Online-scheduling using past and real-time data: An assessment by discrete event simulation using exponential smoothing
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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Online-scheduling using past and real-time data : An assessment by discrete event simulation using exponential smoothing. / Heger, Jens; Grundstein, Sebastian; Freitag, Michael.
in: CIRP - Journal of Manufacturing Science and Technology, Jahrgang 19, 19.11.2017, S. 158-163.Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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TY - JOUR
T1 - Online-scheduling using past and real-time data
T2 - An assessment by discrete event simulation using exponential smoothing
AU - Heger, Jens
AU - Grundstein, Sebastian
AU - Freitag, Michael
PY - 2017/11/19
Y1 - 2017/11/19
N2 - Often deviations occur in the execution of a production schedule because prediction of productivity is unrealistic. Therefore, researchers have shown huge interest in understanding and modelling productivity factors to consider them in planning and design of manufacturing systems. In contrast, this paper examines how productivity can be considered in online-scheduling using past and real-time data and which effect this has on the overall system performance. The discrete event simulation exemplarily considering human productivity factors shows promising results but also the need for more complex forecasting methods Future work will also consider other factors such as tool wear and disturbances.
AB - Often deviations occur in the execution of a production schedule because prediction of productivity is unrealistic. Therefore, researchers have shown huge interest in understanding and modelling productivity factors to consider them in planning and design of manufacturing systems. In contrast, this paper examines how productivity can be considered in online-scheduling using past and real-time data and which effect this has on the overall system performance. The discrete event simulation exemplarily considering human productivity factors shows promising results but also the need for more complex forecasting methods Future work will also consider other factors such as tool wear and disturbances.
KW - Cyber-physical production systems
KW - Discrete event simulation
KW - Exponential smoothing
KW - Human productivity factors
KW - On-line scheduling
KW - Engineering
UR - http://www.scopus.com/inward/record.url?scp=85029492005&partnerID=8YFLogxK
U2 - 10.1016/j.cirpj.2017.07.003
DO - 10.1016/j.cirpj.2017.07.003
M3 - Journal articles
AN - SCOPUS:85029492005
VL - 19
SP - 158
EP - 163
JO - CIRP Journal of Manufacturing Science and Technology
JF - CIRP Journal of Manufacturing Science and Technology
SN - 1755-5817
ER -