Introduction of an Economic Assessment Approach for Factory Planning

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Rieke, L.; Cevirgen, C.; Nyhuis, P.: Introduction of an Economic Assessment Approach for Factory Planning. In: Journal of Production Systems and Logistics 1 (2021), 9. DOI:

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Sum total of downloads: 245

Factories are characterised by a long life cycle and substantial investment costs. In particular, factory planning and reorganisation lead to capital-intensive investments and have a significant influence on the liquidity of companies. Reliable data are the basic prerequisite for a valid economic assessment of intended factory planning projects. However, especially in early planning phases, the available data are often uncertain and inaccurate. This problem significantly impedes the early and precise dimensioning of operating resources, production areas and employees as well as their cost calculation for planned factories. This also increases the risk of erroneous cost-benefit estimates and potential misinvestments. As a result, an early economic assessment and cost estimate for planned factories is essential. Until now, a holistic approach that can quickly and precisely determine investment costs of different planning variants in an early factory planning phase with only limited and uncertain information is not yet available. In order to close this research gap, a holistic approach for calculating investment costs in an early stage of factory planning is in development within the framework of "ELIAS", a collaborate research project of the Institute of Production Systems and Logistics at Leibniz University Hannover and the GREAN GmbH. The central objective of this research project is the software-based development of an investment cost calculator in order to carry out an economic efficiency assessment for potential factory planning projects at an early stage. This article provides both a brief summary of the need and innovative capability of the research idea and the structured procedure for creating a planning tool that closes the research gap described above. By this means, companies are supported in making future-proof decisions at an early stage despite uncertain and inaccurate data.
License of this version: CC BY 3.0 DE
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2021
Appears in Collections:Volume 1 (2021)
Volume 1 (2021)

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pos. country downloads
total perc.
1 image of flag of Germany Germany 166 67.76%
2 image of flag of United States United States 23 9.39%
3 image of flag of Czech Republic Czech Republic 11 4.49%
4 image of flag of China China 9 3.67%
5 image of flag of Estonia Estonia 6 2.45%
6 image of flag of India India 5 2.04%
7 image of flag of United Kingdom United Kingdom 5 2.04%
8 image of flag of Russian Federation Russian Federation 4 1.63%
9 image of flag of No geo information available No geo information available 3 1.22%
10 image of flag of Austria Austria 2 0.82%
    other countries 11 4.49%

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