Selective Darkening Filter and Welding Arc Observation for the Manual Welding Process

An optical see-through LCD (GLCD) with a resolution of n x m pixels gives the ability to selectively control the darkening in the welders view. The setup of such a Selective Auto Darkening Filter is developed and its applicability tested. The setup is done by integrating a camera into the welding operation for extracting the welding arc position properly. A prototype of a GLCD taylored for welding is mounted in the welder's view. The extraction of the welding arc position requires an enhanced video acquisition during welding. The observation of scenes with high dynamic contrast is an outstanding problem which occurs if very high differences between the darkest and the brightest spot in a scene occur. The application to welding with its harsh conditions needs the development of supporting hardware. The synchronization of the camera with the flickering light conditions of pulsed welding processes in Gas Metal Arc Welding (GMAW) stabilizes the acquisition process and allows the scene to be flashed precisely if required by compact high power LEDs. The image acquisition is enhanced by merging two different exposed images for the resulting image. These source images cover a wider histogram range than it is possible by using only a single shot image with optimal camera parameters. After testing different standard contrast enhancement algorithm a novel content based algorithm is developed. It segments the image into areas with similar content and enhances these independently

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

The 1st Advanced Manufacturing Student Conference (AMSC21) Chemnitz, Germany 15–16 July 2021

The Advanced Manufacturing Student Conference (AMSC) represents an educational format designed to foster the acquisition and application of skills related to Research Methods in Engineering Sciences. Participating students are required to write and submit a conference paper and are given the opportunity to present their findings at the conference. The AMSC provides a tremendous opportunity for participants to practice critical skills associated with scientific publication. Conference Proceedings of the conference will benefit readers by providing updates on critical topics and recent progress in the advanced manufacturing engineering and technologies and, at the same time, will aid the transfer of valuable knowledge to the next generation of academics and practitioners. *** The first AMSC Conference Proceeding (AMSC21) addressed the following topics: Advances in “classical” Manufacturing Technologies, Technology and Application of Additive Manufacturing, Digitalization of Industrial Production (Industry 4.0), Advances in the field of Cyber-Physical Systems, Virtual and Augmented Reality Technologies throughout the entire product Life Cycle, Human-machine-environment interaction and Management and life cycle assessment.:- Advances in “classical” Manufacturing Technologies - Technology and Application of Additive Manufacturing - Digitalization of Industrial Production (Industry 4.0) - Advances in the field of Cyber-Physical Systems - Virtual and Augmented Reality Technologies throughout the entire product Life Cycle - Human-machine-environment interaction - Management and life cycle assessmen

TOWARD INTELLIGENT WELDING BY BUILDING ITS DIGITAL TWIN

To meet the increasing requirements for production on individualization, efficiency and quality, traditional manufacturing processes are evolving to smart manufacturing with the support from the information technology advancements including cyber-physical systems (CPS), Internet of Things (IoT), big industrial data, and artificial intelligence (AI). The pre-requirement for integrating with these advanced information technologies is to digitalize manufacturing processes such that they can be analyzed, controlled, and interacted with other digitalized components. Digital twin is developed as a general framework to do that by building the digital replicas for the physical entities. This work takes welding manufacturing as the case study to accelerate its transition to intelligent welding by building its digital twin and contributes to digital twin in the following two aspects (1) increasing the information analysis and reasoning ability by integrating deep learning; (2) enhancing the human user operative ability to physical welding manufacturing via digital twins by integrating human-robot interaction (HRI). Firstly, a digital twin of pulsed gas tungsten arc welding (GTAW-P) is developed by integrating deep learning to offer the strong feature extraction and analysis ability. In such a system, the direct information including weld pool images, arc images, welding current and arc voltage is collected by cameras and arc sensors. The undirect information determining the welding quality, i.e., weld joint top-side bead width (TSBW) and back-side bead width (BSBW), is computed by a traditional image processing method and a deep convolutional neural network (CNN) respectively. Based on that, the weld joint geometrical size is controlled to meet the quality requirement in various welding conditions. In the meantime, this developed digital twin is visualized to offer a graphical user interface (GUI) to human users for their effective and intuitive perception to physical welding processes. Secondly, in order to enhance the human operative ability to the physical welding processes via digital twins, HRI is integrated taking virtual reality (VR) as the interface which could transmit the information bidirectionally i.e., transmitting the human commends to welding robots and visualizing the digital twin to human users. Six welders, skilled and unskilled, tested this system by completing the same welding job but demonstrate different patterns and resulted welding qualities. To differentiate their skill levels (skilled or unskilled) from their demonstrated operations, a data-driven approach, FFT-PCA-SVM as a combination of fast Fourier transform (FFT), principal component analysis (PCA), and support vector machine (SVM) is developed and demonstrates the 94.44% classification accuracy. The robots can also work as an assistant to help the human welders to complete the welding tasks by recognizing and executing the intended welding operations. This is done by a developed human intention recognition algorithm based on hidden Markov model (HMM) and the welding experiments show that developed robot-assisted welding can help to improve welding quality. To further take the advantages of the robots i.e., movement accuracy and stability, the role of the robot upgrades to be a collaborator from an assistant to complete a subtask independently i.e., torch weaving and automatic seam tracking in weaving GTAW. The other subtask i.e., welding torch moving along the weld seam is completed by the human users who can adjust the travel speed to control the heat input and ensure the good welding quality. By doing that, the advantages of humans (intelligence) and robots (accuracy and stability) are combined together under this human-robot collaboration framework. The developed digital twin for welding manufacturing helps to promote the next-generation intelligent welding and can be applied in other similar manufacturing processes easily after small modifications including painting, spraying and additive manufacturing

Application of the Fourth Industrial Revolution for High Volume Production in the Rail Car Industry

Some recent technological advances in line with the fourth industrial revolution (4IR) are rapidly transforming the industrial sector. This work explores the prospect of robotic and additive manufacturing solutions for mass production in the rail industry. It proposes a dual arm, 12-axis welding robot with advance sensors, camera, and algorithm as well as intelligent control system. The computer-aided design (CAD) of the robotic system was done in the Solidworks 2017 environment and simulated using the adaptive neuro-fuzzy interference system (ANFIS) in order to determine the kinematic motion of the robotic arm and the angles of joint. The simulation results showed the smooth motion of the robot and its suitability to carry out the welding operations for mass production of components during rail car manufacturing. In addition, the ability to fabricate several physical models directly from digital data through additive manufacturing (AM) is a key factor to ensuring rapid product development cycle. Given that AM is embedded in a digitally connected environment, flow of information as well as data processing and transmission in real time will be useful for massive turnout during mass production

Design and Analysis of the Virtual Reality Welding Training

A thesis presented to the faculty of the College of Business and Technology at Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Ritesh Chakradhar on November 19, 2021

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

Varying Feedback Strategy and Scheduling in Simulator Training: Effects on Learner Perceptions, Initial Learning, and Transfer

This experimental study investigated the effects of visual feedback on initial learning, perceived self-efficacy, workload, near transfer, far transfer, and perceived realism during a simulator-based training task. Prior studies indicate that providing feedback is critical for schema development (Salmoni, Schmidt, & Walter 1984; Sterman, 1994). However, its influence has been shown to dissipate and is not directly proportionate to the frequency at which it is given (Wulf, Shea, & Matschiner, 1998). A total of 54 participants completed the study forming six treatment groups. The independent treatment, visual feedback, was manipulated as scheduling (absolute—every practice trial or relative—every third trial) and strategies (gradual decrease of visual cues within the interface, gradual increase of visual cues within the interface, or a single consistent cue for each trial). Participants completed twelve practice trials of welding under one of six feedback manipulations; then, participants completed twelve practice trials of welding without it. Lastly, participants performed the weld task on actual equipment in a shop area. No treatment showed significant difference among groups with regard to initial learning, retention, near transfer, and far transfer measures. However, a statistical significance was found during initial learning and retention within each treatment group. Findings support empirical evidence that a variability of practice paradigm promotes learning (Lee & Carnahan, 1990; Shea & Morgan, 1979). Learner perceptions of realism suggest that novice learners perceive simulator fidelity as high, however, these perceptions may dissipate as the learner practices. Those groups that involved the greatest number of cues at the onset of practice or having cues available at every other trial reported the greatest amount of workload. All groups reported increases in perceptions of self-efficacy during practice on the simulator, but those perceptions decreased when participants performed the weld task on actual equipment. Findings suggest that contextual-interference of increasing, decreasing, or changing feedback counteracts the guidance effect of feedback as found in previous studies

Augmented reality ARC welding learning application to enhance student’s motivation

This study introduces a mobile application integrated with augmented reality that can be used by Mechanical Engineering students to learn welding subject. Moreover, a study of perception among a sample of respondents who have used the app has been conducted. Normally, students will learn the theoretical concepts of welding in the class followed by instruction-based training in the workshop. However, students have difficulty to follow everything that has been taught in the class in a limited time. Welding is dangerous for beginners and the welding environments are harmful and injurious to the health. Furthermore, the preliminary study revealed that the students lacked sufficient materials to assist them during revision and need additional materials for welding learning. This study proposes the Mobile Arc Welding Learning (MAWL) app which use mobile app integrated with augmented reality technology to study user’s perceptions based on ease of use, engagement, learnability, satisfaction and usefulness. The research methodology in this study was adapted from Kuechler and Vaishnavi which consists of five phases: awareness of problems, suggestions, development, evaluation, and conclusion. The study incorporates the ARCS motivation model and constructivist theory to provide effective learning material. The evaluation results showed that the independent variables (Engagement, Satisfaction and Usefulness) are significantly related to the dependent variable (motivation). The results of the perception study indicate that the users strongly agreed on ease of use, learnability, satisfaction, usefulness and motivation, while they agreed on engagement. The main contribution of this study is the MAWL app which is a supplementary learning tool with the purpose to motivate students in welding learning. The results show that the ARCS motivation model and constructivist theory can be applied to develop effective learning materials found in the Mobile Arc Welding Learning (MAWL) app. Besides that, engagement, satisfaction and usefulness have positive influence on motivation. Thus, when designing and developing AR mobile-based welding learning app, factors including engagement, satisfaction and usefulness need to be integrated into the app to improve the student’s motivation towards the tool

Nonterrestrial utilization of materials: Automated space manufacturing facility

Four areas related to the nonterrestrial use of materials are included: (1) material resources needed for feedstock in an orbital manufacturing facility, (2) required initial components of a nonterrestrial manufacturing facility, (3) growth and productive capability of such a facility, and (4) automation and robotics requirements of the facility