Welding Process Monitoring Applications and Industry 4.0

Benakis, Michalis; Du, Chunling; Patran, A.; French, Richard

doi:10.1109/coase.2019.8843319

Cited by 11 publications

(8 citation statements)

References 12 publications

(11 reference statements)

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“…Two photodiode sensors and two visual sensors were utilized [61]. Optical and infrared sensors are sensitive to capture plasma radiation signals and can reveal welding features like cooling rate temperature gradient and melt pool 3D geometry that other methods are unable to provide [62]. Artinov et al observe the weld pool geometry by means of a high-speed camera and an infrared camera recording.…”

Section: A Hybrid Data Collectionmentioning

confidence: 99%

“…On-line data bestow the required granularity for understanding and for managing larger complexity applications such as those pertaining to light-matter interaction of laser welding. When these various forms of energy emissions are captured in combination with real-time values of the essential variables, the process insights are even greater [62]. Furthermore, when these two sets are analyzed alongside historical laser welding data, then quality can be assured.…”

Section: Welding Procedures and Welder Qualificationsmentioning

confidence: 99%

“…Nodes of the welding network offer combined and through a cloud platform ubiquitous access to smart machines, production systems, and as well as a large amount of data [32]. Companies that can quickly adapt to the fast-moving pace of digital industrial ecosystems will stay competitive, whereas companies lose their customers when they cannot anticipate demands for connected products and services [62]. This construction should be included in a smart welding quality management system to facilitate new operating ways.…”

Section: Requirements Technical Challenges and Subcontractingmentioning

confidence: 99%

See 2 more Smart Citations

Development of an Intelligent Quality Management System for Micro Laser Welding: An Innovative Framework and Its Implementation Perspectives

Hoz

Cheng

2021

Machines

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Laser micro-welding manufacturers face substantial challenges in verifying weldment quality, as the industry and applications are requiring increasingly the miniaturization and compactness of products. The problem is compounded by new stringent demands for personalized products at competitive, low costs and the highest quality levels. High-pressure equipment manufacturers, in particular, rely on ISO 3834:2021 to assure and demonstrate best welding practices but also to manage risks associated with liability issues. ISO 3834:2021, like all conventional quality management systems, offers a one-dimensional, quasi-static overview of welding quality that may fail to deal with these new challenges and underlying complexities required to deal effectively with process variability. This paper presents a framework for welding companies to integrate horizontally their suppliers and customers with their processes and products, which are also integrated vertically in the context of Smart Manufacturing or Industry 4.0. It is focused on the development of a smart quality management system for intelligent digitization of all company manufacturing and business processes. Furthermore, an innovative data-based welding quality management framework is described for laser micro-welding applications and their implementation perspectives. The research is driven by an inductive methodology and based on a seamless integration of engineering-oriented heuristic and empirical approaches that is appropriate for intelligent and autonomous quality management, given the lack of research in this niche, but increasingly important topic area.

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Section: A Hybrid Data Collectionmentioning

confidence: 99%

Section: Welding Procedures and Welder Qualificationsmentioning

confidence: 99%

Section: Requirements Technical Challenges and Subcontractingmentioning

confidence: 99%

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Development of an Intelligent Quality Management System for Micro Laser Welding: An Innovative Framework and Its Implementation Perspectives

Hoz

Cheng

2021

Machines

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“…Over the past twenty years the fourth industrial revolution has accelerated, causing daily rapid changes and dismantling organizational silos. Engineering solutions and digital technology are being used to transform company models and production procedures [1,2]. With the use of technologies like the internet of things (IoT), big data, machine learning, cloud computing, cyber-security, robots, simulation, additive manufacturing, and extended reality (XR), among others, Industry 4.0 intends to turn conventional industries into intelligent ones [3].…”

Section: Introductionmentioning

confidence: 99%

Augmented Reality Based Training Module for IC Engine Assembly and Disassembly

Sundaram,

Gurusamy

2023

J. Phys.: Conf. Ser.

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Augmented reality (AR) technology has revolutionized various industries, including education and training. This paper proposes an AR-based training module for IC engine assembly and disassembly, which is aimed at providing an interactive and immersive learning experience to trainees. The module was developed using Solidworks for modeling, Blender for animation, and Unity for game development. Its primary objective is to help trainees improve their understanding and retention of complex procedures, thereby enhancing their technical skills, multi-step tasks, and product knowledge. Our approach intends to eliminate traditional paper-based instructions and replace them with AR-based ones, increasing maintenance efficiency and bridging the knowledge gap between OEMs and internal maintenance operators. The training module was designed for technicians and students who are learning how to assemble and disassemble engines. To make it more accessible and versatile, it was integrated with various devices, such as smartphones or tablets. This allows trainees to access the module from anywhere, at any time, and on any device, thus enabling remote learning. The module can be implemented in various settings, such as training centres, manufacturing facilities, or even through online platforms. Overall, this project represents a significant step forward in AR-based training modules for technical education. The module’s accessibility and versatility make it suitable for various settings, and its structured development process ensures that it is effective and reliable. The use of AR technology in education and training is an exciting field with tremendous potential, and this project demonstrates one of the many ways it can be applied to improve learning outcomes.

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“…The fourth industrial revolution has grown over the last two decades, making rapid changes day by day and removing silos within organization. The business models and manufacturing processes are transformed using digital technologies and through engineering solutions [1,2]. The factory of the future, enabled by the German initiative of Industry 4.0 (I4.0), places the human component at the center of the value chain [3].…”

Section: Introductionmentioning

confidence: 99%

MARMA: A Mobile Augmented Reality Maintenance Assistant for Fast-Track Repair Procedures in the Context of Industry 4.0

et al. 2020

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The integration of exponential technologies in the traditional manufacturing processes constitutes a noteworthy trend of the past two decades, aiming to reshape the industrial environment. This kind of digital transformation, which is driven by the Industry 4.0 initiative, not only affects the individual manufacturing assets, but the involved human workforce, as well. Since human operators should be placed in the centre of this revolution, they ought to be endowed with new tools and through-engineering solutions that improve their efficiency. In addition, vivid visualization techniques must be utilized, in order to support them during their daily operations in an auxiliary and comprehensive way. Towards this end, we describe a user-centered methodology, which utilizes augmented reality (AR) and computer vision (CV) techniques, supporting low-skilled operators in the maintenance procedures. The described mobile augmented reality maintenance assistant (MARMA) makes use of the handheld’s camera and locates the asset on the shop floor and generates AR maintenance instructions. We evaluate the performance of MARMA in a real use case scenario, using an automotive industrial asset provided by a collaborative manufacturer. During the evaluation procedure, manufacturer experts confirmed its contribution as an application that can effectively support the maintenance engineers.

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Welding Process Monitoring Applications and Industry 4.0

Abstract: This is a repository copy of Welding process monitoring applications and industry 4.0.

Cited by 11 publications

References 12 publications

Development of an Intelligent Quality Management System for Micro Laser Welding: An Innovative Framework and Its Implementation Perspectives

Development of an Intelligent Quality Management System for Micro Laser Welding: An Innovative Framework and Its Implementation Perspectives

Augmented Reality Based Training Module for IC Engine Assembly and Disassembly

MARMA: A Mobile Augmented Reality Maintenance Assistant for Fast-Track Repair Procedures in the Context of Industry 4.0

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