Model-based training of manual procedures in automated production systems

Maintenance engineers deal with increasingly complex automated production systems (aPSs). Such systems are characterized by an increasing computerization or the addition of robots that collaborate with human workers. The effects of changing or replacing components of such systems are difficult to assess since there are complex interdependencies between process parameters and the state of the components. This paper proposes a model-based training system that visualizes these interdependencies using domain-independent SysML models. The training system consists of a virtual training system for initial training and an online support system for assistance during maintenance or changeover procedures. Both systems use structural SysML models to visualize the state of the machine at a certain step of a procedure. An evaluation of the system in a changeover procedure against a paper-based manual showed promising results regarding effectiveness, usability and attractiveness.Comment: 25 pages, https://www.sciencedirect.com/science/article/pii/S095741581830080

Virtual Reality Applied to Welder Training

Welding is a challenging, risky, and time-consuming profession. Recently, there has been a documented shortage of trained welders, and as a result, the market is pushing for an increase in the rate at which new professionals are trained. To address this growing demand, training institutions are exploring alternative methods to train future professionals with the goals of improving learner retention of information, shortening training periods, and lowering associated expenses. The emergence of virtual reality technologies has led to initiatives to explore their potential for welding training. Multiple studies have suggested that virtual reality training delivers comparable, or even superior, results when compared to more conventional approaches, with shorter training times and reduced costs in consumables. Additionally, virtual reality allows trainees to try out different approaches to their work. The primary goal of this dissertation is to develop a virtual reality welding simulator. To achieve this objective effectively, the creation of a classification system capable of identifying the simulator’s key characteristics becomes imperative. Therefore, the secondary objective of this thesis is to develop a classification system for the accurate evaluation and comparison of virtual reality welding simulators. Regarding the virtual reality welding simulation, the HTC VIVE Pro 2 virtual reality equipment was employed, to transfer the user’s action from the physical to the virtual world. Within this virtual environment, it was introduced a suite of welding tools and integrated a Smoothed Particle Hydrodynamics simulator to mimic the weld creation. After conducting comprehensive testing that revealed certain limitations in welding quality and in the simulator performance, the project opted to incorporate a Computational Fluid Dynamics (CFD) simulator. The development of the CFD simulator proved to be a formidable challenge, and regrettably, its complete implementation was unattainable. Nevertheless, the project delved into three distinct grid architectures, from these, the dynamic grid was ultimately implemented. It also proficiently integrated two crucial solvers for the Navier-Stokes equations. These functions were implemented in the Graphics Processing Unit (GPU), to improve their efficiency. Upon comparing GPU and Central Processing Unit (CPU) performance, the project highlighted the substantial computational advantages of GPUs and the advantages it brings to fluid simulations.A soldadura é uma profissão exigente, perigosa e que requer um grande investimento de tempo para alcançar resultados satisfatórios. Recentemente, tem sido registada uma falta de profissionais qualificados na área da soldadura. Como resultado, o mer cado está a pressionar para um aumento do ritmo a que os novos trabalhadores são formados. Para responder a esta crescente procura, as instituições de formação estão a explorar métodos alternativos para formar futuros profissionais, com o objetivo de melhorar a retenção de informação, encurtar os períodos de treino e reduzir as despe sas associadas. Com o desenvolvimento de tecnologias nas áreas de realidade virtual e realidade aumentada, têm surgido iniciativas para explorar o potencial destas na formação de soldadura. Vários estudos sugeriram que a formação em realidade virtual proporciona resultados comparáveis, ou mesmo superiores, aos de abordagens mais convencionais, com tempos de formação mais curtos e reduções nos custos de consumíveis. Além disso, a realidade virtual permite aos formandos experimentar diferentes abordagens ao seu trabalho. O objetivo principal desta dissertação é o desenvolvimento de um simulador de soldadura em realidade virtual. Para atingir este objetivo de forma eficaz, torna-se imperativa a criação de um sistema de classificação capaz de identificar as características chave do simulador. Assim, o objetivo secundário desta dissertação é desenvolver um sistema de classificação para a avaliação e comparação precisas de simuladores de soldadura em realidade virtual. Relativamente ao simulador de soldadura em realidade virtual, foi utilizado o kit de realidade virtual HTC VIVE Pro 2, para transferir as ações do utilizador no mundo físico para o mundo virtual. No ambiente virtual, foi introduzido um con junto de ferramentas de soldadura e integrado um simulador de Hidrodinâmica de Partículas Suavizadas para simular a criação da solda. Após a realização de testes exaustivos que revelaram algumas limitações na qualidade da solda e no desempenho do simulador, o projeto optou por incorporar um simulador de Dinâmica de Fluidos Computacional (CFD). O desenvolvimento do simulador CFD revelou-se um desa fio formidável e, infelizmente, não foi possível completar a sua implementação. No entanto, o projeto aprofundou três arquiteturas de grelha distintas, das quais foi implementada a grelha dinâmica. O projeto também implementou duas funções cru ciais para resolver as equações de Navier-Stokes. As funções relativas ao simulador de fluidos foram implementadas na Unidade de Processamento Gráfico (GPU), a fim de melhorar a sua eficiência. Ao comparar o desempenho da GPU com o da Unidade Central de Processamento (CPU), o projeto evidenciou os beneficios computacionais das GPUs e as vantagens que trazem para as simulações de fluidos

Rehabilitation Engineering

Population ageing has major consequences and implications in all areas of our daily life as well as other important aspects, such as economic growth, savings, investment and consumption, labour markets, pensions, property and care from one generation to another. Additionally, health and related care, family composition and life-style, housing and migration are also affected. Given the rapid increase in the aging of the population and the further increase that is expected in the coming years, an important problem that has to be faced is the corresponding increase in chronic illness, disabilities, and loss of functional independence endemic to the elderly (WHO 2008). For this reason, novel methods of rehabilitation and care management are urgently needed. This book covers many rehabilitation support systems and robots developed for upper limbs, lower limbs as well as visually impaired condition. Other than upper limbs, the lower limb research works are also discussed like motorized foot rest for electric powered wheelchair and standing assistance device

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

Home-based rehabilitation of the shoulder using auxiliary systems and artificial intelligence: an overview

Advancements in modern medicine have bolstered the usage of home-based rehabilitation services for patients, particularly those recovering from diseases or conditions that necessitate a structured rehabilitation process. Understanding the technological factors that can influence the efficacy of home-based rehabilitation is crucial for optimizing patient outcomes. As technologies continue to evolve rapidly, it is imperative to document the current state of the art and elucidate the key features of the hardware and software employed in these rehabilitation systems. This narrative review aims to provide a summary of the modern technological trends and advancements in home-based shoulder rehabilitation scenarios. It specifically focuses on wearable devices, robots, exoskeletons, machine learning, virtual and augmented reality, and serious games. Through an in-depth analysis of existing literature and research, this review presents the state of the art in home-based rehabilitation systems, highlighting their strengths and limitations. Furthermore, this review proposes hypotheses and potential directions for future upgrades and enhancements in these technologies. By exploring the integration of these technologies into home-based rehabilitation, this review aims to shed light on the current landscape and offer insights into the future possibilities for improving patient outcomes and optimizing the effectiveness of home-based rehabilitation programs.info:eu-repo/semantics/publishedVersio

Requirement analysis and sensor specifications – First version

In this first version of the deliverable, we make the following contributions: to design the WEKIT capturing platform and the associated experience capturing API, we use a methodology for system engineering that is relevant for different domains such as: aviation, space, and medical and different professions such as: technicians, astronauts, and medical staff. Furthermore, in the methodology, we explore the system engineering process and how it can be used in the project to support the different work packages and more importantly the different deliverables that will follow the current. Next, we provide a mapping of high level functions or tasks (associated with experience transfer from expert to trainee) to low level functions such as: gaze, voice, video, body posture, hand gestures, bio-signals, fatigue levels, and location of the user in the environment. In addition, we link the low level functions to their associated sensors. Moreover, we provide a brief overview of the state-of-the-art sensors in terms of their technical specifications, possible limitations, standards, and platforms. We outline a set of recommendations pertaining to the sensors that are most relevant for the WEKIT project taking into consideration the environmental, technical and human factors described in other deliverables. We recommend Microsoft Hololens (for Augmented reality glasses), MyndBand and Neurosky chipset (for EEG), Microsoft Kinect and Lumo Lift (for body posture tracking), and Leapmotion, Intel RealSense and Myo armband (for hand gesture tracking). For eye tracking, an existing eye-tracking system can be customised to complement the augmented reality glasses, and built-in microphone of the augmented reality glasses can capture the expert’s voice. We propose a modular approach for the design of the WEKIT experience capturing system, and recommend that the capturing system should have sufficient storage or transmission capabilities. Finally, we highlight common issues associated with the use of different sensors. We consider that the set of recommendations can be useful for the design and integration of the WEKIT capturing platform and the WEKIT experience capturing API to expedite the time required to select the combination of sensors which will be used in the first prototype.WEKI

A Framework for Augmenting Building Performance Models Using Machine Learning and Immersive Virtual Environment

Building performance models (BPMs), such as building energy simulation models, have been widely used in building design. Existing BPMs are mainly derived using data from existing buildings. They may not be able to effectively address human-building interactions and lack the capability to address specific contextual factors in buildings under design. The lack of such capability often contributes to the existence of building performance discrepancies, i.e., differences between predicted performance during design and the actual performance. To improve the prediction accuracy of existing BPMs, a computational framework is developed in this dissertation. It combines an existing BPM with context-aware design-specific data involving human-building interactions in new designs by using a machine learning approach. Immersive virtual environments (IVEs) are used to acquire data describing design-specific human-building interactions, a machine learning technique is used to combine data obtained from an existing BPM, and IVEs are used to generate an augmented BPM. The potential of the framework is investigated and evaluated. An artificial neural network (ANN)-based greedy algorithm combines context-aware design-specific data obtained from IVEs with an existing BPM to enhance the simulations of human-building interactions in new designs. The results of the application show the potential of the framework to improve the prediction accuracy of an existing BPM evaluated against data obtained from the physical environment. However, it lacks the ability to determine the appropriate combination between context-aware design-specific data and data of the existing BPM. Consequently, the framework is improved to have ability to determine an appropriate combination based on a specified performance target. A generative adversarial network (GAN) is used to combine context-aware design-specific data and data of an existing BPM using the performance target as guide to generate an augmented BPM. The results confirm the effectiveness of this new framework. The performance of the augmented BPMs generated using the GAN-based framework is significantly better than the updated BPMs generated using the ANN-based greedy algorithm. The framework is completed by incorporating a robustness analysis to assist investigations of robustness of the GAN regarding the uncertainty involved in the input parameters (i.e., an existing BPM and context-aware design-specific data). Overall, this dissertation shows the promising potential of the framework in enhancing performance of BPMs and reducing performance discrepancies between estimations made during design and in performance in actual buildings