This study aims to investigate the impact of traditional teaching and active learning methods in lean management (LM) on the development of both soft and hard skills. Based on these three system components, the system facilitates structured and integrated access, storage and re-use of expert knowledge and production data. The interface allows importing, interlinking and storing recipes and reports together with the workers’ knowledge in the common knowledge base.

Last, a semantic data interface interconnects the system with external information systems on the shop floor. Furthermore, the system is equipped with a semantic inference engine, which performs content analysis and thereby automatically generates new facts in the knowledge base. This user interface enables them to access heterogeneous data like equipment specifications, best practices and pictures as well as to rapidly record their observations and actions in the system. The underlying system architecture foresees a semantic wiki-system as the system's interface to workers. This paper presents a methodology to develop lean knowledge management systems based on semantic technology, which are designed for the needs of small and medium sized manufacturing companies.

The use of information systems can significantly improve the required knowledge management process, but need to be adapted to the requirements of manufacturing facilities. In manufacturing facilities, redundant work and poor product quality can be prevented by the effective use of the workers’ knowledge.

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