As nuclear decommissioning ventures become increasingly complex, the role of digitalization in facilitating and enhancing these operations is becoming indispensable. This transition to a more digitized approach presents a myriad of advantages, including: augmented avenues for data acquisition, analysis, and visualization to bolster dismantling strategies; simulations in virtual environments for operator training; precise forecasting of future waste emergence, culminating in refined cost estimations; and more immersive decommissioning visualizations for both operators and external stakeholders. Salient benefits conferred by the integration of digital technologies in decommissioning encompass improved collaboration, enriched knowledge transfer, clarity regarding present technological constraints, insights into key influencing factors, clearer criteria for technology selection, and a profound understanding of the potential challenges and merits of a broader incorporation of digital tools in decommissioning endeavors. Of paramount importance is the opportunity presented for superior workforce training and safety measures, exemplified by ALARAbased planning. Amidst the myriad facets of digital adoption, 3D modeling of nuclear facilities derived from laser-scanned point clouds stands out as a pivotal domain in the digitalization. The transformation of intricate point cloud data into a comprehensible 3D mesh remains the crux of this paper. The process of mesh generation, despite being simpler than its counterpart of converting to a 3D solid model, is crucial for multiple reasons. The resultant 3D mesh offers an enhanced visual representation compared to a sparse point cloud, paving the way for improved spatial perception. Furthermore, it serves as a rudimentary tool for approximating component volumes and the ensuing waste, thereby playing an instrumental role in waste manipulation strategies, notably in collision detection. This paper delves deep into the nuances of mesh generation, conducting an parametric study of mesh conversion algorithms, including down-sampling rates. Through this rigorous examination, we endeavor to shed light on optimal methodologies, hoping to catalyze advancements in the digitalization of nuclear decommissioning processes.

Unloading operation by the unloader is dependent on the experience of the operator in the cabin. If the operator receives information about the unloading situation in the process of lifting the bucket, it is possible to prevent the collision of the bucket with the ship structure. In recent years, numerous measurement systems have become available on the market for three-dimensional surveying of objects, but they are very expensive. This study presents a high quality, low cost 3D laser scanning system designed for object recognition. The developed 3D laser scanning system is built on the base of a 2D laser sensor by the extension with a servo motor and a rotation module. In order to evaluate performance of the developed 3D laser scanning system, the developed system was applied to scan a shape of hatch and cargo holder on a cargo ship. Experimental results showed that to obtain a 3D scanning data for the area around the hatch and cargo holder.