Manual work accounts for one of the largest workgroups in the European manufacturing
sector, and improving the training capacity, quality, and speed brings significant competitive …

This paper presents different prediction methods based on decision tree and ensemble
learning to suggest possible next assembly steps. The predictor is designed to be a …

Industrial assistive systems result from a multidisciplinary effort that integrates IoT (and
Industrial IoT), Cognetics, and Artificial Intelligence. This paper evaluates the Prediction by …

This paper presents a context-aware adaptive assembly assistance system meant to support
factory workers by embedding predictive capabilities. The research is focused on the …

Due to the new technological advancements and the adoption of Industry 4.0 concepts, the
manufacturing industry is now, more than ever, in a continuous transformation. This work …

Autonomous mobile robots (AMRs) are gaining popularity in various applications such as
logistics, manufacturing, and healthcare. One of the key challenges in deploying AMR is …

This paper presents a novel approach to recognize a worker's intentions for assistive
systems in manual assembly. Building on previous research, it introduces a process …

This study addresses the need to develop a sustainable manufacturing process in industrial
factories, as the industry desires to remain competitive while it is challenged to adopt eco …

A great challenge in applying AI to specific problems in the industry is to select the proper
method when multiple methods are available. In this paper, we intend to address this issue …

This thesis is focused on automated coronary centerline extraction from Cardiac Computed
Tomography Angiography (CCTA) data. This belongs to the domain of medical image …