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Tool management optimisation through traceability and tool wear prediction in the aviation industry

Schreiber, Markus ; Weisbrod, Nik ; Ziegenbein, Amina ; Metternich, Joachim (2025)
Tool management optimisation through traceability and tool wear prediction in the aviation industry.
In: Production Engineering : Research and Development, 2023, 17 (2)
doi: 10.26083/tuprints-00028413
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Tool management optimisation through traceability and tool wear prediction in the aviation industry
Language: English
Date: 16 January 2025
Place of Publication: Darmstadt
Year of primary publication: April 2023
Place of primary publication: Berlin ; Heidelberg
Publisher: Springer
Journal or Publication Title: Production Engineering : Research and Development
Volume of the journal: 17
Issue Number: 2
DOI: 10.26083/tuprints-00028413
Corresponding Links:
Origin: Secondary publication DeepGreen
Abstract:

The aviation industry is characterised by high manufacturing requirements of products with difficult-to-machine materials to ensure quality and safety. Standardised and secured processes and transparency in resource and material flows within production are important requirements for meeting these safety and quality standards while staying competitive on the market. Those requirements also apply to a companies’ tool management and are to be met with an optimised tool change strategy considering economic aspects at the same time. The article presents a use case of a company belonging to the aviation industry striving to achieve goals concerning costs, quality, and time in their tool management. To realise potential improvements a retrofitting traceability solution is illustrated enabling data-based maintenance strategies in the use case. The traceability solution aims to provide transparency about tool inventory, the location of tools on the shop floor and functions as data acquisition system to realise the individual tracking of used tools. Using the individual tracking data of tools and matching them with relevant machining data enables the application of data-based maintenance strategies pointing out possibilities to indicate the tools’ wear state. This approach offers benefits such as reducing the scrap rate or machining down times with a direct impact on quality, costs, or lead times of customer orders.

Uncontrolled Keywords: Tool cycle improvement, Tool maintenance, Predictive analytics, Retrofitting, Remaining useful lifetime, Data-based transparency
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-284130
Additional Information:

Issue: Digital-based Production

Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
600 Technology, medicine, applied sciences > 670 Manufacturing
Divisions: 16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) > Management of Industrial Production
Date Deposited: 16 Jan 2025 14:19
Last Modified: 16 Jan 2025 14:20
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/28413
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