Online-scheduling using past and real-time data: An assessment by discrete event simulation using exponential smoothing

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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, Vol. 19, 19.11.2017, p. 158-163.

Research output: Journal contributionsJournal articlesResearchpeer-review

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@article{30ec5220528941db8aca4c48209d8b44,
title = "Online-scheduling using past and real-time data: An assessment by discrete event simulation using exponential smoothing",
abstract = "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.",
keywords = "Cyber-physical production systems, Discrete event simulation, Exponential smoothing, Human productivity factors, On-line scheduling, Engineering",
author = "Jens Heger and Sebastian Grundstein and Michael Freitag",
year = "2017",
month = nov,
day = "19",
doi = "10.1016/j.cirpj.2017.07.003",
language = "English",
volume = "19",
pages = "158--163",
journal = "CIRP Journal of Manufacturing Science and Technology",
issn = "1755-5817",
publisher = "Elsevier B.V.",

}

RIS

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 -