{"id":103441,"date":"2024-02-20T13:45:46","date_gmt":"2024-02-20T12:45:46","guid":{"rendered":"https:\/\/industry-science.com\/?page_id=103441"},"modified":"2024-05-13T20:07:07","modified_gmt":"2024-05-13T18:07:07","slug":"augmented-reality","status":"publish","type":"page","link":"https:\/\/industry-science.com\/en\/tools\/augmented-reality\/","title":{"rendered":"Augmented Reality"},"content":{"rendered":"\n\n\n
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\n \n \n \n \"Applied\n <\/picture>\n <\/div>\n
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Applied Knowledge and Augmented Reality<\/h4>\n
Bridging the gap between learning and application<\/div>
Jana Gonnermann-M\u00fcller<\/a> \n \"ORCID<\/a>, Philip Wotschack<\/a> \n \"ORCID<\/a>, Martin Krzywdzinski<\/a> \n \"ORCID<\/a>, Norbert Gronau<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n The increasing complexity of industrial environments demands new competencies from workers, particularly the ability to interact with advanced digital systems. Traditional training methods often fall short in supporting the effective transfer of applied knowledge to such contexts, and the effectiveness of this transfer, as measured by performance-based outcomes, remains to be investigated. To address this gap, the present study employed a between-subjects experimental design comparing augmented reality- and paper-based instructions within a realistic production training scenario. The results show that participants who learned with augmented reality completed the production process significantly faster and with fewer errors than those using paper instructions. In addition, learners using augmented reality reported higher usability and experienced lower cognitive load during training. These findings suggest that augmented reality can enhance the transfer of practical skills in industrial ... <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | 2025 | Edition 5 | Pages 22-29 | DOI 10.30844\/I4SE.25.5.22<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Enabling\n <\/picture>\n <\/div>\n
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Enabling the Future of Manufacturing with Digital Twins<\/h4>\n
Opportunities and obstacles<\/div>
Javad Ghofrani<\/a> \n \"ORCID<\/a>, Darian Lemke<\/a>, Tassilo S\u00f6ldner<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
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\n\t\t\t \n\t\t\t <\/div>Digital twins connect physical and digital systems, furthering efficiency, enabling predictive maintenance, and allowing the production of more customized products. Despite these advantages, challenges such as high costs, data synchronization, and security risks hinder widespread adoption. This article explores the potential of digital twins and examines key barriers to integration and implementation, also considering some industrial applications including additive manufacturing as a relevant use case. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | Edition 3 | Pages 72-81<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Digital\n <\/picture>\n <\/div>\n
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Digital Twins for Production<\/h4>\n
RAPIDZ \u2014 Resource analysis and process integration through digital twins<\/div>
Christian Salzig<\/a> \n \"ORCID<\/a>, Julia Burr<\/a> \n \"ORCID<\/a>, Sophie Hertzog<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n In today\u2019s manufacturing industry, digital twins are a key enabler for optimizing production processes and efficient resource use. However, creating digital twins is often associated with high or difficult-to-estimate costs and typically requires unknown characteristic values, such as material parameters, making practical implementation challenging. With RAPIDZ, we present a tool for creating and using digital twins that overcomes these barriers through its modular structure. The virtual modeling of physical systems enables comprehensive analysis and real-time forecasting of material flows, energy consumption and machine performance. The use of RAPIDZ increases production line efficiency, enhances flexibility and response time, and enables proactive maintenance to minimize downtime. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | Edition 3 | Pages 6-12 | DOI 10.30844\/I4SE.25.3.6<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Virtual\n <\/picture>\n <\/div>\n
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Virtual Exhibition as a Digital Twin<\/h4>\n
A framework for decision-making for virtual representations<\/div>
Isger Glauninger<\/a> \n \"ORCID<\/a>, Markus Sch\u00fcrmann<\/a>, Matthias M\u00fchl<\/a>, Christian van Husen<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
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\n\t\t\t \n\t\t\t <\/div>Transforming formats such as showrooms, laboratories or exhibitions into a virtual presence offers both opportunities and challenges. Particularly with cyber-physical systems (CPS), which rely heavily on user interaction, extensive adaptations must be made in order to maintain their purpose and function virtually. As part of this research project, digital solutions from different technologies and fields of application were transferred to a virtual exhibition. On this basis, the influence of the digital transformation on the interactivity and emulation of the solutions was analyzed. This article presents a framework that supports practitioners in the implementation of virtual representations. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | Edition 3 | Pages 110-116<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Digital\n <\/picture>\n <\/div>\n
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Digital Twins in Logistics<\/h4>\n
Opportunities and barriers during implementation<\/div>
Benjamin Gorgas<\/a> \n \"ORCID<\/a>, Jan Kliewer<\/a> \n \"ORCID<\/a>, Tobias Marc Wringe<\/a> \n \"ORCID<\/a>, Maximilian B\u00e4hring<\/a> \n \"ORCID<\/a>, Frank Straube<\/a> \n \"ORCID<\/a>, R\u00fcdiger Zarnekow<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Digital Twins offer great potential for increasing efficiency in logistics. Digital supply chain twins (DSCT) enable data-driven decisions and optimize processes at location and network level. A study conducted during an expert workshop shows that companies are interested in DSCT, but challenges such as data quality, cross-actor data exchange and interoperability are hindering their widespread implementation. While pilot projects exist, market penetration remains low. Successful implementation requires standardized interfaces and contractual frameworks for data exchange. As a result, DSCT can make logistics networks more resilient and sustainable in the long term. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | Edition 3 | Pages 34-40 | DOI 10.30844\/I4SE.25.3.34<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Training\n <\/picture>\n <\/div>\n
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Training in the Industrial Metaverse<\/h4>\n
Buzzword or opportunity?<\/div>
Leon Schellhammer<\/a> \n \"ORCID<\/a>, Lucas Waag<\/a>, Mert Cumert<\/a>, Dieter Uckelmann<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n
\n\t\t\t \n\t\t\t <\/div>Metaverse-based training programs offer a realistic and risk-free learning environment that is particularly valuable in industrial contexts, e.g. in immersive training and the simulation of workflows. Challenges remain in the areas of data protection, technological acceptance and integration into existing systems.\u00a0Using a carefully crafted questionnaire, four expert interviews were conducted to investigate whether the metaverse can innovate training programs effectively and lastingly. Its standardized format yields comparable, reliable data while allowing for an accurate evaluation of the results. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | 2025 | Edition 2 | Pages 102-108<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Cognitive\n <\/picture>\n <\/div>\n
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Cognitive Assistance Systems in Intralogistics<\/h4>\n
User studies with augmented reality and an AI chatbot<\/div>
Hendrik Stern<\/a> \n \"ORCID<\/a>, Michael Freitag<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Assistance systems improve work processes, shorten learning times and increase flexibility in the workplace. Human-centered, resilient and sustainable production approaches where user acceptance is of the utmost importance play a crucial role in the digitized Industry 5.0. Two user studies investigate how useful the support of technologies like augmented reality and AI chat actually is. In the context of cognitive assistance systems in intralogistics, artificial intelligence and augmented reality have a great potential and can contribute to an improvement in process performance. The usability of these systems in terms of human-centricity of Industry 5.0 is crucial. This article describes the results and findings of two user studies conducted in the laboratory for intralogistics work processes (picking and packing). The assistance systems used were evaluated using the System Usability Scale. \u00a0 Cognitive assistance systems in intralogistics Assistance systems make a ... <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 40 | 2024 | Edition 5 | Pages 67-72 | DOI 10.30844\/I4SE.24.5.66<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"secureAR\n <\/picture>\n <\/div>\n
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secureAR \u2013 An AR Platform for Industrial Manufacturing<\/h4>\n
Development and testing of an AR assistance system with consideration of cyber security<\/div>
Frank-Peter Schiefelbein<\/a>, Stefan Sigl<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n With its ability to integrate digital information into the real world, augmented reality (AR) is increasingly becoming a critical success factor when it comes to safe, efficient and human-centered manufacturing. However, the implementation of an AR project poses various challenges that can hinder its ability to succeed. A clear sequence of steps for implementing this technology is therefore essential. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 40 | 2024 | Edition 2 | Pages 64-71<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Digital\n <\/picture>\n <\/div>\n
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Digital Transformation for SMEs<\/h4>\n
Developing a roadmap for Industry 4.0 visions in small and medium-sized enterprises<\/div>
Robin Sutherland<\/a> \n \"ORCID<\/a>, Nicolas Wittine<\/a> \n \"ORCID<\/a>, Deike Gliem<\/a> \n \"ORCID<\/a>, Sigrid Wenzel<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Small and medium-sized enterprises still face the challenge of shaping their digital transformation. Maturity models offer a way to capture the situation within a company and support the formation of an Industry 4.0 vision. This paper presents a methodology that companies can use to develop a roadmap for shaping digital transformation by enabling the transfer of this vision into concrete decision-making steps. <\/div>\n <\/div>\n
Industrie 4.0 Management<\/strong> | Volume 39 | 2023 | Edition 4 | Pages 59-62 | DOI 10.30844\/IM_23-4_59-62<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"On-Site\n <\/picture>\n <\/div>\n
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On-Site BLE-Based Data Collection<\/h4>\n
Hendrik Jonitz<\/a>, Thomas Braml<\/a>, Eva-Maria Kern<\/a>, Marius Herzog<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
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\n\t\t\t \n\t\t\t <\/div>The increasing industrialization of the construction industry enables the implementation of a standardized process performance management, which can be used to analyze and control operational processes on construction sites [1]. This requires appropriate process data. The subject of this paper is the presentation of a structured procedure for process data collection based on Bluetooth Low Energy. The experiences gained in the course of field studies are used to derive opportunities and challenges and thus provide practical information on the use of BLE for process data collection. (Only in German) <\/div>\n <\/div>\n
Industrie 4.0 Management<\/strong> | Volume 39 | 2023 | Edition 3 | Pages 42-47<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n<\/div>\n\n
1<\/span>\n2<\/a>\n…<\/span>\n5<\/a>\n\u00bb<\/a><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":461,"featured_media":0,"parent":103435,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_uag_custom_page_level_css":"","footnotes":""},"class_list":["post-103441","page","type-page","status-publish","hentry"],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"front-page-entry":false,"post-entry":false,"post-teaser":false,"post-teaser-mobile":false,"post-custom-size":false,"whitepaper-teaser":false,"card-big":false,"card-portrait":false,"card-big-company":false,"gp-listing":false,"1536x1536":false,"2048x2048":false,"woocommerce_thumbnail":false,"woocommerce_single":false,"woocommerce_gallery_thumbnail":false,"dgwt-wcas-product-suggestion":false},"uagb_author_info":{"display_name":"Nimesh Patel","author_link":"https:\/\/industry-science.com\/en\/author\/nimesh\/"},"uagb_comment_info":0,"uagb_excerpt":null,"_links":{"self":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/pages\/103441","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/users\/461"}],"replies":[{"embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/comments?post=103441"}],"version-history":[{"count":1,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/pages\/103441\/revisions"}],"predecessor-version":[{"id":103442,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/pages\/103441\/revisions\/103442"}],"up":[{"embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/pages\/103435"}],"wp:attachment":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media?parent=103441"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}