Advances in Science and Technology Vol. 132

Abstract: The objective of this work is to develop and validate a Digital Twin (DT) for a multistage production line of tapered roller bearings. The manufacturing process consists of ring machining and component assembly, including intensive quality controls. This work proposes the integration of machine learning models associated with the manufacture of the double outer ring and the two inner rings in the DT. The models are trained with real data, so that the DT can predict the behavior of the production process under changing conditions of ongoing processes, machines or materials, and optimal operating conditions can be predicted. The DT has been developed and integrated with the aim of guiding production by proposing optimal machine configurations. To this end, different stations have been modeled and integrated into the DT as independent modules: grinding machines, inner and outer rings pairing module, and a module for calculating the optimal family of rings to be ground. After integrating the DT in the line, results show not only a raise in the line efficiency but also a decrease in the overall scrap ratio.

Abstract: In recent years, manufacturing companies have become more flexible and reconfigurable to adapt to new manufacturing paradigms and market demands. Simulation technology, which is one of the enablers of Industry 4.0, is usually used to evaluate the performance of manufacturing lines to predict their response against some manufacturing scenario. The concept of a digital twin has gained popularity in the last years. A digital twin is defined as a virtual system connected to the physical system that replicates its behavior. In this paper, a conceptual design of a digital twin-based manufacturing system is established. This includes the hierarchy of virtual elements, the relations between physical and virtual elements, and the definition of the data flow and type. A discrete event simulator has been developed to act as the digital twin of an anodizing treatment line. The simulator is connected to company systems through a neutral interface that feeds the simulator with the current manufacturing plan. The standalone digital twin has been validated using real data and allows one to perform what-if simulations in real time.

Abstract: In times when companies must respond efficiently to market demands, reverse engineering plays a fundamental role. Although design processes are commonly developed with digital workflows, in reverse engineering different and independent phases with bottlenecks between them are involved. The present work addresses the challenge of establishing a continuous and efficient data flow between the three-dimensional digitized data obtained with 3D scanning and the automatic generation of NC toolpaths. A methodology is developed for the generation and optimization of NC toolpaths directly from the 3D point cloud data obtained through the three-dimensional scanning of pre-existing geometries. The methodology consists of an algorithm developed with Grasshopper, a script for visual programming in Rhino’s interface. It does not only attempt to reconstruct the three-dimensional geometry of the scanned part but also, it directly generates the tool paths and optimizes them with evolutionary optimization algorithms that are integrated in the methodology. A case study is developed for TMU-SIO TOWGTAI machining center with the proposed methodology. Finally, the obtained results and the efficiency of the methodology are analyzed and presented.

Abstract: The world is experiencing constant changes due to emerging technologies and business globalization. Industry 4.0 is causing paradigms to change at an industrial level, which, together with the technological advance of communication networks and the internet, will allow for achieving complete digitization of manufacturing processes. Digitization solutions implementation is hampered by the lack of adequate management procedures and methodologies to simplify the requirements analysis and the incorporation of improvements using I4.0.There are several methodologies for managing and controlling projects, but they need to adapt according to the required migration of systems from Industry 3.0 to Industry 4.0. A literature review has allowed identifying the most important characteristics of industry 4.0 based on the main digital enablers. Nowadays, any migration of technological systems also requires using an appropriate management methodology, replacing or complementing the traditional waterfall methodology, that can be easily controlled and where errors can be predicted and corrected in the shortest possible time. These new tools are important to facilitate the implementation of I4.0, especially in regions and companies with a low tradition of adaptation to technological changes.In this work, a novel concurrent methodology framework based on engineering and adapted Scrum work is proposed to implement I4.0 technology migration, using technology enablers. It was designed to provide several advantages, namely: feedback provided every certain period of time to correct errors, the use of multidisciplinary teams, and its easy implementation. This adapted Scrum & concurrent methodology framework will offer a new management approach to the I4.0 transition projects, which we expect can be applied at the industrial level, especially in developing countries.

Abstract: The assembly of an aircraft is executed by performing a series of assembly operations, which are carried out following specific instructions called work instructions. In addition, the quality control of these operations is performed following verification instructions. Traditionally, these work and verification instructions were based on 2D documentation (on paper or digital screen), prepared by manufacturing engineering, and made available to operators by manufacturing engineering systems (MES) when required. Over the last decade, Airbus has made significant progress in ensuring the digital continuity of processes, exploiting information from the industrial digital mock-up (iDMU) downstream, favoring the preparation and use of assembly and quality instructions through new techniques, such as lightweight 3D viewers, or augmented reality. This paper describes experiences of implementation of augmented reality (based on laser or holographic technology) in the workshop, both for assembly and quality processes. Several use cases are analyzed, comparing both technologies, explaining their pros and cons, and justifying the use of each of them in each process.

Abstract: Augmented Reality (AR) has started to be gradually utilized in industrial manufacturing. However, the gap between novel stage and industrial AR-based applications must be comprehensively solved. In this study, the task technology fit (TTF) and method of time measurement (MTM) are applied and put together to create a comprehensive map demonstrating the relationship between manufacturing tasks and AR-solution features. In addition, this map will support exploring the suitability of AR-based solutions and identifying the application areas of AR for industrial manufacturing, primarily focused on quality control, metrology and assembly tasks. By considering both the viewpoint of developers/users and the scientific principles underlying manufacturing tasks in this comprehensive map, the usability and effectiveness of the final AR solution are also ensured at an early stage of AR-based application development.As a result, this paper provides a useful system to utilize AR capabilities for more complex-multistep tasks in a standardized way. Thus, more potential development and improvement of AR-based solutions for quality 4.0, virtual metrology, and complex assemblies in an industrial manufacturing context could be holistically established and built.

Abstract: Reconfigurable Manufacturing Systems (RMS) have gained prominence in the Aerospace Industry in recent years for several reasons. These include drastic changes in production capacity due to post-COVID19 and new environmental regulations to adapt to remain competitive; however, the current RMS design has not changed. Ontology-based engineering systems (OBE) support complex collaborative design processes that involve multidisciplinary parties and various digital tools, integrating different levels of decision-making. Models for Manufacturing (MfM) is an OBE methodology that supports industrial design and decision making in manufacturing and assembly by preserving business knowledge in ontology models, the knowledge base for generating and integrating aircraft design and manufacturing systems. This paper introduces an MfM application for RMS design in the Aerospace Industry, presenting innovative design concepts that allow RMS to be implemented in a collaborative engineering process for an aerospace product.

Abstract: Industry 5.0 arises as a logical advance of Industry 4.0 to enhance the values that were being gradually abandoned due to the rapid technological advancement. These values focus on the human being, the sustainability and the continuity of the industrial system become the main objectives to be maintained during the development of the new smart industry model. These objectives allow the design of work environments within Industry 5.0 that ensure the adaptation of workers to technologies of Industry 4.0, in a sustainable way and that strengthen a resilient industrial system. In the present work the use of Value Sensitive Design (VSD) methodology for the redesign of manufacturing workplace in accordance with the values established by the Industry 5.0 is proposed. In this process, the VSD tripartite methodology allows to maintain the values of Industry 5.0 throughout the design process. Moreover, the integration of this methodology with the Axiomatic Design (AD) allows to achieve specific design parameters that meet the needs of the different stakeholders. The application of this model seeks the development of symbiotic work environments, in which workers increase their different physical, sensory and cognitive abilities with advanced technologies. The design of a work environment following the proposed model promotes a social smart industrial environment in which the safety and health of workers is ensured.

Abstract: The emerging technologies presented by the fourth industrial revolution present new opportunities across the entire industrial sector. Among those paradigms that have seen rapid and significant growth in recent years are Virtual Reality (VR) and Augmented Reality (AR), collectively known as Extended Reality (XR). These technologies provide a wide range of unexplored solutions across the manufacturing industry, that promise to improve the effectiveness and speed of various existing processes. One such activity that could potentially stand to benefit from XR is the project and development of End of Arm Tooling (EOAT) for robot applications.The initial purpose of this work is to first study the XR technologies, their current applications across various industries, and the hardware and software involved in their use and development. Then, the main goal is to develop XR solutions to aid in the project, development, and assembly of EOAT systems for extracting injected parts from a mould. Checking in with industry professionals throughout the development of a VR application, the functionalities were tailored to their needs.

Abstract: With the advancement of globalization and the growth of Industry 4.0, it is necessary to apply new concepts and methods for manufacturing to increase the productive capacity and efficiency of processes. These concepts allow the application of intelligent manufacturing within the Aerospace industry, responsible for transforming manufacturing processes using software technologies based on artificial intelligence, to automate the Sheet Metal Parts modeling process and get more accurate data. Therefore, it applies to Models for Manufacturing (MfM) in product projects, a recent methodology that presents an organization for formally defined information and knowledge. However, MfM does not consider information tracing and inconsistency analysis in the modeling phases. Based on this paradigm, a solution is proposed by developing and adopting methods, processes, and tools of Ontology-Based Engineering based on the MfM model to obtain data. In addition, Semantic Technologies are used for data processing through an OWL structure, also formalizing the information through semantic rules in SWRL. This research aims to: (I) Obtain data extracted from Sheet Metal Parts and structure them from ontology; (II) Formalize information about this data using semantic rules; (III) Validate information between product and manufacturing projects to identify and address inconsistencies in advance.