A Holistic Approach for Quality Oriented Maintenance Planning Supported by Data Mining Methods

In order to realize a holistic and anticipatory approach for maintenance planning, a methodology which consistently compiles and correlates various data via “cause and effect” coherences is depicted. By breaking down the production facilities on component level a basis is set to link condition monitoring data, wear data, quality and production data by using data mining methods. This framework enables the identification of maintenance-critical conditions and the prediction of failure moments and quality deviations.