Autor: Markus Schmitz

Collaboration Using Physical Models

Collaboration Using Physical Models

Ansätze für die Vermittlung von Kollaborationskompetenz in der Fabrikplanung im Rahmen der universitären Lehre
Sigrid Wenzel ORCID Icon, Tim Peter, Markus Schmitz
Digital factory, simultaneous engineering and system interoperability are based on collaborative interdisciplinary working processes in an enterprise. According to a study of the workgoup industry 4.0 [1] the implementation of industry 4.0 leads to new collaborative and cooperative behaviour between employees. For academic teaching this implies, that in addition to technical, methodological and IT expertise, collaboration skills must be encouraged. The following article explains the use of physical models to teach collaboration skills by means of the example of factory planning. These models are currently realized or are already in use in teaching at the department for organization of production and factory planning of the University of Kassel.
Industrie 4.0 Management | Volume 32 | 2016 | Edition 3 | Pages 62-65
Approaches to Support Discrete-event Simulation as a Knowledge-intensive Process

Approaches to Support Discrete-event Simulation as a Knowledge-intensive Process

Dennis Abel, Markus Schmitz, Sigrid Wenzel ORCID Icon
Planning, design and continuous improvement of today’s complex corporate structures and technical systems require a sophisticated level of extensive know-ledge of technology, processes and IT. To apply planning and simulation tools effectively and efficiently engineers and plant operators have to rise to the challenge to use their knowledge in a goal-oriented way and to expand it within creative processes. Consequently, knowledge is more than ever a key productivity factor and an important component of corporate capital. Against this background, the article discusses possibilities for systematization and standardization in simulation studies and especially approaches to increase productivity in simulation studies by supplying assistance functions as well as systematic evaluation methodologies.
Industrie Management | Volume 28 | 2012 | Edition 3 | Pages 7-11