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Understanding and Assessing Complexity in Cutting Tool Management

Bosch, Eva ; Metternich, Joachim (2018)
Understanding and Assessing Complexity in Cutting Tool Management.
In: Procedia CIRP, 72
doi: 10.1016/j.procir.2018.03.108
Article, Bibliographie

Abstract

A high tool availability is usually named the most important goal in tool management. Ensuring that the tools are provided as required frequently results in excessive tool inventories and thus in high capital commitment costs. Modularization is one possibility to reduce the tool inventory by dismantling the entire system in subsystems, so-called modules. The utilization of modules is advantageous for tools if a high tool variety is needed. Since the trend towards a high product variety is continuing, tool variety is increasing as well. Therefore, the modularization of cutting tools is a current topic in research and industry. Advantages such as reduced setup times, the possibility of combining various components and using them on machines independent of their interface are going along. Although, there are also some disadvantages. One of the main disadvantages is the increased complexity in the tool cycle, especially in the tool assembly process. Even though there is high optimization potential in managing the complexity, it has not been addressed in research so far, but needs to be understood and assessed before being able to manage it. Therefore, approaches for understanding and assessing the complexity of the tool assembly process of modularized cutting tools are presented in this paper. In this context, well-known methods for assessing complexity such as the Variant Tree and the Petri-Net are checked for their suitability for cutting tool management.

Item Type: Article
Erschienen: 2018
Creators: Bosch, Eva ; Metternich, Joachim
Type of entry: Bibliographie
Title: Understanding and Assessing Complexity in Cutting Tool Management
Language: English
Date: 2018
Publisher: Elsevier B.V.
Journal or Publication Title: Procedia CIRP
Volume of the journal: 72
DOI: 10.1016/j.procir.2018.03.108
Abstract:

A high tool availability is usually named the most important goal in tool management. Ensuring that the tools are provided as required frequently results in excessive tool inventories and thus in high capital commitment costs. Modularization is one possibility to reduce the tool inventory by dismantling the entire system in subsystems, so-called modules. The utilization of modules is advantageous for tools if a high tool variety is needed. Since the trend towards a high product variety is continuing, tool variety is increasing as well. Therefore, the modularization of cutting tools is a current topic in research and industry. Advantages such as reduced setup times, the possibility of combining various components and using them on machines independent of their interface are going along. Although, there are also some disadvantages. One of the main disadvantages is the increased complexity in the tool cycle, especially in the tool assembly process. Even though there is high optimization potential in managing the complexity, it has not been addressed in research so far, but needs to be understood and assessed before being able to manage it. Therefore, approaches for understanding and assessing the complexity of the tool assembly process of modularized cutting tools are presented in this paper. In this context, well-known methods for assessing complexity such as the Variant Tree and the Petri-Net are checked for their suitability for cutting tool management.

Uncontrolled Keywords: tool variety, tool modularization, variant tree, petri-net
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW)
16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) > Management of Industrial Production
16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) > Machining Technology (2021 merged in TEC Fertigungstechnologie)
Date Deposited: 29 Jun 2018 11:19
Last Modified: 11 Jul 2023 09:03
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