Abstract.A vision for the Operator 4.0 is presented in this paper in the context of human cyber-physical systems and adaptive automation towards humanautomation symbiosis work systems for a socially sustainable manufacturing workforce. Discussions include base concepts and enabling technologies for the development of human-automation symbiosis work systems in Industry 4.0.
Abstract. Human-centricity in manufacturing is becoming an essential enabler to achieve social sustainable manufacturing. In particular, human-centric automation can offer new means to increase competitiveness in the face of new social challenges for the factories of the future. This paper proposes a HumanCentred Reference Architecture that can structure and guide efforts to engineer Next Generation Balanced Automation Systems featuring adaptive automation that take into account various criteria in the operating environment such as time-lapse, performance degradation, age-, disability-and inexperience-related limitations of operators to increase their working capabilities.
Humans are indispensable in the manufacturing industry as its complexity increases in an Industry 4.0 context, mainly due to changing customer demands. Managing the challenges of increased complexity can create a competitive advantage for SMEs. Technologies which enable the emerging phenomenon of Industry 4.0 have the possibility to simplify the sharing of information and knowledge among people at work, especially for Operator 4.0. However, few SMEs have actually implemented such technologies for this purpose. Therefore, this paper aims to create an understanding of the current state and challenges which need to be overcome, and further, to provide some insights on future possibilities by identifying the stages of Industry 4.0 development of SMEs with regards to their capabilities. This qualitative interview study focuses on how human-centered production processes are currently supporting assembly and office work. Two Swedish SMEs were studied, where almost all of their operators and management team on site were interviewed individually concerning their views on their current capabilities. The interviews were thematically analyzed with regards to the state-of-the-art research, and results show that the case companies are in some aspects digitized with regards to computerization and connectivity, but have some challenges in making the shared production-related information more visible and transparent, especially on shop-floors where most information and knowledge are shared through word of mouth or with pen and paper. Conclusively, the studied SMEs have started their digitalization journey, but further Industry 4.0 development needs to align with their respective conditions and needs. While Industry 4.0 enabling technologies that support information and knowledge sharing are emerging, organizational development can support the implementation of such technologies, which should be the focus for future research.
Modern assembly systems are adapting to the increased mass customization resulting in shorter cycle times, more variants and increased complexity for final assembly operators. More variants require additional support functions targeted for assembly operators to avoid assembly errors. An industrial case study was carried out in order to examine the relations between complexity, quality and cognitive automation. Complexity was quantified by the measure Operator Choice Complexity (OCC). Assembly errors were measured from historical data and cognitive automation was assessed on a task level. Results show that complexity positively correlates with assembly errors and that the usage of cognitive support is low. Over 60% of all tasks in the study were performed based on own experience. Increased usage of cognitive automation is needed in final assembly to minimize the negative effects of complexity.
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