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Title: | Pick capacity model for cutting machine tools stored in a next generation Vertical Storage Machine | Authors: | Vanhauwermeiren, Pieter Juwet, Marc DEMEESTER, Eric |
Editors: | Vosniakos, GC | Issue Date: | 2021 | Publisher: | ELSEVIER SCIENCE BV | Source: | FAIM 2021, ELSEVIER SCIENCE BV, p. 479 -486 | Series/Report: | Procedia Manufacturing | Abstract: | Tools for a group of cutting machine tools in a workshop are often centrally stored, maintained and prepared for use. Using a vertical lift machine (VLM) allows orderly and space-saving storage. It is expected that the total time to prepare tools for delivery in the workshop depends on the chosen VLM architecture and on the strategy for organising the tools in the VLM. This research proposes a mathematical model for determining the total preparation time as a function of the number of items ordered for a series of jobs in the workshop. The model is specific applied for machine cutting tools. While previous research focussed on storage strategies for carrousel storage machines or the basic VLM architecture, this research focusses on five VLM architectures that can be combined with three storage strategies in the mathematical model. The model is largely parametric, allowing for specific numerical values as applicable to the workshop being calculated and allowing to use the technical performance parameters of the VLM. The model illustrates that both the choice of the designated VLM architecture and the choice of storage strategy can have a significant impact on the total time needed to prepare the tools. For both choices to be made, no general rule emerges: a calculation with the specific numerical values for the workshop concerned is appropriate. (C) 2021 The Authors. Published by Elsevier Ltd. | Notes: | Vanhauwermeiren, P (corresponding author), Katholieke Univ Leuven, Gebroders Smetstr 1, B-9000 Ghent, Belgium. pieter.vanhauwermeiren@kuleuven.be |
Keywords: | Vertical Lift Module;Pick Capacity;Machine Tools;Pick capacity Model | Document URI: | http://hdl.handle.net/1942/38834 | DOI: | 10.1016/j.promfg.2021.10.065 | ISI #: | 000864594500064 | Rights: | 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the FAIM 2021 | Category: | C1 | Type: | Proceedings Paper |
Appears in Collections: | Research publications |
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