{"id":107748,"date":"2025-02-15T12:00:00","date_gmt":"2025-02-15T12:00:00","guid":{"rendered":"https:\/\/industry-science.com\/?post_type=article&p=107748"},"modified":"2025-02-10T17:22:50","modified_gmt":"2025-02-10T16:22:50","slug":"assembly-in-transition","status":"publish","type":"article","link":"https:\/\/industry-science.com\/en\/articles\/assembly-in-transition\/","title":{"rendered":"Assembly in Transition"},"content":{"rendered":"

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Assembly is a crucial stage in the value creation process of multi-part products and itself comprises the processes of joining and handling, supplemented by adjustment, testing and special operations such as heating [1]. The task of assembly is to put together products of higher complexity with specified functions from individual parts, partially assembled pieces and\/or formless materials within a given time [2]. The decisive initial variable for assembly is the component complexity, which is defined on the basis of the individual parts that make up the assembly object. Complex products consist of between 30 and 500 parts, …<\/div>\n

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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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From Private Law to Private Ordering<\/h4>\n
Rule-making through industrial digital platforms<\/div>
Pia C. Romeike<\/a>, Frederik B\u00e4r<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Industrial digital platforms are considered the driving force behind digital value creation, yet legally they largely operate in a gray area. This article examines what defines industrial digital platforms and what legal framework applies to them. Existing platform regulations apply only to a limited extent to industrial digital platforms, which is why these platforms often establish their own legal framework through their terms and conditions. The article also explores the implications of European regulation, power asymmetries, and the opportunities and limitations of private regulation. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 4 | Pages 98-105 | DOI 10.30844\/I4SD.26.4.10<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Platform\n <\/picture>\n <\/div>\n
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Platform Adoption as a Dynamic Capability<\/h4>\n
How SMEs overcome barriers to adoption of B2B collaboration platforms<\/div>
Nikolai Sch\u00e4fer<\/a> \n \"ORCID<\/a>, Marcel H\u00fclsbeck<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Digital collaboration and innovation platforms offer SMEs significant potential to compensate for structural resource weaknesses and to participate in innovation ecosystems. Nevertheless, adoption in the B2B context remains low. This paper examines adoption barriers based on a systematic literature review using Teece\u2019s dynamic capabilities approach. The analysis suggests that recurring obstacles can be structured along three dimensions: Sensing\u2014lack of ecosystem awareness, absence of scanning routines; Seizing\u2014IP concerns, governance uncertainty, adoption fatigue; Reconfiguring\u2014closed-innovation culture, lack of absorptive capacity. Building on this, a practice-oriented capability-building framework is developed with recommendations for action. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 4 | Pages 42-48 | DOI 10.30844\/I4SE.26.4.5<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
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\n \n \n \n \"Industry\n <\/picture>\n <\/div>\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
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\n \n \n \n \"AI-Powered\n <\/picture>\n <\/div>\n
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AI-Powered Lubrication Strategies for Thread Forming<\/h4>\n
Adaptive spray jet control to increase process reliability and tool life<\/div>
Reinhard Schmied<\/a>, Marco Susic<\/a>, Christian Donhauser<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n
\n\t\t\t \n\t\t\t <\/div>Thread forming requires precise lubricant application because high contact pressures and process temperatures strongly influence tool loading, friction, and process stability. Although minimum quantity lubrication (MQL) systems are widely used, current spray-based approaches can still suffer from spray losses, insufficient wetting of the thread grooves, and unstable droplet transport. This article presents a concept for adaptive precision lubrication in thread forming based on computational fluid dynamics (CFD)-supported flow analysis, experimental validation, and artificial intelligence (AI)-assisted optimization. The focus is on droplet size, spray jet geometry, nozzle position, ambient flow conditions, and their influence on wetting intensity. Preliminary simulation-based investigations indicate that data-driven optimization can help identify wetting deficiencies and support the development of future control strategies for resource-efficient lubricant application. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2027 | Edition 3 | Pages 76-83<\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Application\n <\/picture>\n <\/div>\n
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\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
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\n \n \n \n \"VR\n <\/picture>\n <\/div>\n
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\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<\/div>\n\n","protected":false},"excerpt":{"rendered":"

Assembly is an important part of industrial production and is also characterized by a high proportion of manual work. Manufacturing companies have an intrinsic interest in increasing personnel productivity and preventing unit labor costs from rising. Many thus hope to gain economic benefits by implementing digitalization projects. The potential of digitalization in assembly must be exploited to achieve these goals.<\/p>\n","protected":false},"featured_media":107653,"menu_order":0,"template":"","categories":[79167,79298],"tags":[79349,79631,79449,79629,80079],"product_cat":[79304],"topic":[67617,68206,67701],"technology":[79493],"knowhow":[],"industry":[],"writer":[81130],"content-type":[83932],"potential":[67894],"solution":[69358],"glossary":[],"class_list":["post-107748","article","type-article","status-publish","has-post-thumbnail","category-design-en","category-typeset","tag-augmented-reality-en","tag-digitaler-zwilling-en","tag-digitalisierung-en","tag-montage-en","tag-predictive-maintenance-en","product_cat-articles","topic-adaptability","topic-industry-4-0","topic-production-system","technology-digitalization","writer-herwig-winkler-en","content-type-article","potential-innovation-en","solution-assembly","product","first","instock","downloadable","virtual","sold-individually","taxable","purchasable","product-type-article"],"uagb_featured_image_src":{"full":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min.jpeg",1400,788,false],"thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-150x150.jpeg",150,150,true],"medium":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-666x375.jpeg",666,375,true],"medium_large":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-768x432.jpeg",768,432,true],"large":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-1024x576.jpeg",1020,574,true],"front-page-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-1032x320.jpeg",1032,320,true],"post-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-764x376.jpeg",764,376,true],"post-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-392x320.jpeg",392,320,true],"post-teaser-mobile":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-608x496.jpeg",608,496,true],"post-custom-size":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-640x325.jpeg",640,325,true],"whitepaper-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-274x376.jpeg",274,376,true],"card-big":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-514x292.jpeg",514,292,true],"card-portrait":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-320x440.jpeg",320,440,true],"card-big-company":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-514x289.jpeg",514,289,true],"gp-listing":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-196x180.jpeg",196,180,true],"1536x1536":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min.jpeg",1400,788,false],"2048x2048":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min.jpeg",1400,788,false],"woocommerce_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-510x510.jpeg",510,510,true],"woocommerce_single":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-510x287.jpeg",510,287,true],"woocommerce_gallery_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-min-100x100.jpeg",100,100,true],"dgwt-wcas-product-suggestion":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/02\/AdobeStock_408317036-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":"Assembly is an important part of industrial production and is also characterized by a high proportion of manual work. Manufacturing companies have an intrinsic interest in increasing personnel productivity and preventing unit labor costs from rising. Many thus hope to gain economic benefits by implementing digitalization projects. The potential of digitalization in assembly must be…","_links":{"self":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article\/107748","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\/107653"}],"wp:attachment":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media?parent=107748"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/categories?post=107748"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/tags?post=107748"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/product_cat?post=107748"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/topic?post=107748"},{"taxonomy":"technology","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/technology?post=107748"},{"taxonomy":"knowhow","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/knowhow?post=107748"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/industry?post=107748"},{"taxonomy":"writer","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/writer?post=107748"},{"taxonomy":"content-type","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/content-type?post=107748"},{"taxonomy":"potential","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/potential?post=107748"},{"taxonomy":"solution","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/solution?post=107748"},{"taxonomy":"glossary","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/glossary?post=107748"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}