Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology

The concept of repair and restoration using additive manufacturing (AM) is to build new metal layers on a broken part. It is beneficial for complex parts that are no longer available in the market. Optimization methods are used to solve product design problems to produce efficient and highly sustain...
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Autor*in:	Hiyam Adil Habeeb [verfasserIn] Dzuraidah Abd Wahab [verfasserIn] Abdul Hadi Azman [verfasserIn] Mohd Rizal Alkahari [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	additive manufacturing repair and restoration design optimization design for additive manufacturing artificial intelligence hybrid method

Übergeordnetes Werk:	In: Metals - MDPI AG, 2012, 13(2023), 3, p 490
Übergeordnetes Werk:	volume:13 ; year:2023 ; number:3, p 490

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/met13030490

Katalog-ID:	DOAJ087294532

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language	English
source	In Metals 13(2023), 3, p 490 volume:13 year:2023 number:3, p 490
sourceStr	In Metals 13(2023), 3, p 490 volume:13 year:2023 number:3, p 490
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callnumber-first	T - Technology
author	Hiyam Adil Habeeb
spellingShingle	Hiyam Adil Habeeb misc TN1-997 misc additive manufacturing misc repair and restoration misc design optimization misc design for additive manufacturing misc artificial intelligence misc hybrid method misc Mining engineering. Metallurgy Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology
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topic_title	TN1-997 Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology additive manufacturing repair and restoration design optimization design for additive manufacturing artificial intelligence hybrid method
topic	misc TN1-997 misc additive manufacturing misc repair and restoration misc design optimization misc design for additive manufacturing misc artificial intelligence misc hybrid method misc Mining engineering. Metallurgy
topic_unstemmed	misc TN1-997 misc additive manufacturing misc repair and restoration misc design optimization misc design for additive manufacturing misc artificial intelligence misc hybrid method misc Mining engineering. Metallurgy
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title	Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology
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title_sort	design optimization method based on artificial intelligence (hybrid method) for repair and restoration using additive manufacturing technology
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title_auth	Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology
abstract	The concept of repair and restoration using additive manufacturing (AM) is to build new metal layers on a broken part. It is beneficial for complex parts that are no longer available in the market. Optimization methods are used to solve product design problems to produce efficient and highly sustainable products. Design optimization can improve the design of parts to improve the efficiency of the repair and restoration process using additive manufacturing during the end-of-life (EoL) phase. In this paper, the objective is to review the strategies for remanufacturing and restoration of products during or at the EoL phase and facilitate the process using AM. Design optimization for remanufacturing is important to reduce repair and restoration time. This review paper focuses on the main challenges and constraints of AM for repair and restoration. Various AI techniques, including the hybrid method that can be integrated into the design of AM, are analyzed and presented. This paper highlights the research gap and provides recommendations for future research directions. In conclusion, the combination of artificial neural network (ANN) algorithms with genetic algorithms as a hybrid method is a key solution in solving limitations and is the future for repair and restoration using additive manufacturing.
abstractGer	The concept of repair and restoration using additive manufacturing (AM) is to build new metal layers on a broken part. It is beneficial for complex parts that are no longer available in the market. Optimization methods are used to solve product design problems to produce efficient and highly sustainable products. Design optimization can improve the design of parts to improve the efficiency of the repair and restoration process using additive manufacturing during the end-of-life (EoL) phase. In this paper, the objective is to review the strategies for remanufacturing and restoration of products during or at the EoL phase and facilitate the process using AM. Design optimization for remanufacturing is important to reduce repair and restoration time. This review paper focuses on the main challenges and constraints of AM for repair and restoration. Various AI techniques, including the hybrid method that can be integrated into the design of AM, are analyzed and presented. This paper highlights the research gap and provides recommendations for future research directions. In conclusion, the combination of artificial neural network (ANN) algorithms with genetic algorithms as a hybrid method is a key solution in solving limitations and is the future for repair and restoration using additive manufacturing.
abstract_unstemmed	The concept of repair and restoration using additive manufacturing (AM) is to build new metal layers on a broken part. It is beneficial for complex parts that are no longer available in the market. Optimization methods are used to solve product design problems to produce efficient and highly sustainable products. Design optimization can improve the design of parts to improve the efficiency of the repair and restoration process using additive manufacturing during the end-of-life (EoL) phase. In this paper, the objective is to review the strategies for remanufacturing and restoration of products during or at the EoL phase and facilitate the process using AM. Design optimization for remanufacturing is important to reduce repair and restoration time. This review paper focuses on the main challenges and constraints of AM for repair and restoration. Various AI techniques, including the hybrid method that can be integrated into the design of AM, are analyzed and presented. This paper highlights the research gap and provides recommendations for future research directions. In conclusion, the combination of artificial neural network (ANN) algorithms with genetic algorithms as a hybrid method is a key solution in solving limitations and is the future for repair and restoration using additive manufacturing.
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title_short	Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology
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