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Quality Control in Welding

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 14393

Special Issue Editors


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Guest Editor
Department of Mechanical Engineering, Universidad de Salamanca, Av. Fernando Ballesteros, 0, 37700 Béjar, Spain
Interests: quality control; metrology; maintenance; mechanical engineering; non-destructive testing; standards of quality of materials, manufacturing, testing, and occupational risk prevention
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Guest Editor
Department of Mining Technology, Topography and Structures, University of León, Avda. Astorga, s/n, 24401 Ponferrada, Spain
Interests: photogrammetry; drones; laser scanning; radiometric calibration; remote sensing; RGB-D sensors; 3D modeling; mobile mapping
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Welding is the most widely used metal bonding method in engineering and construction. Pipes, machine components, structural systems, and other elements that are commonly used in civil and mechanical engineering have welded parts or elements. Many of the welded joints can withstand high mechanical stresses and their integrity lies in the safety of many machines and structures. The simple failure of a weld may be due to small discontinuities or superficial or internal defects that are sometimes difficult to see; thus, the quality controls are very strict and highly standardized by a wide range of international regulations that are mandatory in most cases. Non-destructive welding tests (NDT) are of great importance in the field of quality control, mainly due to their potential to detect defects or discontinuities in most materials without causing damage to the machine and facilities.

The increase in the requirements of security, precision, and completeness related to quality control in welded joints is pushing the scientific community, as well as companies, to propose innovative solutions, ranging from new hardware/software approaches and integration with other devices to the adoption and development of artificial intelligence methods for the automatic extraction of salient features and quality assessment for performance verification.

The aim of the present Special Issue is to cover the relevant topics and trends in “Quality Control in Welding” and to introduce the new tendencies in the application of novelty techniques for quality assurance in welding. Real-time monitoring, active thermography, structured light systems, photogrammetry, phase-array ultrasounds, and deep and machine learning are just some examples of innovative research topics that are currently being developed and improved.

Therefore, we invite you to submit research articles, experimental work, reviews, and/or case studies related to this topic. Contributions may include, but are not limited to, the following topics:

  • 3D documentation techniques;
  • Accuracy, precision and quality assessment
  • Active/passive thermography;
  • Civil Structures
  • Corrosion studies;
  • Data and sensor fusion;
  • Deep learning/machine learning;
  • Destructive testing;
  • Electromagnetic tests;
  • Feature extraction;
  • Laser scanning;
  • Maintenance issues;
  • Welding materials;
  • Metrology;
  • Non-destructive testing (NDT);
  • Optical and thermal methods;
  • Point cloud processing: filtering, segmentation, classification, modelling;
  • Radiography;
  • Real time monitoring;
  • Sensor design and platform developments;
  • Simulation of welding and joining processes;
  • Structural health monitoring;
  • Structured light;
  • Ultrasonic;
  • Verification and validation.

Prof. Dr. Manuel Rodríguez-Martín
Dr. Pablo Rodríguez-Gonzálvez
Guest Editors

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Published Papers (4 papers)

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Research

14 pages, 3937 KiB  
Article
WELDMAP: A Photogrammetric Suite Applied to the Inspection of Welds
by Esteban Ruiz de Oña, Manuel Rodríguez-Martin, Pablo Rodríguez-Gonzálvez, Rocio Mora and Diego González-Aguilera
Appl. Sci. 2022, 12(5), 2553; https://doi.org/10.3390/app12052553 - 28 Feb 2022
Cited by 1 | Viewed by 2737
Abstract
This paper presents a new tool for external quality control in welds using close-range photogrammetry. The main contribution of the developed approach is the automatic assessment of welds based on 3D photogrammetric models, enabling objective and accurate analyses through an in-house tool that [...] Read more.
This paper presents a new tool for external quality control in welds using close-range photogrammetry. The main contribution of the developed approach is the automatic assessment of welds based on 3D photogrammetric models, enabling objective and accurate analyses through an in-house tool that was developed, WELDMAP. As a result, inspectors can perform external quality control of welds in a simple and efficient way without requiring visual inspections or external tools, and thus avoiding the subjectivity and imprecisions of the classical protocol. The tool was validated with a large dataset in laboratory tests as well as in real scenarios. Full article
(This article belongs to the Special Issue Quality Control in Welding)
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15 pages, 3741 KiB  
Article
Parametric Optimization of the GMAW Welding Process in Thin Thickness of Austenitic Stainless Steel by Taguchi Method
by Glauco Nobrega, Maria Sabrina Souza, Manuel Rodríguez-Martín, Pablo Rodríguez-Gonzálvez and João Ribeiro
Appl. Sci. 2021, 11(18), 8742; https://doi.org/10.3390/app11188742 - 19 Sep 2021
Cited by 13 | Viewed by 3330
Abstract
In the present work, an analysis of different welding parameters was carried out on the welding of stainless-steel thin thickness tubes by the Gas Metal Arc Welding (GMAW) process. The influence of three main parameters, welding voltage, movement angle, and welding current in [...] Read more.
In the present work, an analysis of different welding parameters was carried out on the welding of stainless-steel thin thickness tubes by the Gas Metal Arc Welding (GMAW) process. The influence of three main parameters, welding voltage, movement angle, and welding current in the quality of the welds, was studied through a specifically designed experimental process based on the establishment of three different levels of values for each of these parameters. Weld quality is evaluated using destructive testing (macrographic analysis). Specifically, the width and root penetration of the weld bead were measured; however, some samples have been disregarded due to welding defects outside the permissible range or caused by excessive melting of the base metals. Data are interpreted, discussed, and analyzed using the Taguchi method and ANOVA analysis. From the analysis of variance, it was possible to identify the most influential parameter, the welding voltage, with a contribution of 43.55% for the welding penetration and 75.26% for the bead width, which should be considered in the designs of automatic welding processes to improve the quality of final welds. Full article
(This article belongs to the Special Issue Quality Control in Welding)
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13 pages, 4710 KiB  
Article
Analysis of Acoustic Emission (AE) Signals for Quality Monitoring of Laser Lap Microwelding
by Ming-Chyuan Lu, Shean-Juinn Chiou, Bo-Si Kuo and Ming-Zong Chen
Appl. Sci. 2021, 11(15), 7045; https://doi.org/10.3390/app11157045 - 30 Jul 2021
Cited by 10 | Viewed by 2485
Abstract
In this study, the correlation between welding quality and features of acoustic emission (AE) signals collected during laser microwelding of stainless-steel sheets was analyzed. The performance of selected AE features for detecting low joint bonding strength was tested using a developed monitoring system. [...] Read more.
In this study, the correlation between welding quality and features of acoustic emission (AE) signals collected during laser microwelding of stainless-steel sheets was analyzed. The performance of selected AE features for detecting low joint bonding strength was tested using a developed monitoring system. To obtain the AE signal for analysis and develop the monitoring system, lap welding experiments were conducted on a laser microwelding platform with an attached AE sensor. A gap between the two layers of stainless-steel sheets was simulated using clamp force, a pressing bar, and a thin piece of paper. After the collection of raw signals from the AE sensor, the correlations of welding quality with the time and frequency domain features of the AE signals were analyzed by segmenting the signals into ten 1 ms intervals. After selection of appropriate AE signal features based on a scatter index, a hidden Markov model (HMM) classifier was employed to evaluate the performance of the selected features. Three AE signal features, namely the root mean square (RMS) of the AE signal, gradient of the first 1 ms of AE signals, and 300 kHz frequency feature, were closely related to the quality variation caused by the gap between the two layers of stainless-steel sheets. Classification accuracy of 100% was obtained using the HMM classifier with the gradient of the signal from the first 1 ms interval and with the combination of the 300 kHz frequency domain signal and the RMS of the signal from the first 1 ms interval. Full article
(This article belongs to the Special Issue Quality Control in Welding)
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34 pages, 9436 KiB  
Article
A Rule-Based System to Promote Design for Manufacturing and Assembly in the Development of Welded Structure: Method and Tool Proposition
by Claudio Favi, Roberto Garziera and Federico Campi
Appl. Sci. 2021, 11(5), 2326; https://doi.org/10.3390/app11052326 - 5 Mar 2021
Cited by 13 | Viewed by 4167
Abstract
Welding is a consolidated technology used to manufacture/assemble large products and structures. Currently, welding design issues are tackled downstream of the 3D modeling, lacking concurrent development of design and manufacturing engineering activities. This study aims to define a method to formalize welding knowledge [...] Read more.
Welding is a consolidated technology used to manufacture/assemble large products and structures. Currently, welding design issues are tackled downstream of the 3D modeling, lacking concurrent development of design and manufacturing engineering activities. This study aims to define a method to formalize welding knowledge that can be reused as a base for the development of an engineering design platform, applying design for assembly method to assure product manufacturability and welding operations (design for welding (DFW)). The method of ontology (rule-based system) is used to translate tacit knowledge into explicit knowledge, while geometrical feature recognition with parametric modeling is adopted to couple geometrical information with the identification of welding issues. Results show how, within the design phase, manufacturing issues related to the welding operations can be identified and fixed. Two metal structures (a jack adapter of a heavy-duty prop and a lateral frame of a bracket structure) fabricated with arc welding processes were used as case studies and the following benefits were highlighted: (i) anticipation of welding issues related to the product geometry and (ii) reduction of effort and time required for the design review. In conclusion, this research moves forward toward the direction of concurrent engineering, closing the gap between design and manufacturing. Full article
(This article belongs to the Special Issue Quality Control in Welding)
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