The Application of Augmented Reality Technology in the Production Processes

Szajna, Andrzej; Szajna, Janusz; Stryjski, Roman; Sąsiadek, Michał; Woźniak, W

doi:10.1007/978-3-319-97490-3_31

Cited by 11 publications

(17 citation statements)

References 6 publications

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“…One of the latest examples of improvement in this specific production process is the EPLAN Smart Wiring (ESW) system, which is a touchscreen application that guides an employee, step by step, through the whole wire assembly process of the control cabinet. For the most advanced and automated version of the production process, which includes all the wires being preproduced to the unique, exact length, the ESW system provides a search window to identify which wire on the application list is the one held by an employee [8][9][10].…”

Section: Shaping the Solutions For Wire Assembly Process Of The Control Cabinetsmentioning

confidence: 99%

Application of the Deep CNN-Based Method in Industrial System for Wire Marking Identification

et al. 2021

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Industry 4.0, a term invented by Wolfgang Wahlster in Germany, is celebrating its 10th anniversary in 2021. Still, the digitalization of the production environment is one of the hottest topics in the computer science departments at universities and companies. Optimization of production processes or redefinition of the production concepts is meaningful in light of the current industrial and research agendas. Both the mentioned optimization and redefinition are considered in numerous subtopics and technologies. One of the most significant topics in these areas is the newest findings and applications of artificial intelligence (AI)—machine learning (ML) and deep convolutional neural networks (DCNNs). The authors invented a method and device that supports the wiring assembly in the control cabinet production process, namely, the Wire Label Reader (WLR) industrial system. The implementation of this device was a big technical challenge. It required very advanced IT technologies, ML, image recognition, and DCNN as well. This paper focuses on an in-depth description of the underlying methodology of this device, its construction, and foremostly, the assembly industrial processes, through which this device is implemented. It was significant for the authors to validate the usability of the device within mentioned production processes and to express both advantages and challenges connected to such assembly process development. The authors noted that in-depth studies connected to the effects of AI applications in the presented area are sparse. Further, the idea of the WLR device is presented while also including results of DCNN training (with recognition results of 99.7% although challenging conditions), the device implementation in the wire assembly production process, and its users’ opinions. The authors have analyzed how the WLR affects assembly process time and energy consumption, and accordingly, the advantages and challenges of the device. Among the most impressive results of the WLR implementation in the assembly process one can be mentioned—the device ensures significant process time reduction regardless of the number of characters printed on a wire.

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Section: Shaping the Solutions For Wire Assembly Process Of The Control Cabinetsmentioning

confidence: 99%

Application of the Deep CNN-Based Method in Industrial System for Wire Marking Identification

et al. 2021

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“…Szajna A. (Szajna et al, 2019 [ 34 ]) effectuates the development of the software, which synchronizes the ESW 3D graphics with the image being seen in the AR glasses, towards the elimination of physical markers and application of recent methods in machine learning, precisely, feature learning and deep learning (Quoc et al, 2012 [ 53 ]), representing the breakthrough approach in AI (Hinton et al, 2006 [ 54 ]; Bengio and LeCun, 2007 [ 55 ]). The creation of two-dimensional and three-dimensional representations displayed by the AR glasses used in the presented research, is a fusion of Unity (a cross-platform software engine developed by Unity Technologies), open-source modules and libraries, merged with the proprietary software aided by deep learning technology.…”

Section: The Assumptions Principles and Aims Of The Ar Support Smentioning

confidence: 99%

“…Szajna A. (Szajna et al, 2019 [ 34 ]) expects to provide the ability of the system to automatically recognize a whole control cabinet and its individual components, viewed directly through the AR glasses in the actual environment. Such improvement is expected to allow the elimination of one of the steps from the control cabinet production operation, namely the need to attach physical markers to every single control cabinet.…”

Section: The Assumptions Principles and Aims Of The Ar Support Smentioning

confidence: 99%

“… Visualization of the production station with the DTPoland AR Smart Wiring 4.0 prototype system. Source: based on Szajna et al (2019) [ 34 ] with the necessary upgrade included. …”

Section: Figurementioning

confidence: 99%

“…The solution was described to some extent in 2018, together with a brief description of AR technology (Szajna et al, 2019) [ 34 ]. This paper is a continuation of the abovementioned research, enriched with the validation and test study.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessment of Augmented Reality in Manual Wiring Production Process with Use of Mobile AR Glasses

Szajna

Stryjski

Woźniak

et al. 2020

Sensors

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Digitalization of production environment, also called Industry 4.0 (the term invented by Wahlster Wolfgang in Germany) is now one of the hottest topics in the computer science departments at universities and companies. One of the most significant topics in this area is augmented reality (AR). The interest in AR has grown especially after the introduction of the Microsoft HoloLens in 2016, which made this technology available for researchers and developers all around the world. It is divided into numerous subtopics and technologies. These wireless, see-through glasses give a very natural human-machine interface, with the possibility to present certain necessary information right in front of the user’s eyes as 3D virtual objects, in parallel with the observation of the real world, and the possibility to communicate with the system by simple gestures and speech. Scientists noted that in-depth studies connected to the effects of AR applications are presently sparse. In the first part of this paper, the authors recall the research from 2019 about the new method of manual wiring support with the AR glasses. In the second part, the study (tests) for this method carried out by the research team is described. The method was applied in the actual production environment with consideration of the actual production process, which is manual wiring of the industrial enclosures (control cabinets). Finally, authors deliberate on conclusions, technology’s imperfections, limitations, and future possible development of the presented solution.

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