{"id":95087,"date":"2024-02-15T12:00:00","date_gmt":"2024-02-15T11:00:00","guid":{"rendered":"https:\/\/industry-science.com\/?post_type=article&p=95087"},"modified":"2025-02-04T16:55:36","modified_gmt":"2025-02-04T15:55:36","slug":"refrigerating-appliances-recycling","status":"publish","type":"article","link":"https:\/\/industry-science.com\/en\/articles\/refrigerating-appliances-recycling\/","title":{"rendered":"Cost-efficient Digitization of Refrigerating Appliances Recycling"},"content":{"rendered":"

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The transformation from linear to circular economic models is a central pillar of sustainable development strategies worldwide. The approach aims to enable a longer life for products and materials while minimizing waste and environmental impact by closing material cycles. Digital technologies play an important role in increasing transparency and efficiency throughout the entire life cycle of a product. The European Union\u2019s Ecodesign for Sustainable Products Regulation [1] prescribes the introduction of a Digital Product Passport (DPP). A digital product passport is a document that bundles all important information about a product, …<\/div>\n

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\n\n\n\n<\/thead>\n\n\n\n\n\n\n\n\n<\/tbody>\n<\/table>\n

Subscription<\/th>\nincluded<\/th>\nPurchase<\/th>\n
without<\/td>\n−<\/td>\n29,00 \u20ac<\/td>\n
Digital<\/td>\n−<\/td>\n27,55 \u20ac<\/td>\n
Expert<\/td>\n−<\/td>\n26,10 \u20ac<\/td>\n
Professional<\/td>\n✓<\/span><\/td>\n0,00 \u20ac<\/td>\n
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Industry 4.0\u2014Progress and Digitalization in Limbo<\/h4>\n
Status of sustainable transformation and digitalization in production engineering<\/div>
Christian Donhauser<\/a> \n \"ORCID<\/a>, Daniel Riepl<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n
\n\t\t\t \n\t\t\t <\/div>Digitalization projects help users represent complex processes more simply and efficiently. However, there are many obstacles to implementation. Reluctance to implement these projects is palpable. This affects, among others, employers and employees, who may fall behind economically by waiting or avoiding change. These observations can be traced back to an overarching research question: What barriers and systemic challenges hinder sustainable transformation within the context of Industry 4.0, particularly when considering human labor in production engineering? What questions are the affected stakeholders asking? The primary goal of this long-term research project is to define these questions decisively and in detail in order to develop a conceptual foundation that integrates research, teaching, and technological development and thus combines the potential of digital technologies with the experiential and practical knowledge of production workers. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 3 | Pages 56-60<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Application\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

Application Potentials of Chinese Knowledge Platforms<\/h4>\n
Digital platforms for knowledge transfer in research and education<\/div>
Yunhao Su<\/a>, Martin Braun<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n
\n\t\t\t \n\t\t\t <\/div>Knowledge drives innovation, which is why digital platforms are increasingly used for knowledge transfer. The People\u2019s Republic of China (PRC) is a global leader in digitalization and digital platforms are central to Chinese knowledge transfer and innovation systems. This study supplements theoretical concepts of knowledge transfer with empirical findings on the (further) development of relevant knowledge platforms. It examines the influence of specific design features on the functionality and quality of digital knowledge platforms. A literature review identifies seven condensed success criteria. Nine leading Chinese knowledge platforms are categorized based on their transfer logic and functional scope. Online survey participants assess the platform-specific manifestations of the identified criteria and highlight potential and areas for improvement in platform-based knowledge transfer. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 3 | Pages 84-93<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Digital\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

Digital Twin Technology and Architecture<\/h4>\n
A synthesis of concept and practice<\/div>
Arka Mukherjee<\/a> \n \"ORCID<\/a>, Shibaji Chandra<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n
\n\t\t\t \n\t\t\t <\/div>Digital twins are a key enabling technology of the fourth industrial revolution, integrating physical systems with their digital counterparts to create intelligent, data-driven environments. This conceptual\/practice-oriented paper examines how to establish a modern architectural framework for digital twins leverages modern tech-stack like IoT, Data Fabric, AI\/ML, seamless integration and enterprise grade security. The paper is grounded in an abundance of literature by leading vendors and analysts in space. It offers a comparative study of different vendors implementing the solution stack in the proposed architecture. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 3 | Pages 114-122<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"VR\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

VR Training for Multimodal Cobot Interaction<\/h4>\n
Virtual learning environments for collaborative robots<\/div>
Christoph S. Zoller<\/a>, Justus Langer<\/a>, Kristoffer Waldow<\/a> \n \"ORCID<\/a>, Merle Meyer<\/a>, Arnulph Fuhrmann<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n The VIRAMM research project is developing and prototyping a VR-based training concept for the integration of collaborative robots (cobots) in assembly-oriented U-cells. Since the benefits of cobots depend heavily on process, layout, and role integration, VIRAMM addresses the previously lacking consistent scenario design for variant comparisons with Key Performance Indicator (KPI)-based evaluation. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 3 | Pages 106-112<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Decentralized\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

Decentralized Coordination of AMRs<\/h4>\n
Regulations for Autonomous Mobile Robots<\/div>
Manuel Savadogo<\/a>, Malte Stonis<\/a> \n \"ORCID<\/a>, Peter Nyhuis<\/a> \n \"ORCID<\/a>, J\u00fcrgen Hupp<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n
\n\t\t\t \n\t\t\t <\/div>The increasing automation of intralogistics requires flexible and resilient control concepts for Autonomous Mobile Robots (AMR). While centralized coordination approaches enable stringent control, they quickly reach their limits in terms of scalability and robustness. This paper therefore presents regulations for the decentralized coordination of AMR within the framework of the ORPHEUS project. The focus is on translating known decentralized decision-making principles into a rule framework tailored to industrial material flow scenarios, addressing both operational task assignment and safety-related conflict situations. ORPHEUS thus makes a significant contribution to the methodological structuring, parameterization, and practical transferability of decentralized coordination logics. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 3 | Pages 96-105<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Developing\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

Developing Virtual Reality in Learning Contexts<\/h4>\n
Navigating efficiency, content relevance and scalability<\/div>
Stella Kanatouri<\/a> \n \"ORCID<\/a>, Oliver Sosna<\/a> \n \"ORCID<\/a>, Alexander Kulik<\/a>, Sina C. Truckenbrodt<\/a> \n \"ORCID<\/a>, Friederike Klan<\/a> \n \"ORCID<\/a>, Christian Erfurth<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n While virtual reality can facilitate hands-on learning, its development faces barriers, including high costs and time demands and scalability challenges. This article presents two case studies that illustrate strategies for overcoming such barriers when training the next generation of skilled workers in environmental technologies. By examining approaches for streamlining development and increasing content relevance and scalability, we highlight lessons learned for future practice. We conclude by envisioning a future in which educational institutions can flexibly and cost-effectively prototype virtual reality in learning contexts, ensuring alignment with curricular goals and learners\u2019 needs. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | Edition 3 | Pages 26-34 | DOI 10.30844\/I4SE.26.3.3<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"

Correctly recycling obsolete refrigeration devices plays an important role in environmental and climate protection efforts. Recycling plants are subject to regular audits to ensure their compliance with strict environmental regulations. However, the collection of audit-related data is a challenging and time-consuming task, as it is usually done manually and is prone to errors. One solution for more sustainable and efficient monitoring is to automate digital data collection using sensors and artificial intelligence. This enables a direct estimate of the expected level of pollutants. This paves the way for continuous performance monitoring and efficient management of refrigeration appliance recycling plants.<\/p>\n","protected":false},"featured_media":107495,"menu_order":0,"template":"","categories":[79167,79168,79298],"tags":[79627,80265,79362,79356],"product_cat":[79304],"topic":[67838,68206,68267],"technology":[67790,67946],"knowhow":[],"industry":[],"writer":[83699,83697,81417,83700,83698],"content-type":[],"potential":[],"solution":[],"glossary":[],"class_list":["post-95087","article","type-article","status-publish","has-post-thumbnail","category-design-en","category-translate-en","category-typeset","tag-industrie-4-0-en","tag-iot-en","tag-ki-en","tag-nachhaltigkeit-en","product_cat-articles","topic-digital-twin","topic-industry-4-0","topic-sustainability","technology-artificial-intelligence","technology-sensors","writer-christian-thiehoff-en","writer-georgii-emelianov-en","writer-jochen-deuse-en","writer-jochen-schiemann-en","writer-mikhail-polikarpov-en","product","first","instock","downloadable","virtual","sold-individually","taxable","purchasable","product-type-article"],"uagb_featured_image_src":{"full":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min.jpeg",1400,788,false],"thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-150x150.jpeg",150,150,true],"medium":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-666x375.jpeg",666,375,true],"medium_large":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-768x432.jpeg",768,432,true],"large":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-1024x576.jpeg",1020,574,true],"front-page-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-1032x320.jpeg",1032,320,true],"post-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-764x376.jpeg",764,376,true],"post-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-392x320.jpeg",392,320,true],"post-teaser-mobile":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-608x496.jpeg",608,496,true],"post-custom-size":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-640x325.jpeg",640,325,true],"whitepaper-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-274x376.jpeg",274,376,true],"card-big":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-514x292.jpeg",514,292,true],"card-portrait":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-320x440.jpeg",320,440,true],"card-big-company":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-514x289.jpeg",514,289,true],"gp-listing":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-196x180.jpeg",196,180,true],"1536x1536":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min.jpeg",1400,788,false],"2048x2048":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min.jpeg",1400,788,false],"woocommerce_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-510x510.jpeg",510,510,true],"woocommerce_single":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-510x287.jpeg",510,287,true],"woocommerce_gallery_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-100x100.jpeg",100,100,true],"dgwt-wcas-product-suggestion":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/02\/AdobeStock_677746955-min-64x36.jpeg",64,36,true]},"uagb_author_info":{"display_name":"Florian Goldmann","author_link":"https:\/\/industry-science.com\/en\/author\/"},"uagb_comment_info":0,"uagb_excerpt":"Correctly recycling obsolete refrigeration devices plays an important role in environmental and climate protection efforts. Recycling plants are subject to regular audits to ensure their compliance with strict environmental regulations. However, the collection of audit-related data is a challenging and time-consuming task, as it is usually done manually and is prone to errors. One solution…","_links":{"self":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article\/95087","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article"}],"about":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/types\/article"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media\/107495"}],"wp:attachment":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media?parent=95087"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/categories?post=95087"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/tags?post=95087"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/product_cat?post=95087"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/topic?post=95087"},{"taxonomy":"technology","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/technology?post=95087"},{"taxonomy":"knowhow","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/knowhow?post=95087"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/industry?post=95087"},{"taxonomy":"writer","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/writer?post=95087"},{"taxonomy":"content-type","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/content-type?post=95087"},{"taxonomy":"potential","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/potential?post=95087"},{"taxonomy":"solution","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/solution?post=95087"},{"taxonomy":"glossary","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/glossary?post=95087"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}