Special Issue "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: 30 December 2021.

Special Issue Editors

Prof. Dr. Manuel Rodríguez-Martín
E-Mail Website
Guest Editor
Department of Mechanical Engineering, Universidad de Salamanca, Av. Fernando Ballesteros, 0, 37700 Béjar, Salamanca, Spain
Interests: quality control; metrology; maintenance; mechanical engineering; non-destructive testing; standards of quality of materials, manufacturing, testing, and occupational risk prevention

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

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

Article
Analysis of Acoustic Emission (AE) Signals for Quality Monitoring of Laser Lap Microwelding
Appl. Sci. 2021, 11(15), 7045; https://doi.org/10.3390/app11157045 - 30 Jul 2021
Viewed by 212
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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Article
A Rule-Based System to Promote Design for Manufacturing and Assembly in the Development of Welded Structure: Method and Tool Proposition
Appl. Sci. 2021, 11(5), 2326; https://doi.org/10.3390/app11052326 - 05 Mar 2021
Cited by 1 | Viewed by 431
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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