Virtualized Welding Based Learning of Human Welder Behaviors for Intelligent Robotic Welding

Combining human welder (with intelligence and sensing versatility) and automated welding robots (with precision and consistency) can lead to next generation intelligent welding systems. In this dissertation intelligent welding robots are developed by process modeling / control method and learning the human welder behavior. Weld penetration and 3D weld pool surface are first accurately controlled for an automated Gas Tungsten Arc Welding (GTAW) machine. Closed-form model predictive control (MPC) algorithm is derived for real-time welding applications. Skilled welder response to 3D weld pool surface by adjusting the welding current is then modeled using Adaptive Neuro-Fuzzy Inference System (ANFIS), and compared to the novice welder. Automated welding experiments confirm the effectiveness of the proposed human response model. A virtualized welding system is then developed that enables transferring the human knowledge into a welding robot. The learning of human welder movement (i.e., welding speed) is first realized with Virtual Reality (VR) enhancement using iterative K-means based local ANFIS modeling. As a separate effort, the learning is performed without VR enhancement utilizing a fuzzy classifier to rank the data and only preserve the high ranking “correct” response. The trained supervised ANFIS model is transferred to the welding robot and the performance of the controller is examined. A fuzzy weighting based data fusion approach to combine multiple machine and human intelligent models is proposed. The data fusion model can outperform individual machine-based control algorithm and welder intelligence-based models (with and without VR enhancement). Finally a data-driven approach is proposed to model human welder adjustments in 3D (including welding speed, arc length, and torch orientations). Teleoperated training experiments are conducted in which a human welder tries to adjust the torch movements in 3D based on his observation on the real-time weld pool image feedback. The data is off-line rated by the welder and a welder rating system is synthesized. ANFIS model is then proposed to correlate the 3D weld pool characteristic parameters and welder’s torch movements. A foundation is thus established to rapidly extract human intelligence and transfer such intelligence into welding robots

The Use of Virtual Welding Simulators to Evaluate Experienced Welders

Virtual reality welding simulations have been, and continue to be, a trend in welding training programs. The goal of this study was to examine the use of virtual reality simulations as an assessment tool for existing welders. This study used a virtual reality welding simulator, VRTEX® 360, to assess the existing skills of experienced and trained novice welders. This study also used the shielded metal arc welding (SMAW) process to perform simple and complex welds. Performance was evaluated through a quality score, which was based on the following five welding parameters: arc length, position, work angle, travel angle, and travel speed. The virtual reality welding simulator was able to evaluate performance, but it could not distinguish between experienced and trained novice welders. On average, experienced welders as a group scored 10 quality points higher than trained novice welders. Welding experience also had a large to very large effect on the quality score for each weld type. One identified trend for both experienced and trained novice welders was as weld difficulty increased, the quality score decreased. It is recommended that industries use virtual reality simulators to evaluate welders for ensuring high­quality welding in production practices

An evaluation of the AWS Entry Level Welder Training Program

The purpose of this study was to evaluate the effectiveness of a training program for Entry Level Welders and to provide this information to the American Welding Society (AWS), industry, and educators. The problem of this study was to evaluate the AWS Entry Level Welder Training Program (ELWTP) by obtaining the opinions of faculty members who taught the program and welders who had completed the program. Two groups comprised the research population for this study. The first group consisted of faculty members who were actually involved in teaching the course at institutions accredited by the AWS to offer the curriculum. The second group consisted of all graduates of the program registered as Certified Entry Level Welders. There were 118 Certified Entry Level Welders and 251 registered institutions (faculty) on lists furnished by the AWS. A questionnaire was developed based on the curriculum guidelines presented in AWS Manual EG2.0-95, Guide for Training and Qualification of Welding Personnel-Entry Level Welders. These guidelines direct the institutions in providing competency-based training that leads to the certification of trainees in accordance with AWS specifications. The ELWTP consists of six Courses which are further divided into 65 Learning Objectives. These Courses and Learning Objectives provided the framework for the questionnaire. Respondents (faculty and graduates) were asked to evaluate the course content of each of the 65 Learning Objectives by means of a five-point Likert Scale, and the means for welders and faculty were compared. The results of the study indicated that, of the six ELWTP Courses, only Course B. Drawing and Welding Symbol Interpretation had a preference by both welders and faculty to have the course content Increased Slightly. In general, both welders and faculty members were satisfied with the Courses and Learning Objectives as offered by the ELWTP with welders slightly favoring increases in instructional content

Development and evaluation of mixed reality-enhanced robotic systems for intuitive tele-manipulation and telemanufacturing tasks in hazardous conditions

In recent years, with the rapid development of space exploration, deep-sea discovery, nuclear rehabilitation and management, and robotic-assisted medical devices, there is an urgent need for humans to interactively control robotic systems to perform increasingly precise remote operations. The value of medical telerobotic applications during the recent coronavirus pandemic has also been demonstrated and will grow in the future. This thesis investigates novel approaches to the development and evaluation of a mixed reality-enhanced telerobotic platform for intuitive remote teleoperation applications in dangerous and difficult working conditions, such as contaminated sites and undersea or extreme welding scenarios. This research aims to remove human workers from the harmful working environments by equipping complex robotic systems with human intelligence and command/control via intuitive and natural human-robot- interaction, including the implementation of MR techniques to improve the user's situational awareness, depth perception, and spatial cognition, which are fundamental to effective and efficient teleoperation. The proposed robotic mobile manipulation platform consists of a UR5 industrial manipulator, 3D-printed parallel gripper, and customized mobile base, which is envisaged to be controlled by non-skilled operators who are physically separated from the robot working space through an MR-based vision/motion mapping approach. The platform development process involved CAD/CAE/CAM and rapid prototyping techniques, such as 3D printing and laser cutting. Robot Operating System (ROS) and Unity 3D are employed in the developing process to enable the embedded system to intuitively control the robotic system and ensure the implementation of immersive and natural human-robot interactive teleoperation. This research presents an integrated motion/vision retargeting scheme based on a mixed reality subspace approach for intuitive and immersive telemanipulation. An imitation-based velocity- centric motion mapping is implemented via the MR subspace to accurately track operator hand movements for robot motion control, and enables spatial velocity-based control of the robot tool center point (TCP). The proposed system allows precise manipulation of end-effector position and orientation to readily adjust the corresponding velocity of maneuvering. A mixed reality-based multi-view merging framework for immersive and intuitive telemanipulation of a complex mobile manipulator with integrated 3D/2D vision is presented. The proposed 3D immersive telerobotic schemes provide the users with depth perception through the merging of multiple 3D/2D views of the remote environment via MR subspace. The mobile manipulator platform can be effectively controlled by non-skilled operators who are physically separated from the robot working space through a velocity-based imitative motion mapping approach. Finally, this thesis presents an integrated mixed reality and haptic feedback scheme for intuitive and immersive teleoperation of robotic welding systems. By incorporating MR technology, the user is fully immersed in a virtual operating space augmented by real-time visual feedback from the robot working space. The proposed mixed reality virtual fixture integration approach implements hybrid haptic constraints to guide the operator’s hand movements following the conical guidance to effectively align the welding torch for welding and constrain the welding operation within a collision-free area. Overall, this thesis presents a complete tele-robotic application space technology using mixed reality and immersive elements to effectively translate the operator into the robot’s space in an intuitive and natural manner. The results are thus a step forward in cost-effective and computationally effective human-robot interaction research and technologies. The system presented is readily extensible to a range of potential applications beyond the robotic tele- welding and tele-manipulation tasks used to demonstrate, optimise, and prove the concepts

A Neuro-Expert Approach for Decision -Making in Welding Environment.

Decision making in welding is very important for achieving a good quality welded joint for the least possible cost. Of particular interest is decision making involving the selection of process, parameters, weld procedure specification, defect analysis and trouble shooting. This research has provided a means of capturing the planning knowledge in a Neuro-Expert System in a form that is capable of learning new information, correcting old information and automating the decision-making process in a welding environment. A strategy is formulated for the representation of knowledge in the form of a neural links and the translation of rules into neural link weights. After training those weights were converted back into rules to find out the inconsistent rules and capture new rules using a new approach. The various job variables affecting the process of welding are identified in detail and a Neuro-Expert system for the selection of process, parameters and weld procedure specification is developed. The neural networks are integrated with an expert system for decision making in welding environment. Apart from providing the initial parameters of welding, the expert system is used to validate the output of the neural network and served as a user-friendly interface for the neural network. Defect Analysis is performed in welding domain by mapping the welding parameters and defect patterns in a neural network. A neural network based approach for representing the knowledge in expert system is utilized for this purpose as the modification and updating of the knowledge was easier

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

An Investigation of the Perception of Professional Development among Mississippi\u27s Secondary Welding Teachers

This research study originated as a result of a paucity of information available regarding how secondary welding teachers in Mississippi perceive the value of professional development they have received within the previous two years. The purpose of this study was to examine the perceptions of Mississippi’s secondary welding teachers regarding how professional development had affected their teaching methods and collaboration with peers. Also, this study sought to determine whether the teachers had positive motivation in attending professional development activities, and how motivated they were to pursue their own professional development, other than school-mandated activities. Finally, the study examined the barriers teachers perceived to hinder them from pursuing their own professional development. The findings in this study revealed that Mississippi’s secondary welding teachers had a positive perception regarding how current professional development had changed their teaching methodology, student expectation, content comprehension, and confidence in teaching. Furthermore, respondents indicated that they had experienced enhanced collaboration with other welding teachers within the state as a result of professional development sessions; however, data revealed that collaboration between their academic counterparts was nearly nonexistent. Financial incentives and improving their teaching skill were found to be positive motivators for teachers. Personal costs, distance traveled to professional development sessions, and perceived value of professional development were determined to be barriers to attending professional development opportunities. It was recommended that future studies should include determining if welding teachers with welding certifications outperform teachers who do not have welding certifications, determine the consistency of laboratory equipment among school districts, whether the laboratory equipment in the local schools match those found in the actual employment environment, determine whether the teachers have the most up-to-date skills needed to match those skills found in industrial employment and investigate the perception of local businesses and industries about the quality of the student they have hired who graduated from Mississippi secondary welding programs. Lastly, it is recommended that administrators consider including academic teachers, career and technical teachers, and industry representatives in professional development activities to increase collaboration between stakeholders

Engineering Principles

Over the last decade, there has been substantial development of welding technologies for joining advanced alloys and composites demanded by the evolving global manufacturing sector. The evolution of these welding technologies has been substantial and finds numerous applications in engineering industries. It is driven by our desire to reverse the impact of climate change and fuel consumption in several vital sectors. This book reviews the most recent developments in welding. It is organized into three sections: “Principles of Welding and Joining Technology,” “Microstructural Evolution and Residual Stress,” and “Applications of Welding and Joining.” Chapters address such topics as stresses in welding, tribology, thin-film metallurgical manufacturing processes, and mechanical manufacturing processes, as well as recent advances in welding and novel applications of these technologies for joining different materials such as titanium, aluminum, and magnesium alloys, ceramics, and plastics