Details
| Original language | English |
|---|---|
| Pages (from-to) | 92-97 |
| Number of pages | 6 |
| Journal | Procedia CIRP |
| Volume | 32 |
| Publication status | Published - 22 Jun 2015 |
| Event | 5th Conference on Learning Factories 2015 - Bochum, Germany Duration: 7 Jul 2015 → 8 Jul 2015 |
Abstract
Nowadays, production enterprises are faced with an array of challenges including increasing pressure regarding costs, demands for individualized products as well as the growing significance of logistic performance and costs, to name just a few. These in turn give rise to special requirements that the production planning, control and monitoring, among others, need to meet with suitable methods and techniques. Within this context, developments such as Industry 4.0 and cyber-physical production systems on the technology side, and approaches such as innovative learning factories for training employees hold great potential. This paper clarifies the advantages of cyber-physical systems in view of production planning, controlling and monitoring. Based on that, using the concept of IFA's Learning Factory, it describes how these can be specifically utilized in applying logistic models to improve order processing.
Keywords
- Cyber-physical production system, Learning factory, Logistics, Manufacturing engineering, Production planning and control
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Procedia CIRP, Vol. 32, 22.06.2015, p. 92-97.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Cyber-physical production systems combined with logistic models
T2 - 5th Conference on Learning Factories 2015
AU - Seitz, Kai Frederic
AU - Nyhuis, Peter
PY - 2015/6/22
Y1 - 2015/6/22
N2 - Nowadays, production enterprises are faced with an array of challenges including increasing pressure regarding costs, demands for individualized products as well as the growing significance of logistic performance and costs, to name just a few. These in turn give rise to special requirements that the production planning, control and monitoring, among others, need to meet with suitable methods and techniques. Within this context, developments such as Industry 4.0 and cyber-physical production systems on the technology side, and approaches such as innovative learning factories for training employees hold great potential. This paper clarifies the advantages of cyber-physical systems in view of production planning, controlling and monitoring. Based on that, using the concept of IFA's Learning Factory, it describes how these can be specifically utilized in applying logistic models to improve order processing.
AB - Nowadays, production enterprises are faced with an array of challenges including increasing pressure regarding costs, demands for individualized products as well as the growing significance of logistic performance and costs, to name just a few. These in turn give rise to special requirements that the production planning, control and monitoring, among others, need to meet with suitable methods and techniques. Within this context, developments such as Industry 4.0 and cyber-physical production systems on the technology side, and approaches such as innovative learning factories for training employees hold great potential. This paper clarifies the advantages of cyber-physical systems in view of production planning, controlling and monitoring. Based on that, using the concept of IFA's Learning Factory, it describes how these can be specifically utilized in applying logistic models to improve order processing.
KW - Cyber-physical production system
KW - Learning factory
KW - Logistics
KW - Manufacturing engineering
KW - Production planning and control
UR - http://www.scopus.com/inward/record.url?scp=84939839419&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2015.02.220
DO - 10.1016/j.procir.2015.02.220
M3 - Conference article
AN - SCOPUS:84939839419
VL - 32
SP - 92
EP - 97
JO - Procedia CIRP
JF - Procedia CIRP
SN - 2212-8271
Y2 - 7 July 2015 through 8 July 2015
ER -