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CAD-based approach for early-stage design for optimizing aircraft maintenance reachability

  • Burhan Şahin

    Dr. Burhan Şahin, born in 1990, is chief engineer of DMU (Digital Mock-Up) management in TAI-Turkish Aerospace Industry, Ankara, Turkey. He received BSc degree in Mechanical Engineering from Celal Bayar University, Turkey, in 2012. He received PhD degree in Manufacturing Engineering from Celal Bayar University, Turkey, in 2022. He worked as researcher for Arcelik R&D, Turkey, from 2012 to 2019. His research interests are structural design, production, CAD design, plastic polymers, systems engineering, composite materials, prototyping, project management, and DMU management of aerial vehicles.

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    and Emre Doruk

    Dr. Emre Doruk, born in 1987, is a researcher in TAI-Turkish Aerospace Industry, Ankara, Turkey. He received BSc degree in Mechanical Engineering from Uludag University, Turkey in 2010. He received PhD degree in Manufacturing Engineering from Sakarya University, Turkey in 2019. He worked as researcher for Tofas-Fiat R&D, Turkey from 2014 to 2019. His research interests are light-weighting, AHSS, aluminum alloy, fatigue and damage tolerance, rapid prototyping, sheet metal forming, and crashworthiness.

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Published/Copyright: August 27, 2025
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Abstract

Integrating maintenance considerations into aircraft design is essential for ensuring both operational efficiency and reliability. One of the key factors in aircraft selection and facilitating maintenance is the accessibility of critical components. This study focuses on the design and enhancement of design-based maintenance access panels during the early stages of conceptual design. The primary goal is to develop a methodology for identifying optimal locations for access panels, thereby minimizing the need for modifications during later design phases. The approach considers various factors, including Mean Time Between Failures (MTBF), maintenance intervals, and accessibility. The research encompasses several phases, such as evaluating maintenance needs, establishing a product lifecycle framework, and implementing Digital Mock-Up (DMU) activities based on Computer Aided Design (CAD) data and product development processes. This methodology fosters collaboration between design and maintenance teams, employing iterative techniques to develop access panels based on advanced DMU and CAD models. The findings of this research underscore the importance of a collaborative approach, the necessity of integrating maintenance considerations early in the design process, and the advantages of using design-based tools to optimize access panel design. Adopting this methodology helps aircraft manufacturers improve maintainability, reduce maintenance costs, and boost efficiency.


Corresponding author: Emre Doruk, Turkish Aerospace Industries Inc, Ankara, Türkiye, E-mail:

About the authors

Burhan Şahin

Dr. Burhan Şahin, born in 1990, is chief engineer of DMU (Digital Mock-Up) management in TAI-Turkish Aerospace Industry, Ankara, Turkey. He received BSc degree in Mechanical Engineering from Celal Bayar University, Turkey, in 2012. He received PhD degree in Manufacturing Engineering from Celal Bayar University, Turkey, in 2022. He worked as researcher for Arcelik R&D, Turkey, from 2012 to 2019. His research interests are structural design, production, CAD design, plastic polymers, systems engineering, composite materials, prototyping, project management, and DMU management of aerial vehicles.

Emre Doruk

Dr. Emre Doruk, born in 1987, is a researcher in TAI-Turkish Aerospace Industry, Ankara, Turkey. He received BSc degree in Mechanical Engineering from Uludag University, Turkey in 2010. He received PhD degree in Manufacturing Engineering from Sakarya University, Turkey in 2019. He worked as researcher for Tofas-Fiat R&D, Turkey from 2014 to 2019. His research interests are light-weighting, AHSS, aluminum alloy, fatigue and damage tolerance, rapid prototyping, sheet metal forming, and crashworthiness.

Acknowledgment

The authors gratefully acknowledge TAI-Turkish Aerospace Industry for their technical support.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/mt-2025-0100).


Published Online: 2025-08-27
Published in Print: 2025-10-27

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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