Description
Today knowledge is becoming increasingly important due to structural changes. While production factors such as work, location and, above all, capital were still relevant in the 1990s, the knowledge of a company is today a decisive competitive factor. By concentrating the entrepreneurial tasks on this crucial resource, it must be ensured that the knowledge necessary for business success is built up, secured and optimally used in a market-oriented manner. Existing approaches to knowledge management, however, neglect the special challenges of the manufacturing industry, do not take sufficient account of human communication and do not represent knowledge holistically.
The aim of this work is to analyze the specific requirements of the manufacturing industry for the change towards knowledge companies and to represent them in a holistic knowledge management concept. The systematic analysis of the influences on knowledge management, such as obstacles, success factors, methods and systems, creates an understanding of how knowledge can be optimally used in the manufacturing industry. By representing knowledge, its relationships and the logic contained therein in an ontology-based knowledge management framework, companies are supported in the formal recording of the success-critical resource. The adequate integration of the technology of artificial intelligence and machine learning also enables employees to interact with ontologies as a form of knowledge representation with little effort.
In addition, the work shows how the ontology-based knowledge management framework can be used in a real production and how an optimal design of the current and future use of resources can be guaranteed.
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