{"id":103484,"date":"2024-02-20T14:18:39","date_gmt":"2024-02-20T13:18:39","guid":{"rendered":"https:\/\/industry-science.com\/?page_id=103484"},"modified":"2024-05-14T04:52:45","modified_gmt":"2024-05-14T02:52:45","slug":"services","status":"publish","type":"page","link":"https:\/\/industry-science.com\/en\/management\/services\/","title":{"rendered":"Services"},"content":{"rendered":"\n\n\n
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\n \n \n \n \"Customized\n <\/picture>\n <\/div>\n
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Customized Organs from Space<\/h4>\n
How weightlessness could change human lives<\/div> <\/td>\n <\/tr>\n <\/table>\n
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\n\t\t\t \n\t\t\t <\/div>\nDue to its weightlessness, space offers enormous opportunities for production. The unique conditions of microgravity, for example, can simplify the development of organs and tissues from the body's own stem cells, allowing therapies to be developed in a more targeted manner. Even though many independent initiatives are currently emerging to explore this and other potential applications, their success is not a foregone conclusion. <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Bridging\n <\/picture>\n <\/div>\n
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Bridging Knowledge Gaps with GenAI in Industrial Maintenance<\/h4>\n
Specific needs and contextualized solutions<\/div>
Uta Wilkens<\/a> \n \"ORCID<\/a>, Julian Polte<\/a> \n \"ORCID<\/a>, Philipp Lelidis<\/a>, Eckart Uhlmann<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n The paper specifies the genAI support needs for industrial maintenance against the background of a sociotechnical systems perspective. Emphasizing two needs, accessing implicit operator knowledge and prioritizing complex regulatory knowledge, a multi-layer architecture is outlined for an AI-based context-sensitive maintenance assistance system (MAS). The main purpose is to bridge knowledge gaps with genAI if human expertise and human implicit knowledge are not available and to cope with sub-process-specific challenges of multiple regulations. The MAS facilitates access to technical knowledge, distributes expertise, and shares implicit knowledge of experienced operators across different layers of information processing. The approach goes beyond standardization and has a high potential to enhance organizational as well as individual resilience. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | 2025 | Edition 5 | Pages 50-57 | DOI 10.30844\/I4SE.25.5.50<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Smart\n <\/picture>\n <\/div>\n
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Smart Business Models in Intralogistics<\/h4>\n
A service-oriented approach to customized logistics solutions<\/div>
Anja Wiebusch<\/a>, Niklas Wilkowski<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Equipment-as-a-Service (EaaS) enables logistics companies to offer their customers tailored solutions, helping them to remain flexible and reduce costs as well as risks even in difficult times. Customers no longer pay for the object itself but only for the service provided, such as the usage time of a forklift truck. This allows them to focus on their core competencies and convert high investment costs into more flexible operating costs [1]. High capital commitment and the risk of underutilization of machines can thus be avoided and transferred to the logistics provider. This article examines the adjustments that logistics providers must make to accommodate this business model as well as some possible use cases. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | Edition 4 | Pages 30-35<\/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 \"Hybrid\n <\/picture>\n <\/div>\n
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Hybrid Learning Landscapes for Technical Concepts<\/h4>\n
The digitalization of training via practical concepts and targeted networking<\/div>
Sebastian Anselmann<\/a> \n \"ORCID<\/a>, Jessica W\u00e4dt<\/a>, Uwe Fa\u00dfhauer<\/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>The L\u00e4nder- und Phasen\u00fcbergreifende Interface (LPI) (engl. Cross-Regional and Cross-Phase Interface) promotes the sustainable digitalization of vocational and technical education through the systematic provision of expertise and innovative networking formats. The focus is on hybrid learning landscapes (HLL), which interlink physical and digital learning spaces to create individualized, practical learning environments. Innovative approaches such as learning factories, VR\/AR and learning analytics are integrated. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | Edition 3 | Pages 126-132<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Collaborative\n <\/picture>\n <\/div>\n
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Collaborative Drone Inspection<\/h4>\n
A new approach to inspection work with AI support<\/div>
Till Becker<\/a>, Agron Neziraj<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Drone technology and the use of artificial intelligence (AI) offer promising advantages in various sectors, including in inspection. The use of innovative inspection technologies can make inspections more efficient overall. This research project examines various legal and economic aspects of AI-based autonomous drone inspections. It also develops a target process that represents the use of an AI-based drone inspection and controls the use of such inspection technology. In particular, this article focuses on a collaborative approach to this new inspection methodology. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | Edition 2 | Pages 94-100<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Distributed\n <\/picture>\n <\/div>\n
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Distributed Application Integration in Industry<\/h4>\n
Employing microservices for enterprise application integration (EAI)<\/div>
Jan-Peer Rudolph<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n In line with current digital transformations, the number of software applications in use by companies is continuously increasing. This particularly affects industrial enterprises, which face challenges due to their often complex business processes. A holistic and sustainable integration of these business processes requires a strong link between the different information systems used. In this context, application integration, also known as enterprise application integration (EAI), is becoming more important. Modern approaches such as the use of microservices offer a particularly flexible and efficient solution for seamlessly connecting different applications and thus promoting the agility and scalability of a company\u2019s IT landscape. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | 2025 | Edition 1 | Pages 74-80<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Cloud-Agnostic\n <\/picture>\n <\/div>\n
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Cloud-Agnostic Platform-as-a-Service (PaaS)<\/h4>\n
An approach to prevent vendor lock-in<\/div>
Jens Kohler<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Modern cloud architectures benefit, among other things, from improved availability due to different cloud locations and greater flexible scalability due to the theoretically unlimited computing power of the cloud. However, in addition to challenges regarding data protection and data security, companies are increasingly concerned about the growing dependency on their cloud provider. In this article, we present a prototype implementation for switching between cloud services from different providers at the PaaS level. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 41 | 2025 | Edition 1 | Pages 68-73<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Improving\n <\/picture>\n <\/div>\n
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Improving Social Media Moderation with Generative Language Models<\/h4>\n
Study on the detection and correction of disinformation<\/div>
Anton Schegolev<\/a>, Maximilian Ambros<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Fake news are increasingly dominating the digital world. The question arises: Can modern technologies reverse this trend? The article highlights the potential of the GPT-4o language model for identifying fake news in online comments and news articles and for correcting false information. With impressive accuracy, the model shows how language technology can combat misinformation. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 40 | 2024 | Edition 6 | Pages 72-79 | DOI 10.30844\/I4SE.24.6.72<\/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 Industry 4.0 with AI Tutoring Systems<\/h4>\n
State of technology<\/div>
Norbert Gronau<\/a> \n \"ORCID<\/a>, Georg David Ritterbusch<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n The rapid development of artificial intelligence (AI) is constantly opening new opportunities, particularly in training for the factory of the future. For employees, this not only means a significant advantage in the actual manufacturing process, but also in the field of continuing education. This paper provides an overview of AI tutoring systems continuing education in the context of Industry 4.0 by presenting a categorization that discusses different approaches of AI tutoring systems by learning methods, application areas and their respective technologies. In addition, an outlook on the disruptive effect of generative AI on AI tutoring systems in Industry 4.0 is given. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 40 | 2024 | Edition 5 | Pages 50-57 | DOI 10.30844\/I4SE.24.5.50<\/a><\/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":103482,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_uag_custom_page_level_css":"","footnotes":""},"class_list":["post-103484","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\/103484","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=103484"}],"version-history":[{"count":1,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/pages\/103484\/revisions"}],"predecessor-version":[{"id":103485,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/pages\/103484\/revisions\/103485"}],"up":[{"embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/pages\/103482"}],"wp:attachment":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media?parent=103484"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}