Journal Published Online: 28 February 2020
Volume 4, Issue 2

Digital Technologies Enabling Data of Production Systems for Decision Support

CODEN: SSMSCY

Abstract

Using digital technologies can support the flow and use of digital information in a timelier manner both within and between production systems. Smart manufacturing systems use these enabling technologies to maximize the capabilities’ cost, delivery, flexibility, and quality. The focus in industry so far has mainly been on the technologies and systems, but to succeed in digitalization, it is vital to understand how the technologies can be put into practice to meet the needs of an industrial organization. The focus of this article is to demonstrate how digital technologies can be used to enable data from production systems to inform decisions and generate value for an organization. This article showcases this with examples from real-world industrial cases, and the technologies used are 3-D laser scanning and 5G communication. The 3-D laser scanning is used to collect spatial data to build a virtual representation of a factory, and 5G is utilized to collect machine data from various data sources, e.g., the machine computer and external sensors. The results show that available data can support multiple roles in the organization and throughout the different phases of a production system. The status of the machine can be monitored in real time, a design can be evaluated against a system’s behavior, an organization can learn from the data transformed into information, and the virtual representation provides a very accurate and photorealistic representation of a system as-is. Digital technologies can enable more data representing the system and support the organization in knowing more about their processes when used in the right way.

Author Information

Bärring, Maja
Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, Sweden
Johansson, Björn
Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, Sweden
Stahre, Johan
Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, Sweden
Pages: 18
Price: Free
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Details
Stock #: SSMS20190034
ISSN: 2520-6478
DOI: 10.1520/SSMS20190034