Showing papers in "Procedia Manufacturing in 2020"

TL;DR: This study collects and analyzes the main contributions in the literature about the application of blockchain in the agricultural sector, focusing on food traceability issues, and shows that the blockchain technology is still in its early stage.

TL;DR: A systematic literature review was conducted to assess the role of Digital Twin models in industrial operations and to identify challenges for realization and insights are provided for different industrial sectors, practitioners, researchers and experts of the field on the specific roles of digital Twin models and challenges of implementing these models in the areas of production, predictive maintenance, and after-sale services.

TL;DR: A brief introduction of RUL prediction is given and the start-of-the-art DL approaches in terms of four main representative deep architectures, including Auto-encoder, Deep Belief Network, DBN, Convolutional Neural Network and Recurrent Neural Network are reviewed.

TL;DR: In this publication, a deep learning approach for image processing is investigated in order to quantify the tool wear state using machine tool integrated microscopes in the scientific and industrial environment.

TL;DR: In this paper, the authors present key leadership characteristics and skills in the context of Industry 4.0 and their relationship with four leadership skills groups: cognitive skills, interpersonal skills, business skills, and strategic skills.

TL;DR: In this article, a laboratory-scale instrumented 3D printing machine has been designed and manufactured, and a numerical model has been developed to predict the influence of the process parameters on the cooling and adhesion.

TL;DR: Evaluating the main application fields of Industry 4.0 and analyzing the enabling technologies used in these fields appears to be Logistics 4.

TL;DR: The proposed diagnostic method can achieve effective bearing fault diagnosis with relatively fewer CNN model parameters, and has some generalization ability.

TL;DR: The roles of collaborative and intelligent robotic system and its enabling technologies including ROS and ROS2, integrated drive system, robotic sensors, horizontal integration of a robotic network, human-robot friendly and natural interaction, and deep learnt robots are re-visited.

TL;DR: This paper explores the current literature on the integration of DES and DTs and identifies trends and challenges for contemporary Logistics.

TL;DR: An innovative approach that uses a collaborative robot to support the smart inspection and corrective actions for quality control systems in the manufacturing process, complemented by an intelligent system that learns and adapts its behavior according to the inspected parts.

TL;DR: A framework enabling collaborative product design based on AR is presented, which acts as the digital thread for connecting engineers to customers and is tested in vitro, in a machine shop, in order to gather useful insight into the skills and competencies acquired by the participants during the development of the project.

TL;DR: In this article, a complete demonstration of the modelling and simulation of a 1 MW photovoltaic plant in one zone located in the north of Morocco, as a study, is presented.

TL;DR: In this paper, the authors analyze the challenges and opportunities of technological innovations, of technological progress represented by the artificial intelligence, and present not only the benefits of this new revolution but also its possible disadvantages.

TL;DR: A novel way of conceptualizing the human operator necessarily implicates human values in the technologies that constitute it and the design methodology known as value sensitive design (VSD) is drawn upon to discuss how these Operator 4.0 technologies can be designed for human values.

TL;DR: This work analyzes three different transportation systems with incremental use of drones for the delivery of parcels, addressing the problem of delivering parcels without drone, the problem in which the deliveries are performed by a fleet of drones starting from the central depot, and a hybrid transportation system where the classical vehicles are equipped with drones.

TL;DR: A deep learning-based process monitoring method for directed energy deposition in AM using thermal images collected during manufacturing are used to identify the process condition, and a deep convolutional neural network model is proposed to build an end-to-end condition monitoring framework.

TL;DR: A gap analysis is performed by performing a gap analysis between current (traditional) business models and next generation digitized shipping industry, discussing the maturity level and the technological barriers.

TL;DR: In this paper, the authors evaluated the effect of bead stepover on the final part geometry form, micro-hardness and density in a 5-axis laser-based DED BeAM Machine Magic800 with laser spot size of 080 mm.

TL;DR: In this article, the authors propose a DT modeling method based on a multi-agent architecture for quality control during manufacturing processes and provide solutions to gather relevant information and analyze the corresponding influences on product quality.

TL;DR: This work introduces a descriptive approach for understanding Maritime 4.0 in a more comprehensive manner and describes how processes and manufacturing processes can be improved and advanced through such efforts.

TL;DR: The state-of-the-art of the TCM systems covering three major machining operations are presented, their application feasibility in industry environments is discussed, and some current TCMS implementations are states.

TL;DR: In this article, the effect of feed on the performance of carbon fiber reinforced polymers (CFRP) composites was investigated under dry, MQL and cryogenic conditions and the results were compared.

TL;DR: In this article, the authors present findings concerning the prospects of the implementation of digital transformation technologies (DTT) for more sustainable processes in logistics and supply chain management of manufacturing companies.

TL;DR: In this paper, a rolling bearing fault diagnosis method via short time Fourier transform (STFT) and improved instantaneous frequency estimation algorithm is proposed, which can convert all the trajectories of instantaneous components, e.g., fault characteristic frequency (FCF) and modulation rotating frequency, to linear path in the time-frequency domain.

TL;DR: In this paper, the results of the preliminary tests carried out by means of the FBM technology in which an external contribution of rotational speed of the samples was introduced, in order to increase the relative speed and energy dissipation between the parts and the fluidised abrasive particles, with the aim to increase process efficiency in terms of surface roughness reduction.

TL;DR: In this article, a Siamese convolutional neural network (Siamese-CNN) was used to do one-shot recognition for quality control of steel by identifying defects on the steel surface.

TL;DR: In this paper, the authors show how new technologies like Building Information Modeling connected with Virtual and Augmented Reality could empower Lean Construction methodologies to increase efficiency during the building execution process.

TL;DR: The present study investigates the use of powder laser metal deposition and wire-arc additive manufacturing for hybrid manufacturing of Ti-6Al-4V aerospace forgings, based on a conventionally pre-formed forging which does not yet have all the features of the final component, which will be added by additive manufacturing.

TL;DR: A human reliability assessment simulation model is proposed that takes into consideration performance shaping factors that affect human work in a complex Industry 4.0 system by considering the deployment of an anthropocentric approach, where human operators will make decisions, supported by cyber physical systems, rather than human work being dominated and determined by technology.