Performance Indicators for Factory Planning on the Basis of the Virtual Production Intelligence Approach

Christian Büscher (), Max Hoffmann, Rudolf Reinhard, Daniel Schilberg and Sabina Jeschke
Additional contact information
Christian Büscher: RWTH Aachen University, IMA/ZLW & IfU
Max Hoffmann: RWTH Aachen University, IMA/ZLW & IfU
Rudolf Reinhard: RWTH Aachen University, IMA/ZLW & IfU
Daniel Schilberg: RWTH Aachen University, IMA/ZLW & IfU
Sabina Jeschke: RWTH Aachen University, IMA/ZLW & IfU

A chapter in Automation, Communication and Cybernetics in Science and Engineering 2013/2014, 2014, pp 829-844 from Springer

Abstract: Abstract Production companies in high-wage countries face growing complexity in their production conditions due to increasing variance and shorter product lifecycles. Solutions that provide an integrated view of the planning processes are needed to achieve increasing production quality and efficiency. One approach for managing this complexity is the use of simulation applications to design digital models. Using the approach of “Virtual Production”, e.g. factory planning scenarios can be evaluated in advance by simulation. A new integrative concept called Virtual Production Intelligence (VPI) has been developed that applies solutions of different intelligence approaches to the field of virtual production by means of integration and analysis of data aggregated along the simulated processes. In this paper, performance indicators are presented for monitoring factory planning processes using the VPI approach. Hence, critical stages can be simulated in advance to support factory planning projects.

Keywords: Virtual Production Intelligence; Digital Factory; Factory Planning; Performance Indicators; Data Warehousing; Decision Support (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-08816-7_65

Ordering information: This item can be ordered from
http://www.springer.com/9783319088167

DOI: 10.1007/978-3-319-08816-7_65

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().