The new paradigms of Industry 4.0 force all the industrial sectors to face a deep digital transformation in order to be on the edge in a competitive and globalized scenario. Following this trend, the shipbuilding industry has to establish its own path to adapt itself to the digital era. This chapter aims to explore this challenge and give an outlook on the multiple transformative technologies that are involved. For that reason, a case of study is presented as a starting point, in which the digital technologies that can be applied are easily recognized. A social network analysis (SNA) is developed among these key enabling technologies (KETs), in order to stress their correlations and links. As a result, artificial intelligence (AI) can be highlighted as a support to the other technologies, such as vertical integration of naval production systems (e.g., connectivity, Internet of things, collaborative robotics, etc.), horizontal integration of value networks (e.g., cybersecurity, diversification, etc.), and life cycle reengineering (e.g., drones, 3D printing (3DP), virtual and augmented reality, remote sensing networks, robotics, etc.).

/pdf/trends-of-digital-transformation-in-the-shipbuilding-sector-2w0mk635qe.pdf

Trends of Digital Transformation in the Shipbuilding Sector

Industry 4.0 is based on the cyber-physical transformation of processes, systems and methods applied in the manufacturing sector, and on its autonomous and decentralized operation. Industry 4.0 reflects that the industrial world is at the beginning of the so-called Fourth Industrial Revolution, characterized by a massive interconnection of assets and the integration of human operators with the manufacturing environment. In this regard, data analytics and, specifically, the artificial intelligence is the vehicular technology towards the next generation of smart factories.Chapters in this book cover a diversity of current and new developments in the use of artificial intelligence on the industrial sector seen from the fourth industrial revolution point of view, namely, cyber-physical applications, artificial intelligence technologies and tools, Industrial Internet of Things and data analytics. This book contains high-quality chapters containing original research results and literature review of exceptional merit. Thus, it is in the aim of the book to contribute to the literature of the topic in this regard and let the readers know current and new trends in the use of artificial intelligence for the Industry 4.0.

/pdf/new-trends-in-the-use-of-artificial-intelligence-for-the-2ne1fofnau.pdf

New Trends in the Use of Artificial Intelligence for the Industry 4.0

Advancements in control systems and integration of artificial intelligence in welding robots: A review

Small medium enterprises located in high-cost environments like Northern Europe, are increasing their reliance on digitalization and robotics to lower production costs and to keep the competitive edge over companies in low-cost environments. Using and developing technological methods shows that a high degree of flexibility is kept by digitally integrating manual labour and ensuring seamless end-to-end information flow across the internal and downstream supply chains. Thus, the concept of a product-model is proposed which congregates the design, engineering, and pre-production information about the product itself and the manufacturing system, in the context of steel welding industry. The necessary research and development are conducted through several design science cycles to ensure both the relevance of the proposed concept for the studied case company, and the rigor of the contribution to the knowledge base in the field. It is intended through the implementation of product-model based technologies to eliminate the need for manually conducted pre-production operations e.g., welding-robot programming, and radically reduce the time needed for pre-production operations. 

Digital Integration for Automatic Programming of Welding Robots

This paper presents a framework that integrates digital twin and virtual reality (VR) technologies to improve the efficiency and safety of human–robot collaborative systems in the disassembly domain. With the increasing complexity of the handling of end-of-life electronic products and as the related disassembly tasks are characterized by variabilities such as rust, deformation, and diverse part geometries, traditional industrial robots face significant challenges in this domain. These challenges require adaptable and flexible automation solutions that can work safely alongside human workers. We developed an architecture to address these challenges and support system configuration, training, and operational monitoring. Our framework incorporates a digital twin to provide a real-time virtual representation of the physical disassembly process, allowing for immediate feedback and dynamic adjustment of operations. In addition, VR is used to simulate and optimize the workspace layout, improve human–robot interaction, and facilitate safe and effective training scenarios without the need for physical prototypes. A unique case study is presented, where the collaborative system is specifically applied to the disassembly of antenna amplifiers, illustrating the potential of our comprehensive approach to facilitate engineering processes and enhance collaborative safety. 

A Framework for Enhanced Human–Robot Collaboration during Disassembly Using Digital Twin and Virtual Reality

In this paper, the concept of homogeneity is defined, from a topological perspective, in order to analyze how uniform is the material composition in 2D electron microscopy images. Topological multiresolution parameters are taken into account to obtain better results than classical techniques.

Topological Homogeneity for Electron Microscopy Images

In this paper, a customized interface developed in the framework of the ROBOT FASE II project is described. This project aimed at improving the productivity of two FANUC ARCMate 100iC MIG welding robots with R-30iA controllers mounted in an 8 meters-high mobile gantry crane at Navantia company in Puerto Real, Spain. The solution designed for welding application by the University of Cadiz consists of four parts (1) a library of piece templates including relevant information for each piece to be welded, including obviously the typical piece geometry shape and dimensions, but also all parameters needed for welding(sequence, intensity of the arc, waving description,…) and optimized to get a perfect result by a professional welder team (2) a coordinate measuring arm used to capture 3D information from the real world, (3) a software to generate automatically the optimized FANUC welding program using both the template and the 3D information captured by the arm, adapting the template to real-world coordinates and orientation, (4) and finally an FTP interface to transmit the optimized welding program to each robot for immediate welding operation. The use of this solution for welding operation has reduced robot programming time from hours to minutes for a typical structure allowing an important increase of productivity at Navantia company.

Development of a Customized Interface for a Robotic Welding Application at Navantia Shipbuilding Company

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Topological Homogeneity for Electron Microscopy Images

Development of a Customized Interface for a Robotic Welding Application at Navantia Shipbuilding Company