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While academia and industry see large potential for human-robot collaboration (HRC), only a small number of realized HRC application is currently found in industry. To gather more data about current hindrances to wider implementation of collaborative robots, a study among 15 robot manufactureres and 14 system integrators of collaborative robot technology has been conducted through a predesigned questionnaire procedure. Additionally, five industrial users of human-robot collaboration have been interviewed on the main challenges they experienced during the initial implementation process. The quantitative data has been analyzed using the Wilcoxon-Signed-Rank-Test. Accoring to the study participants, the main challenges within the implementation currently are the identification of HRC-suitable processes, the application of relevant safety norms (such as ISO 10218, ISO/TS 15066) and the application-individual risk assessment.
The level of automation in intralogistics has steadily increased over recent years. For small and medium-sized enterprises (SMEs), however, the associated digital change is a major challenge. Since most SMEs are facing increasing sales volumes (e.g. due to e-commerce and good overall economy) in combination with decreasing lot sizes due to the market demand for individualized products, SMEs have to find innovative solutions to cope with these challenges in production as well as in logistics. Innovative technologies, like 3D printing technologies for the production for small lot sizes and future-oriented intralogistics technologies can serve as enablers in logistics to realize flexible logistic processes for increasing market requiremments. Considering that, this paper examines innovative and future-oriented technologies for intralogistics such as smart containers, driverless forklift systems, data glasses, smart shelves and smart pallets regarding their potential for SMEs. This explorative research paper shows that digital technologies are already suitable and available for SMEs.However, challenges are still seen in areas like the identification and digitalization potential and the financing of these new projects. The primary reason escpecially for SMEs for this is that they have to make investments based on an economically feasible payback period and less based on prestigious reasons like digitalization flagship projecs done by large corporations. In addition, the identification of feasible starting points for digitalization within intralogistic systems embedded in specific factory processes is a major challenge not only for SMEs.
Gesellschaftliche und industrielle Trends im Zuge der Digitaliserung induzieren Veränderungsprozesse in der Industrie. Eine hohe Flexibilität und schnelle Entscheidungsfindungsprozesse stellen entscheidende Wettbewerbsvorteile für Unternehmen dar, um zukünftig erfolgreich am Markt agieren zu können. Um dies zu ermöglichen, müssen aggregierte Echtzeitdaten und Prognosen unmittelbar sowohl am Ort der Wertschöpfung als auch dezentral zur Verfügung stehen. Die Entscheidungsunterstützung mit Hilfe geeigneter Visualisierungen ist ein maßgeblicher Bestandteil von Shopfloor Management Systemen. Aufgrund der steigenden Anforderungen wurde das konventionelle und analoge Shopfloor Management in den letzten Jahren verstärkt durch digitale Lösungen ersetzt. Ein ganzheitlicher Shopfloor Management Ansatz, der die Trends und die daraus resultierenden Herausforderungen für die Industrie abdeckt, ist aktuell nicht vorhanden. Zukünftige Shopfloor Management Lösungen sollen diese Lücke schließen. Hierfür wurde ein ganzheitliches System entwickelt, welches Produktionsinformationen in Echtzeit unmittelbar am Shopfloor visualisiert, eine integrierte flexible Planung und Steuerung der Produktion beinhaltet sowie die Mitarbeiterbedürfnisse berücksichtigt. Eine flexible und individuelle Schichtplanung durch die Mitarbeiter und eine umfassende automatische Beanspruchungsbeurteilung sind dazu integriert worden. Zudem ermöglicht das System die Prognose und Visualisierung von Produktionsinformationen und unterstützt die Anwender bei der Durchführung strukturierter Shopfloor-Meetings. Dadurch werden Entscheidungen direkt auf den Ort der Wertschöpfung verlagert.
Mastering of complex systems and interfaces, idea and innovation management as well as virtually integrated product and process planning are essential competences to be developed and fostered to cope with the changing role of the workforce in a future industry 4.0 work system. Learning factories, like the Logistics Learning Factory at Reutlingen University, which are equipped with state-of-the-art infrastructure, offer a high potential to decidedly address these competences.
Shorter product life cycles and emerging technologies are changing the circumstances under which the design of assembly and logistics systems has to be carried out. Engineers are in charge of adapting the production in accordance with the underlying product at a higher pace, oversee a more complex system and find the ideal solution for a functional work system design as well as social interactions between humans and machines in cyber-physical systems. Such collaborative work systems consider the individual capabilities and potentials of humans and machines to combine them in a manner that assists the operator during his daily work routine. To be able to design such work systems, specific competences such as the ability of integrated process and product planning as well as systems and interface competence are required. Learning factories train students as well as professionals to gain such qualifications by providing a close-to-reality learning environment based on a didactical concept which covers all relevant methods for ergonomic work system design and a state-of-the-art infrastructure. Group-based, activity oriented scenarios enable the participants to put the learnings into their everyday work life. Thereby, learning factories have an indirect impact on the transfer of proven best practices to the industry.
Learning factories present a promising environment for education, training and research, especially in manufacturing related areas which are a main driver for wealth creation in any nation. While numerous learning factories have been built in industry and academia in the last decades, a comprehensive scientific overview of the topic is still missing. This paper intends to close this gap establishing the state of the art of learning factories. The motivations, historic background, and the didactic foundations of learning factories are outlined. Definitions of the term learning factory and the corresponding morphological model are provided. An overview of existing learning factory approaches in industry and academia is provided, showing the broad range of different applications and varying contents. The state of the art of learning factories curricula design and their use to enhance learning and research as well as potentials and limitations are presented. Conclusions and an outlook on further research priorities are offered.