{"id":108453,"date":"2025-04-15T12:00:00","date_gmt":"2025-04-15T12:00:00","guid":{"rendered":"https:\/\/industry-science.com\/?post_type=article&p=108453"},"modified":"2025-03-31T20:33:37","modified_gmt":"2025-03-31T18:33:37","slug":"intelligent-load-carrier","status":"publish","type":"article","link":"https:\/\/industry-science.com\/en\/articles\/intelligent-load-carrier\/","title":{"rendered":"Intelligent Load Carrier Management"},"content":{"rendered":"

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In the face of global competition and a rapidly changing market environment, manufacturing companies must carrier their goods along the supply chain in ever shorter periods of time [1]. Digital transformation has long been at work here, networking components such as load carriers, for example, to enable an intelligent supply chain. Using GPS or, more recently, Bluetooth connections to satellites [2], it is now easy to track the positions of objects and the routes that they are taking. However, what may be desirable with regard to objects poses a …<\/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
\n \t \n
\t\t

Competence Assurance for the Verification and Validation of Simulation Models<\/h4>\n
Requirements for AI-supported assistance in production and logistics<\/div>
Sigrid Wenzel<\/a> \n \"ORCID<\/a>, Felix \u00d6zkul<\/a> \n \"ORCID<\/a>, Robin Sutherland<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Can artificial intelligence be used to assess the validity and credibility of simulation models and data for production and logistics? And what requirements must AI assistance meet to effectively support experts in verification and validation while simultaneously safeguarding their competence? In an online survey, simulation experts were asked regarding their expectations and needs. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 5 | Pages 24-33 | DOI 10.30844\/I4SE.26.5.3<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Experiential\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

Experiential Knowledge Powered by AI\u00a0<\/h4>\n
Practical insights from industry<\/div>
Martin Schmauder<\/a> \n \"ORCID<\/a>, Gritt Ott<\/a> \n \"ORCID<\/a>, Bianca Windisch<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n The use of experiential knowledge is a key success factor for companies. Based on four corporate case studies, this article analyzes the technical, organizational, and personnel challenges associated with the use of retrieval-augmented generation (RAG) systems. The results show that the success of such systems depends on the strategic development and maintenance of the knowledge base, as well as on employee engagement. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 5 | Pages 128-135 | DOI 10.30844\/I4SE.26.5.15<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Inclusive\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

Inclusive Work System Design<\/h4>\n
Automation, standardization, and adaptability<\/div>
Sebastian Schlund<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n The design of inclusive work systems is gaining importance due to demographic change and the increasing digital penetration of value creation processes. While traditional ergonomic approaches are based primarily on percentile logic and thus address only a portion of the user population, the integration of digital technologies opens up new possibilities for the dynamic and individualized adaptation of work systems. This article presents a conceptual framework for inclusive work system design that integrates standardization, automation, and adaptability. Methodologically, the article is based on a conceptual analysis of existing approaches from ergonomics and human-centered design. The article makes a theoretical contribution to the systematization of inclusive work system design and identifies areas of focus for further research and industrial practice. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 5 | Pages 70-76 | DOI 10.30844\/I4SE.26.5.8<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"MTM\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

MTM Analyses with AI and Rule-Based Algorithms<\/h4>\n
An approach to interpreting textual process descriptions<\/div>
Constantin Eckart<\/a> \n \"ORCID<\/a>, Martin Benter<\/a> \n \"ORCID<\/a>, Peter Kuhlang<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n MTM methods are a proven standard for analyzing and designing human work processes. However, work planners continue to face challenges in applying these methods correctly and efficiently. Artificial intelligence \u2014 particularly in the case of large language models \u2014 holds significant potential for combatting these challenges. However, the use of AI raises legitimate questions regarding the reliability and traceability of the results. The approach presented here combines LLMs with a rule-based algorithm to extract the information required for MTM analyses from textual process descriptions such as work instructions. This information is then translated into MTM analyses in accordance with the MTM methodology. This approach ensures that the resulting analyses can be transparently traced back to the original input data by the user. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 5 | Pages 62-69 | DOI 10.30844\/I4SE.26.5.7<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Data-Driven\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

Data-Driven Supplier Selection in Industry 4.0<\/h4>\n
Towards an industrial platform for selection and configuration<\/div>
Purushothaman Ganesh<\/a> \n \"ORCID<\/a>, Baris E. Albayrak<\/a> \n \"ORCID<\/a>, J\u00f6rg Franke<\/a> \n \"ORCID<\/a>, Till Sindel<\/a> \n \"ORCID<\/a>, Jens F\u00fcrst<\/a>, Sebastian Lang<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Industrial supply chains must repeatedly reconfigure sourcing strategies in response to disruptions, yet supplier capability information remains heterogeneous and difficult to operationalize. Existing research addresses supplier selection, simulation, and interoperability standards separately, treating discovery, evaluation, and optimization as disconnected steps requiring manual data transformation. This paper presents a framework for a data-driven industrial platform integrating three components: Asset Administration Shell-based supplier profiles structured by an Actor-Service ontology for semantic discovery, automatic discrete-event simulation model generation from layout data for performance evaluation, and KPI-driven configuration using optimization algorithms. The main contributions are an end-to-end interoperable workflow, a two-tier supplier profile concept separating semantic descriptions from simulation parameters, and a standardized KPI interface maintaining consistency ... <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 4 | Pages 50-61 | DOI 10.30844\/I4SE.26.4.6<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n
\n \n
\n \n \n \n \"Replacing\n <\/picture>\n <\/div>\n
\n \t \n
\t\t

Replacing Organizational Trust with Technical Guarantees<\/h4>\n
Privacy-enhancing technologies for dynamic industrial value networks<\/div>
Hajeong Jeon<\/a> \n \"ORCID<\/a>, Johannes Lohm\u00f6ller<\/a> \n \"ORCID<\/a>, Klaus Wehrle<\/a> \n \"ORCID<\/a>, Jan Pennekamp<\/a> \n \"ORCID<\/a><\/div>\n <\/td>\n <\/tr>\n <\/table>\n
\n Long-term relationships are now insufficient to ensure trust in digitalized and dynamic industrial networks where sensitive data sharing is prevalent. While organizational trust mechanisms, such as contracts, remain significant, they are often slow and challenging to scale within evolving digital platforms. This article thus proposes privacy-enhancing technologies as a foundation for embedding technical and verifiable guarantees alongside organizational trust mechanisms. As a result, secure industrial collaboration can be achieved without the persistence of data silos. <\/div>\n <\/div>\n
Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 4 | Pages 72-80 | DOI 10.30844\/I4SE.26.4.8<\/a><\/div> <\/div>\n <\/div>\n <\/a>\n <\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"

Load carriers are essential for transporting manufactured parts in manufacturing companies. Despite their \u2018simplicity\u2019, they are usually expensive to purchase as they are manufactured expressly to fit purpose. While tracking methods such as GPS tracking can be used to prevent the loss of load carriers, this is associated with monitoring costs and presents challenges with regard to data protection as soon as the work performance of intralogistics employees is monitored. Assigning load carriers to designated clusters and monitoring these clusters provides an effective solution\u2014without drawing conclusions about employee performance. Furthermore, artificial intelligence can optimize this approach whilst also deterring the theft of load carriers.<\/p>\n","protected":false},"featured_media":108359,"menu_order":0,"template":"","categories":[79167,79298],"tags":[79447,79504,79627,79365,80138],"product_cat":[79304],"topic":[79352,79371,79333],"technology":[68674],"knowhow":[],"industry":[79354],"writer":[82805],"content-type":[83932],"potential":[67894,69462],"solution":[67610,78673,67687],"glossary":[],"class_list":["post-108453","article","type-article","status-publish","has-post-thumbnail","category-design-en","category-typeset","tag-datenschutz-en","tag-digitale-transformation-en","tag-industrie-4-0-en","tag-logistik-en","tag-supply-chain-management-en","product_cat-articles","topic-data-privacy","topic-logistics","topic-process-optimization","technology-robotics","industry-smart-objects","writer-dominik-augenstein-en","content-type-article","potential-innovation-en","potential-resource-efficiency","solution-logistik-en","solution-logistics-technology","solution-process-management","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\/03\/AdobeStock_741519158.jpeg",1400,788,false],"thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-150x150.jpeg",150,150,true],"medium":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-666x375.jpeg",666,375,true],"medium_large":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-768x432.jpeg",768,432,true],"large":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-1024x576.jpeg",1020,574,true],"front-page-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-1032x320.jpeg",1032,320,true],"post-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-764x376.jpeg",764,376,true],"post-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-392x320.jpeg",392,320,true],"post-teaser-mobile":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-608x496.jpeg",608,496,true],"post-custom-size":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-640x325.jpeg",640,325,true],"whitepaper-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-274x376.jpeg",274,376,true],"card-big":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-514x292.jpeg",514,292,true],"card-portrait":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-320x440.jpeg",320,440,true],"card-big-company":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-514x289.jpeg",514,289,true],"gp-listing":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-196x180.jpeg",196,180,true],"1536x1536":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158.jpeg",1400,788,false],"2048x2048":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158.jpeg",1400,788,false],"woocommerce_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-510x510.jpeg",510,510,true],"woocommerce_single":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-510x287.jpeg",510,287,true],"woocommerce_gallery_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-100x100.jpeg",100,100,true],"dgwt-wcas-product-suggestion":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/03\/AdobeStock_741519158-64x36.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":"Load carriers are essential for transporting manufactured parts in manufacturing companies. Despite their \u2018simplicity\u2019, they are usually expensive to purchase as they are manufactured expressly to fit purpose. While tracking methods such as GPS tracking can be used to prevent the loss of load carriers, this is associated with monitoring costs and presents challenges with…","_links":{"self":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article\/108453","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\/108359"}],"wp:attachment":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media?parent=108453"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/categories?post=108453"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/tags?post=108453"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/product_cat?post=108453"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/topic?post=108453"},{"taxonomy":"technology","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/technology?post=108453"},{"taxonomy":"knowhow","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/knowhow?post=108453"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/industry?post=108453"},{"taxonomy":"writer","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/writer?post=108453"},{"taxonomy":"content-type","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/content-type?post=108453"},{"taxonomy":"potential","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/potential?post=108453"},{"taxonomy":"solution","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/solution?post=108453"},{"taxonomy":"glossary","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/glossary?post=108453"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}