TU Darmstadt / ULB / TUbiblio

Learning to See Clear: Quantification and Multidimensional Assessment of Value Stream Mapping Alternatives Considering Variability

Rößler, Markus Philipp and Metternich, Joachim and Abele, Eberhard (2014):
Learning to See Clear: Quantification and Multidimensional Assessment of Value Stream Mapping Alternatives Considering Variability.
In: Business and Management Research, Sciedu Press, Canada, pp. 93-109, 3, (2), ISSN 1927-6001,
[Online-Edition: http://dx.doi.org/10.5430/bmr.v3n2p93],
[Article]

Abstract

The prior quantification and validation of future state maps in lean production and optimization projects mostly is not taken into consideration in the traditional value stream mapping approaches. Furthermore the implementation of future states is based upon the trial and error principle. The effects of proactively changing production systems often are unknown and could underlie vast variations due to the planned outcome. So for many managers hard facts are missing and the uncertainties included in such a value stream optimization project are very high. This prevents a necessary system change accompanied by the adoption of lean methods. Thus in this paper a comprehensive value stream optimization approach is presented which primarily focuses upon chances for prior static and dynamic future state map quantification. Under consideration of parameter variability a downstream multidimensional assessment of possible design alternatives is proposed using a fuzzy decision making method to facilitate transparency in the selection of the most adequate future state map. The method described in this paper will be discussed at an industrial case study.

Item Type: Article
Erschienen: 2014
Creators: Rößler, Markus Philipp and Metternich, Joachim and Abele, Eberhard
Title: Learning to See Clear: Quantification and Multidimensional Assessment of Value Stream Mapping Alternatives Considering Variability
Language: English
Abstract:

The prior quantification and validation of future state maps in lean production and optimization projects mostly is not taken into consideration in the traditional value stream mapping approaches. Furthermore the implementation of future states is based upon the trial and error principle. The effects of proactively changing production systems often are unknown and could underlie vast variations due to the planned outcome. So for many managers hard facts are missing and the uncertainties included in such a value stream optimization project are very high. This prevents a necessary system change accompanied by the adoption of lean methods. Thus in this paper a comprehensive value stream optimization approach is presented which primarily focuses upon chances for prior static and dynamic future state map quantification. Under consideration of parameter variability a downstream multidimensional assessment of possible design alternatives is proposed using a fuzzy decision making method to facilitate transparency in the selection of the most adequate future state map. The method described in this paper will be discussed at an industrial case study.

Journal or Publication Title: Business and Management Research, Sciedu Press, Canada
Volume: 3
Number: 2
Uncontrolled Keywords: Lean production, Value stream mapping, Quantification, Performance management, Variability, Fuzzy multi-criteria decision analysis
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Production Management, Technology and Machine Tools (PTW)
Date Deposited: 12 Sep 2014 11:56
Official URL: http://dx.doi.org/10.5430/bmr.v3n2p93
Export:

Optionen (nur für Redakteure)

View Item View Item