Process control for WAAM using computer vision

This study is mainly about the vision system and control algorithm programming for wire arc additive manufacturing (WAAM). Arc additive manufacturing technology is formed by the principle of heat source cladding produced by welders using molten inert gas shielded welding (MIG), tungsten inert gas shielded welding (TIG) and layered plasma welding power supply (PA). It has high deposition efficiency, short manufacturing cycle, low cost, and easy maintenance. Although WAAM has very good uses in various fields, the inability to control the adding process in real time has led to defects in the weld and reduced quality. Therefore, it is necessary to develop the real-time feedback through computer vision and algorithms for WAAM to ensure that the thickness and the width of each layer during the addition process are the same

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

Welding Processes

Despite the wide availability of literature on welding processes, a need exists to regularly update the engineering community on advancements in joining techniques of similar and dissimilar materials, in their numerical modeling, as well as in their sensing and control. In response to InTech's request to provide undergraduate and graduate students, welding engineers, and researchers with updates on recent achievements in welding, a group of 34 authors and co-authors from 14 countries representing five continents have joined to co-author this book on welding processes, free of charge to the reader. This book is divided into four sections: Laser Welding; Numerical Modeling of Welding Processes; Sensing of Welding Processes; and General Topics in Welding

Towards the Fabrication Strategies for Intelligent Wire Arc Additive Manufacturing of Wire Structures from CAD Input to Finished Product

With the increasing demand for freedom of part design in the industry, additive manufacturing (AM) has become a vital fabrication process for manufacturing metallic workpieces with high geometrical complexity. Among all metal additive manufacturing technologies, wire arc additive manufacturing (WAAM), which uses gas metal arc welding (GMAW), is gaining popularity for rapid prototyping of sizeable metallic workpieces due to its high deposition rate, low processing conditions limit, and environmental friendliness. In recent years, WAAM has been developed synergistically with industrial robotic systems or CNC machining centers, enabling multi-axis free-form deposition in 3D space. On this basis, the current research of WAAM has gradually focused on fabricating strut-based wire structures to enhance its capability of producing low-fidelity workpieces with high spatial complexity. As a typical wire structure, the large-size free-form lattice structure, featuring lightweight, superior energy absorption, and a high strength-weight ratio, has received extensive attention in developing its WAAM fabrication process. However, there is currently no sophisticated WAAM system commercially available in the industry to implement an automated fabrication process of wire or lattice structures. The challenges faced in depositing wire structures include the lack of methods to effectively identify individual struts in wire structures, 3D slicing algorithms for the whole wire structures, and path planning algorithms to establish reasonable deposition paths for these generated discrete sliced layers. Moreover, the welded area of the struts within the wire structure is relatively small, so the strut forming is more sensitive and more easily affected by the interlayer temperature. Therefore, the control and prediction of strut formation during the fabricating process is still another industry challenge. Simultaneously, there is also an urgent need to improve the processing efficiency of these structures while ensuring the reliability of their forming result

Machine Learning Based Defect Detection in Robotic Wire Arc Additive Manufacturing

In the last ten years, research interests in various aspects of the Wire Arc Additive Manufacturing (WAAM) processes have grown exponentially. More recently, efforts to integrate an automatic quality assurance system for the WAAM process are increasing. No reliable online monitoring system for the WAAM process is a key gap to be filled for the commercial application of the technology, as it will enable the components produced by the process to be qualified for the relevant standards and hence be fit for use in critical applications in the aerospace or naval sectors. However, most of the existing monitoring methods only detect or solve issues from a specific sensor, no monitoring system integrated with different sensors or data sources is developed in WAAM in the last three years. In addition, complex principles and calculations of conventional algorithms make it hard to be applied in the manufacturing of WAAM as the character of a long manufacturing cycle. Intelligent algorithms provide in-built advantages in processing and analysing data, especially for large datasets generated during the long manufacturing cycles. In this research, in order to establish an intelligent WAAM defect detection system, two intelligent WAAM defect detection modules are developed successfully. The first module takes welding arc current / voltage signals during the deposition process as inputs and uses algorithms such as support vector machine (SVM) and incremental SVM to identify disturbances and continuously learn new defects. The incremental learning module achieved more than a 90% f1-score on new defects. The second module takes CCD images as inputs and uses object detection algorithms to predict the unfused defect during the WAAM manufacturing process with above 72% mAP. This research paves the path for developing an intelligent WAAM online monitoring system in the future. Together with process modelling, simulation and feedback control, it reveals the future opportunity for a digital twin system

Effects of part-to-part gap and the direction of welding on laser welding quality

Engineering & Systems DesignThe use of laser welding has become quite widespread because it can achieve higher productivity than spot welding. This is due to its desirable features, which include high power density, faster welding speed, highly accurate welding, and excellent repeatability. In addition, laser welding can minimize the distortion in heat-affected zones (HAZs), and there is no tooling that wears out or must be changed over. In spite of these advantages, laser welding still causes many problems when used on compositions such as galvanized steel and aluminum alloy. Galvanized steel, for example, is composed of a zinc layer whose physical parameters differ from those of steel as a base material. Zinc vaporizes at a temperature of 907 K, whereas steel begins to melt at 1510 K. This phenomenon causes serious defects in welds because the pressure of zinc is more powerful than that of steel. As a result, a certain manipulable control is needed in order for the zinc coating to be able to evaporate. To prevent this circumstance, the following solutions have been proposed: (i) a de-gassing method that induces the zinc fumes to escape from the part-to-part gap between two materials; (ii) the removal of zinc layers that will be joined together; (iii) a pulsed laser method that minimizes zinc vaporization using a high energy per pulse and a short pulse duration; (iv) a laser hybrid method; and (v) the addition of additional elements to the surface, which form a compound with the vaporizing zinc. Despite these suggestions, applications involving zinc-coated steels are rarely used in the automotive industry because the shapes of the materials to be welded are not always uniform. In this study, we ascertain the effects of the part-to-part gap and the direction of welding on the quality of laser welding. Using a 2 kW fiber laser and galvanized steel sheets (with thicknesses of 1.4 mm and 1.8 mm), our experiments employed lap welding, which has been applied to side members in the automotive industry. The experimental design was used with a 33 factorial design with 3 replications. The three types of welding direction used are ascendance, descendance, and a uniform gap. Based on the experiments, using analysis of variance (ANOVA) it was determined that the direction of welding is an important factor that can affect the weld quality. In addition, the differences between the shear tensile strengths in the ascendance and descendance directions were determined using a t-Test. The maximum shear tensile strength in the ascendance direction was achieved with a laser power of 2000 W and a welding speed of 2100 mm/min, followed by a part-to-part gap of 0.32 mm/min as the steepest ascent method. Moreover, we analyzed cross-sections of sampling specimens, varying the gap differences in order to verify the differences in shear tensile strength based on two different directions of welding.ope

Open-Source TIG-Based Metal 3D-Printing

Metal 3-D printing has been relegated to high-cost proprietary high-resolution systems and low-resolution low-cost metal inert gas (MIG) systems. In order to provide a path to high-resolution, low-cost, metal 3-D printing, this manuscript proposes a new open source metal 3-D printer design based around a low-cost tungsten inert gas (TIG) welder coupled to a commercial open source self replicating rapid prototyper. Optimal printing parameters for the machine are acquired using a novel computational intelligence software. TIG has many advantages over MIG, such as having a low heat input, clean beads, and the potential for both high-resolution prints as well as insitu alloying of complex geometries. The design can be adapted to most RepRap-class systems and has a basic yet powerful free and open source software (FOSS) package for the characterization of the 3-D printer. This system can be used for fabricating custom metal scientific components and tools, near net-shape structural metal component rapid prototyping, adapting and depositing on existing metal structures, and is deployable for in-field prototyping for appropriate technology applications

Advanced titanium welding in particle physics and aerospace engineering

The quest for answers that will unlock the mysteries of the cosmos and broaden our perception and understanding of the physical laws that govern the universe, demands studying particle collisions of high energies at particle accelerators. Monitoring of these collisions requires complex detectors whose development pushes the boundaries of engineering. In the present study advanced titanium welding is explored in the development of the new ATLAS Inner Tracker detector to be installed in line with the High-Luminosity Large Hadron Collider at CERN. Pulsed welding currents are employed to join thin titanium pipes used in the detector’s evaporative CO2 cooling system. The benefits of the low heat input enabled by the welding process are utilised in the repair and remanufacturing industry of aerospace applications. Wire arc additive manufacturing is applied in the regeneration of aerospace components providing successive material deposition on a layer-upon-layer manner. To this extent investigations and implementations related to Pulsed Gas Tungsten Arc Welding are explored in the presented work aiming to further understand, implement and advance the welding process. Assurance of the weld quality is furthered studied, as the outcome of the process depends on maintaining input parameters and welding conditions at optimum levels for the whole duration of the process. By implementing process monitoring methodologies, invaluable data are recorded whose analysis can be utilised in the detection of process disturbances and weld quality assessment

NASA Tech Briefs, December 1990

Topics: New Product Ideas; NASA TU Services; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Sciences; Life Sciences

Additive Manufacturing Research and Applications

This Special Issue book covers a wide scope in the research field of 3D-printing, including: the use of 3D printing in system design; AM with binding jetting; powder manufacturing technologies in 3D printing; fatigue performance of additively manufactured metals, such as the Ti-6Al-4V alloy; 3D-printing methods with metallic powder and a laser-based 3D printer; 3D-printed custom-made implants; laser-directed energy deposition (LDED) process of TiC-TMC coatings; Wire Arc Additive Manufacturing; cranial implant fabrication without supports in electron beam melting (EBM) additive manufacturing; the influence of material properties and characteristics in laser powder bed fusion; Design For Additive Manufacturing (DFAM); porosity evaluation of additively manufactured parts; fabrication of coatings by laser additive manufacturing; laser powder bed fusion additive manufacturing; plasma metal deposition (PMD); as-metal-arc (GMA) additive manufacturing process; and spreading process maps for powder-bed additive manufacturing derived from physics model-based machine learning