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...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-02-01
|
| Series: | Metals |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4701/13/3/490 |
| _version_ | 1827748707939909632 |
|---|---|
| author | Hiyam Adil Habeeb Dzuraidah Abd Wahab Abdul Hadi Azman Mohd Rizal Alkahari |
| author_facet | Hiyam Adil Habeeb Dzuraidah Abd Wahab Abdul Hadi Azman Mohd Rizal Alkahari |
| author_sort | Hiyam Adil Habeeb |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T06:11:38Z |
| format | Article |
| id | doaj.art-c5b6177f9b364f638bf40c23e0400407 |
| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-03-11T06:11:38Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj.art-c5b6177f9b364f638bf40c23e04004072023-11-17T12:38:29ZengMDPI AGMetals2075-47012023-02-0113349010.3390/met13030490Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing TechnologyHiyam Adil Habeeb0Dzuraidah Abd Wahab1Abdul Hadi Azman2Mohd Rizal Alkahari3Department of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, MalaysiaDepartment of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, MalaysiaDepartment of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, MalaysiaFaculty of Mechanical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal 76100, MalaysiaThe 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.https://www.mdpi.com/2075-4701/13/3/490additive manufacturingrepair and restorationdesign optimizationdesign for additive manufacturingartificial intelligencehybrid method |
| spellingShingle | Hiyam Adil Habeeb Dzuraidah Abd Wahab Abdul Hadi Azman Mohd Rizal Alkahari Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology Metals additive manufacturing repair and restoration design optimization design for additive manufacturing artificial intelligence hybrid method |
| title | Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology |
| title_full | Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology |
| title_fullStr | Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology |
| title_full_unstemmed | Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology |
| title_short | Design Optimization Method Based on Artificial Intelligence (Hybrid Method) for Repair and Restoration Using Additive Manufacturing Technology |
| title_sort | design optimization method based on artificial intelligence hybrid method for repair and restoration using additive manufacturing technology |
| topic | additive manufacturing repair and restoration design optimization design for additive manufacturing artificial intelligence hybrid method |
| url | https://www.mdpi.com/2075-4701/13/3/490 |
| work_keys_str_mv | AT hiyamadilhabeeb designoptimizationmethodbasedonartificialintelligencehybridmethodforrepairandrestorationusingadditivemanufacturingtechnology AT dzuraidahabdwahab designoptimizationmethodbasedonartificialintelligencehybridmethodforrepairandrestorationusingadditivemanufacturingtechnology AT abdulhadiazman designoptimizationmethodbasedonartificialintelligencehybridmethodforrepairandrestorationusingadditivemanufacturingtechnology AT mohdrizalalkahari designoptimizationmethodbasedonartificialintelligencehybridmethodforrepairandrestorationusingadditivemanufacturingtechnology |