A Novel Approach to the Holistic 3D Characterization of Weld Seams—Paving the Way for Deep Learning-Based Process Monitoring

In an industrial environment, the quality assurance of weld seams requires extensive efforts. The most commonly used methods for that are expensive and time-consuming destructive tests, since quality assurance procedures are difficult to integrate into production processes. Beyond that, available test methods allow only the assessment of a very limited set of characteristics. They are either suitable for determining selected geometric features or for locating and evaluating internal seam defects. The presented work describes an evaluation methodology based on microfocus X-ray computed tomography scans (µCT scans) which enable the 3D characterization of weld seams, including internal defects such as cracks and pores. A 3D representation of the weld contour, i.e., the complete geometry of the joint area in the component with all quality-relevant geometric criteria, is an unprecedented novelty. Both the dimensions of the weld seam and internal defects can be revealed, quantified with a resolution down to a few micrometers and precisely assigned to the welded component. On the basis of the methodology developed within the framework of this study, the results of the scans performed on the alloy AA 2219 can be transferred to other aluminum alloys. In this way, the data evaluation framework can be used to obtain extensive reference data for the calibration and validation of inline process monitoring systems employing Deep Learning-based data processing in the scope of subsequent work.

Manual metal arc welding of dissimilar 30MnB5 and S 235 low alloyed steels for agricultural applications

In agricultural mechanization industry, different types of materials are assembled with each other to establish agricultural machine systems. However, the necessity of joining dissimilar materials used in the same machine system may cause some problems. Joining two different materials by welding and selecting the most appropriate weld metal (electrode) for this is a very difficult problem. The increasing importance of the economic factors in today’s industry requires both the use of dissimilar materials in agricultural mechanization and the production of longer-lasting agricultural machines, thus making it necessary to use dissimilar steels in agricultural mechanization systems. Therefore, it is important to apply a welding process to dissimilar steels used in agricultural mechanization. In this study, 30MnB5/S235 steel pairs were joined by the manual metal arc welding (MMAW) method using different covered electrodes. In order to determine the mechanical properties of the welded samples, hardness, bending, and impact tests were carried out. In addition, visual inspection to the weld seams, liquid penetrant testing, and metal-lographic examinations to determine the microstructural properties were conducted. As a result of the microstructure studies, structures such as grain boundary ferrite, Widmanstätten ferrite, acicular ferrite, bainite, and martensite were determined in the weld metal and HAZs. As a result of the hardness test, the highest hardness values were determined in HAZs on the side of 30MnB5 steel. As a result of the bending test, the highest mechanical properties were obtained in the weld seams made with basic flux-cored wire. As a result of the notch impact test, the highest mechanical properties were obtained in the weld seams made with basic flux-cored wire, after the base metals.

A Novel Approach to the Holistic 3D Characterization of Weld Seams – Paving the Way for Deep Learning-Based Process Monitoring

In an industrial environment, the quality assurance of weld seams requires extensive efforts. The most commonly used methods for that are expensive and time-consuming destructive tests, since quality assurance procedures are difficult to integrate into production processes. Beyond that, available test methods allow only the assessment of a very limited set of characteristics. They are either suitable for determining selected geometric features or for locating and evaluating internal seam defects. The presented work describes an evaluation methodology based on microfocus X-ray computed tomography scans (µCT scans) which enable the 3D characterization of weld seams, including internal defects such as cracks and pores. A 3D representation of the weld contour, i.e., the complete geometry of the joint area in the component with all quality-relevant geometric criteria, is an unprecedented novelty. Both the dimensions of the weld seam and internal defects can be revealed, quantified with a resolution down to a few micrometers and precisely assigned to the welded component. On the basis of the methodology developed within the framework of this study, the results of the scans performed on the alloy AA 2219 can be transferred to other aluminum alloys. In this way, the data evaluation framework can be used to obtain extensive reference data for the calibration and validation of inline process monitoring systems employing Deep Learning-based data processing.

Secure and Privacy-Respecting Documentation for Interactive Manufacturing and Quality Assurance

The automated documentation of work steps is a requirement of many modern manufacturing processes. Especially when it comes to important procedures such as safety critical screw connections or weld seams, the correct and complete execution of certain manufacturing steps needs to be properly supervised, e.g., by capturing video snippets of the worker to be checked in hindsight. Without proper technical and organizational safeguards, such documentation data carries the potential for covert performance monitoring to the disadvantage of employees. Naïve documentation architectures interfere with data protection requirements, and thus cannot expect acceptance of employees. In this paper we outline use cases for automated documentation and describe an exemplary system architecture of a workflow recognition and documentation system. We derive privacy protection goals that we address with a suitable security architecture based on hybrid encryption, secret-sharing among multiple parties and remote attestation of the system to prevent manipulation. We finally contribute an outlook towards problems and possible solutions with regards to information that can leak through accessible metadata and with regard to more modular system architectures, where more sophisticated remote attestation approaches are needed to ensure the integrity of distributed components.

On the Application of Magnetoacoustic Emission for a Nondestructive Assessment of the Post Welding Heat Treatment of High Chromium Steel Weld Seams

The paper analyses the possibility of post weld heat treatment (PWHT) quality assessment with the help of magnetoacoustic emission (MAE) signal measurements. Two welded superheater tubes, made of high chromium VM12 steel, were analysed—as welded and heat treated one. The analysed sample in the as welded state exhibited significantly higher hardness, accompanied by a big difference in the MAE signal intensity (of order of about 50%). In order to explain that, the influence of tempering on the MAE signal intensity is demonstrated for the very similar X20CrMoV12.1 steel. It is shown that the observed increase of the MAE intensity as a function of annealing time is directly correlated with the change in hardness. The as described dependence allows to propose a method based on the MAE signal measurements as a new tool for the PWHT assessment.

Microstructural Stability of Extruded Mg-Mn-Ce Hollow Profiles with Weld Seams

Despite aluminum profiles, magnesium profiles have not been well developed due to the low formability. Furthermore, extruded magnesium profiles show a strong dependence on the mechanical properties, according to the loading direction. This is caused by a strong basal texture, which is directly dependent on the process parameters during the extrusion and the subsequent aging. Thus, the present paper focuses on the analysis of the microstructure and its evolution of extruded magnesium hollow profiles, which were subjected to a series of heat treatments at 475 °C up to one hour. The hollow profiles were extruded through a porthole die, thus, containing longitudinal weld seams. These were formed by material that underwent heavy shearing along the tool surface based on the friction conditions in the porthole die. Three extrusion ratios (ER = 8:1, ER = 16:1, ER = 30:1) were applied, resulting in three different wall thicknesses of the profiles. The microstructure of the profiles was analyzed using light-optical microscopy (LOM) and scanning electron microscopy (SEM) coupled with electron backscatter diffraction (EBSD). The analysis revealed no change of the microstructure of the profiles extruded at the two higher extrusion ratios within the time frame of the heat treatment. In contrast, the microstructure and, thus, the micro-texture of the profile with the lowest extrusion ratio (ER = 8:1) has been affected to a great extent. While only small changes in microstructure in the weld-free area were observed, the initial microstructure in the weld seam was transformed from fine recrystallized grains into a significantly bimodal microstructure mainly due to an abnormal grain growth (AGG). These changes were accompanied by a promotion of the rare-earth (RE) texture component for the weld-free material and a change of the overall texture from RE to a typical non-RE double fiber texture for the weld seam due to the intense AGG within the short-time heat treatments. In addition, the influence of the extrusion ratio on particle size and distribution as well as the character of the microstructure governing the behavior during heat treatments was analyzed and discussed.

Influence of competing notches on the fatigue strength of cut plate edges

Material fatigue is one of the elementary causes of damage in steel construction besides corrosion and abrasion. Design recommendations require that weld seams are placed in less stressed areas due to the crack-sensitive nature of the welded areas. As a result, unwelded areas of the components such as free cut plate edges gain technical and economic relevance as locations for potential fatigue cracks. In the metal processing industry, different thermal cutting processes are frequently used. During the process, unwanted boundary conditions can lead to undesired cuts in the component geometry during the cutting process. These process dysfunctions lead to incorrect components and to rejects. This article presents results of fatigue test data of oxy-fuel thermal cut edges of defect-free and faulty repair-welded samples to investigate the influence of competing notches on the cut edge. Specimens are made from construction steels S355N and S690Q of a 20-mm-thick plate. The presented data shows that the fatigue strength of the damaged cut edges can be recovered by the repair procedure and does not show any reduction of the fatigue strength due to the determined pores or other metallurgical notches of the repaired section.

Improving the tracking quality of the weld seam butt with V-form grooving by using Kalman filter and neural network

An algorithm for tracking of the welded seams grooving by using a Kalman filter based on six characteristic points of the profile obtained using the RF627 laser vision sensor is proposed. In order to reduce the error in weld seams control, a multilayer neural network with a backpropagation algorithm is created to compensate for errors caused by colored noise when using the Kalman filter. Experimental results show that when the algorithm is applied, the error in tracking the trajectory of weld seams is reduced. Keywords tracking of weld seams; multilayer/multi-pass welding; Kalman filter; multilayer perceptron