Modeling and analyzing dynamic cycle networks for manufacturing planning

C. Plehn; J. Koch; K. Diepold; B. Stahl; B. Lohman; G. Reinhart; M. F. Zäh

doi:10.1016/j.procir.2015.04.025

Modeling and analyzing dynamic cycle networks for manufacturing planning

C. Plehn, J. Koch, K. Diepold, B. Stahl, B. Lohman, G. Reinhart, M. F. Zäh

Technical University of Munich

Research output: Contribution to journal › Conference article › peer-review

10 Scopus citations

Abstract

Knowledge about cyclic influences and their interdependencies supports the prediction of future changes in manufacturing systems and is thus highly valuable for manufacturing planning. Based on system dynamics and former research regarding cycle management, a dynamic cycle network is developed. This enables quantitative analysis and comprehension of cycles within the network, helping to understand future behavior of cyclic influences in manufacturing and to anticipate their potential effects. The results contribute to the development of a planning framework for continuous production planning by further elaborating the innovative concept of cycle management in manufacturing.

Original language	English
Pages (from-to)	149-154
Number of pages	6
Journal	Procedia CIRP
Volume	28
DOIs	https://doi.org/10.1016/j.procir.2015.04.025
State	Published - 2015
Event	3rd CIRP Global Web Conference on Production Engineering Research: Advancement Beyond State of the Art, CIRPe 2014 - Naples, Italy Duration: 3 Jun 2014 → 5 Jun 2014

Keywords

Changeability
Changeable manufacturing
Cycle management
Cyclic influences
Manufacturing planning
System dynamics

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10.1016/j.procir.2015.04.025

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title = "Modeling and analyzing dynamic cycle networks for manufacturing planning",

abstract = "Knowledge about cyclic influences and their interdependencies supports the prediction of future changes in manufacturing systems and is thus highly valuable for manufacturing planning. Based on system dynamics and former research regarding cycle management, a dynamic cycle network is developed. This enables quantitative analysis and comprehension of cycles within the network, helping to understand future behavior of cyclic influences in manufacturing and to anticipate their potential effects. The results contribute to the development of a planning framework for continuous production planning by further elaborating the innovative concept of cycle management in manufacturing.",

keywords = "Changeability, Changeable manufacturing, Cycle management, Cyclic influences, Manufacturing planning, System dynamics",

author = "C. Plehn and J. Koch and K. Diepold and B. Stahl and B. Lohman and G. Reinhart and Z{\"a}h, {M. F.}",

note = "Publisher Copyright: {\textcopyright} 2014 The Authors. Published by Elsevier B.V.; 3rd CIRP Global Web Conference on Production Engineering Research: Advancement Beyond State of the Art, CIRPe 2014 ; Conference date: 03-06-2014 Through 05-06-2014",

year = "2015",

doi = "10.1016/j.procir.2015.04.025",

language = "English",

volume = "28",

pages = "149--154",

journal = "Procedia CIRP",

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publisher = "Elsevier B.V.",

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TY - JOUR

T1 - Modeling and analyzing dynamic cycle networks for manufacturing planning

AU - Plehn, C.

AU - Koch, J.

AU - Diepold, K.

AU - Stahl, B.

AU - Lohman, B.

AU - Reinhart, G.

AU - Zäh, M. F.

PY - 2015

Y1 - 2015

N2 - Knowledge about cyclic influences and their interdependencies supports the prediction of future changes in manufacturing systems and is thus highly valuable for manufacturing planning. Based on system dynamics and former research regarding cycle management, a dynamic cycle network is developed. This enables quantitative analysis and comprehension of cycles within the network, helping to understand future behavior of cyclic influences in manufacturing and to anticipate their potential effects. The results contribute to the development of a planning framework for continuous production planning by further elaborating the innovative concept of cycle management in manufacturing.

AB - Knowledge about cyclic influences and their interdependencies supports the prediction of future changes in manufacturing systems and is thus highly valuable for manufacturing planning. Based on system dynamics and former research regarding cycle management, a dynamic cycle network is developed. This enables quantitative analysis and comprehension of cycles within the network, helping to understand future behavior of cyclic influences in manufacturing and to anticipate their potential effects. The results contribute to the development of a planning framework for continuous production planning by further elaborating the innovative concept of cycle management in manufacturing.

KW - Changeability

KW - Changeable manufacturing

KW - Cycle management

KW - Cyclic influences

KW - Manufacturing planning

KW - System dynamics

UR - http://www.scopus.com/inward/record.url?scp=84939511266&partnerID=8YFLogxK

U2 - 10.1016/j.procir.2015.04.025

DO - 10.1016/j.procir.2015.04.025

M3 - Conference article

AN - SCOPUS:84939511266

SN - 2212-8271

VL - 28

SP - 149

EP - 154

JO - Procedia CIRP

JF - Procedia CIRP

T2 - 3rd CIRP Global Web Conference on Production Engineering Research: Advancement Beyond State of the Art, CIRPe 2014

Y2 - 3 June 2014 through 5 June 2014

ER -

Modeling and analyzing dynamic cycle networks for manufacturing planning

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Keywords

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