classification

In the BMBF-funded project “Provenance Analytics” research groups at the Bauhaus-Universität Weimar and the Hochschule Ostwestfalen-Lippe develop approaches for detecting anomalies in sensor data. In this short survey, we review the main methods for predicting failures in the production processes of manufacturing machines and give a brief overview of the activities planned in the project.

The research project “eStep Mittelstand - modular solutions for SME to strengthen the independent integration of ebusiness standards in complex supply chain processes” has developed solutions to build up the usage of ebusiness standards in business processes of SME. The methods and models enable SME to run successful ebusiness projects despite high complexity. The transformation to standardized, electronic business processes will be facilitated by the self assessment tool (SAT), the decision tree (EB) and the eStep Mittelstand Middleware (eMiMi). A DIN SPEC, developed together with the Deutschen Institut für Normung (DIN) e. V., provides a guideline to enlarge the functionalities of SAT and EB.