of lighting and turbidity (Jerlov water type) conditions underwater. Underwater rendering has been implemented using Blender, with marine growth from 2D/3D scanned and hand-modelled entities combined with a CAD model of an actual offshore installation. The proposed approach provides for the generation of synthetic images usable for training computer vision models in marine-growth inspection applications as well as other related underwater applications. This has been demonstrated in a case study, wherein the utility of the rendered dataset has been briefly demonstrated in a neural network marine-growth segmentation task. The produced renderings are available as a dataset of 1038 scene renders, using varying poses and randomized representative marine growth; each render includes RGB images, ground-truth segmentation masks, water-free RGB images, and depth information. In future work, the expansion with additional species and objects in other oceanic and coastal environments is envisioned.
The maritime industry is one of the greenest modes of transportation, taking care of almost 90% of the global trade. The maritime container business revolves around liner shipping, which consists of container vessels sailing on fixed itineraries. For the last 20 years, there has been an increasing number of publications regarding how to design such fixed routes (services), to ensure a high level of service while minimizing operational costs and environmental impact. The liner shipping network design problem can briefly be described as follows: Given a set of demands (defined by origin, destination, time limit) and a set of vessels with variable capacity, the task is to design a set of weekly services, assign vessels to the services, and flow the demand through the resulting network such that it arrives within the stated time constraints. The objective is to maximize revenue of transported demand subtracting the operational costs. We present an in-depth literature overview of existing models and solution methods for liner shipping network design, and discuss the four main families of solution methods: integrated mixed integer programming models; two-stage algorithms designing services in the first step and flowing containers in the second step; two-stage algorithms first flowing containers and then designing services; and finally algorithms for selecting a subset of proposed candidate services. We end the presentation by comparing the performance of leading algorithms using the public LINER-LIB instances. The paper is concluded by discussing future trends in liner shipping, indicating directions for future research.
Coupled mooring analysis using CFD with dynamic mooring models is becoming an established field. This is an important step for better predictions of responses of moored marine structures in extreme sea states and also for capturing the low-frequency response correctly. The coupling between the CFD and mooring solvers are most often carried out by exchanging the fairlead/anchor points and fairlead forces. In this paper we will discuss the effects of using (i) viscous fluid flow on a mooring component level (submerged buoys and clump weights) and (ii) the fluid-structure coupling between the viscous fluid solver and the mooring system.
High-fidelity viscous computational fluid dynamics (CFD) models coupled to dynamic mooring models is becoming an established tool for marine wave-body-mooring (WBM) interaction problems. The CFD and the mooring solvers most often communicate by exchanging positions and mooring forces at the mooring fairleads. Mooring components such as submerged buoys and clump weights are usually not resolved in the CFD model, but are treated as Morison-type bodies. This paper presents two recent developments in high-fidelity WBM modelling: (i) a one-way fluid-mooring coupling that samples the CFD fluid kinematics to approximate drag and inertia forces in the mooring model; and (ii) support for inter-moored multibody simulations that can resolve fluid dynamics on a mooring component level. The developments are made in the high-order discontinuous Galerkin mooring solver MoodyCore, and in the two-phase incompressible Navier–Stokes finite volume solver OpenFOAM. The fluid-mooring coupling is verified with experimental tests of a mooring cable in steady current. It is also used to model the response of the slack-moored DeepCwind FOWT exposed to regular waves. Minor effects of fluid-mooring coupling were noted, as expected since this a mild wave case. The inter-mooring development is demonstrated on a point-absorbing WEC moored with a hybrid mooring system, fully resolved in CFD-MoodyCore. The WEC (including a quasi-linear PTO) and the submerged buoys are resolved in CFD, while the mooring dynamics include inter-mooring effects and the one-way sampling of the flow. The combined wave-body-mooring model is judged to be very complete and to cover most of the relevant effects for marine WBM problems.
We present computations of cavitating flow over a NACA0015 hydrofoil. The simulations are performed by a finite volume compressible Euler model with dynamic mesh adaptation. The adaptive mesh refinement (AMR) is driven by a generic, simple and efficient error estimator based on the jump in value between cell faces for a given variable. It is shown that AMR based on vapour fraction provide unsatisfactory results both for (quasi-) steady and unsteady cavitation, as the major flow features are not captured. Instead, adaptivity driven by the Q-value proved successful even for resolving the cavity interface.
High-fidelity models become more and more used in the wave energy sector. They offer a fully nonlinear simulation tool that in theory should encompass all linear and nonlinear forces acting on a wave energy converter (WEC). Studies using high-fidelity models are usually focusing on validation of the model. However, a validated model does not necessarily provide reliable solutions. Solution verification is the methodology to estimate the numerical uncertainties related to a simulation. In this work we test four different approaches: the classical grid convergence index (GCI); a least-squares version (LS-GCI); a simplified version of the least-square method (SLS-GCI); and the ITTC recommended practice. The LS-GCI requires four or more solutions whereas the other three methods only need three solutions. We apply these methods to four different high-fidelity models for the case of a heaving sphere. We evaluate the numerical uncertainties for two parameters in the time domain and two parameters in the frequency domain. It was found that the GCI and ITTC were hard to use on the frequency domain parameters as they require monotonic convergence which sometimes does not happen due to the differences in the solutions being very small. The SLS-GCI performed almost as well as the SL-GCI method and will be further investigated.