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In the last decade, numerous learning factories for education, training, and research have been built up in industry and academia. In recent years learning factory initiatives were elevated from a local to a European and then to a worldwide level. In 2014 the CIRP Collaborative Working Group (CWG) on Learning Factories enables a lively exchange on the topic "Learning Factories for future oriented research and education in manufacturing". In this paper results of discussions inside the CWG are presented. First, what is meant by the term Learning Factory is outlined. Second, based on the definition a description model (morphology) for learning factories is presented. The morphology covers the most relevant characteristics and features of learning factories in seven dimensions. Third, following the morphology the actual variance of learning factory manifestations is shown in six learning factory application scenarios from industrial training over education to research. Finally, future prospects of the learning factory concept are presented.
Due to the complexity of assembly processes, a high ratio of tasks is still performed by human workers. Short-cyclically changing work contents due to smaller lot sizes, especially the varied series assesmbly, increases both the need for information support as well as the risk of rising physical and psychological stress. The use of technical and digital assistance systems can counter these challenges. Through the integration of information and communication technology as well as collaborative assembly technologies, hybrid cyber-physical assembly systems will emerge. Widely established assembly planning approaches for digital and technical support systems in cyber physical assembly systems will be outlined and discussed with regard to synergies and delimitations of planning perspectives.
Close and safe interaction of humans and robots in joint production environments is technically feasible, however should not be implemented as an end in itself but to deliver improvement in any of a production system’s target dimensions. Firstly, this paper shows that an essential challenge for system integrators during the design of HRC applications is to identify a suitable distribution of available tasks between a robotic and a human resource. Secondly, it proposes an approach to determine task allocation by considering the actual capabilities of both human and robot in order to improve work quality. It matches those capabilities with given requirements of a certain task in order to identify the maximum congruence as the basis for the allocation decision. The approach is based on a study and subsequent generic description of human and robotic capabilities as well as a heuristic procedure that facilities the decision making process.
In recent years, the numer of hybrid work systems using human robot collaboration (HRC) increased in industrial production environments - enhancing productivity while reducing work-related burden. Despite growing availability of HRC-suitable manipulation and safety technology, tools and techniques facilitating the design, planning and implementation process are still lacking. System engineers who strive to implement technically feasible, ergonomically meaningful and economically beneficial HRC application need to make design and technology decisions in various subject areas, whereas the design alternatives per morphological analysis is applied to establish a description model that can serve as both a supporting design guideline for future HRC application of value-adding, industrial quality as well as a tool to characterize and compare existing applications. It focuses on HRC within assembly processes, and illustrates the complexity of HRC applications in a comprehensible manner through its multi-dimensional structure. The morphology has been validated through its application on various existing industrial HRC applications, research demonstrators and interviews of experts from academia.