When improving industrial process chains in terms of productivity it is becoming more and more important to not only consider the static, but also the dynamic behavior of value streams. The effects of intended changes on production systems often are unknown and could underlie vast variations due to the planned outcome. In order to validate such changes before implementation, the use of material flow simulation is widely discussed in research and industrial practice. Such optimization projects usually require the collaboration of production system and simulation experts. Through the increased dissemination of various simulation tools on the market as well as multiple simulation methods available (discrete event, agent based and system dynamics) the actual selection of a suitable simulation setting is a challenging task. To support such optimization teams in the selection of an appropriate simulation method a decision making approach based on comparative criteria is shown and discussed in this article, concluding with a case study. 

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.

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In this article a procedure is introduced to improve transparency and reliability of results for the selection of material flow design alternatives including machine tools and other capital-intensive goods. In the design phase of material flow planning projects, key performance indicators (KPIs) for design alternatives including processing as well as intralogistics elements can be derived using simulation. Using the state of the art method in value stream design and simulation often volatile input data is taken into account only in the simulation itself, but not in the downstream comparison of alternative designs, which could lead to imprecise conclusions and therefore to wrong investment decisions. To overcome this issue and to consider variability in the whole simulation phase and a subsequent decision making process, a multi-criteria decision analysis (MCDA) with two fuzzy representations is proposed and discussed here with the aim of helping practitioners to get more competitive value streams. A further goal of the article is the comparison between both forms used for fuzzy representation. Using the design example of machine tool-intralogistics systems obtained results are discussed.