[Zurück]


Vorträge und Posterpräsentationen (ohne Tagungsband-Eintrag):

M. Nausch, A. Schumacher, W. Sihn:
"Assessment of Organizational Capability for Data Utilization - A Readiness Model in the Context of Industry 4.0";
Vortrag: International Symposium for Production Research 2019, Wien; 28.08.2019 - 30.08.2019.



Kurzfassung englisch:
- Increased utilization of digital elements and computer assistance in industrial enterprises leads to the acquisition of data encompassing all company levels and areas. Subsequently, manufacturing companies face large amounts of collected data from different sources and in various formats. Today this data is beginning to be viewed as a resource, comparable to material or machines. Thus, the ability to effectively collect and utilize internal and external data, is becoming an increasingly important factor in determining their economic success.
In this paper we develop a readiness model which can assess the Capability to Utilize Data in Industrial Enterprises (CUDIE). This model enables industrial decision makers to determine their organization´s current status, to define strategies to increase data usage and to identify individual fields for improvement. Our model is based on various frameworks for readiness and maturity model development, as well as an Industry 4.0 maturity model that has already been applied in industrial settings. To assess readiness in real industry environments we transformed the theoretical CUDIE-model into a practically applicable tool that combines self-assessment with an external audit-based assessment.
Finally, in order to validate the model, and to collect feedback concerning its applicability and suitability, we tested our model on an industry use-case. There we could conclude that our method can be used to help companies to identify their current capability for data utilization, to derive areas of improvement and to define their future strategic steps.

Schlagworte:
Industry 4.0, Readiness Model, Data Utilization, Manufacturing Industry, Assessment Method


"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.1007/978-3-030-31343-2


Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.