Intelligent systems for additive manufacturing-based repair in remanufacturing: a systematic review of its potential

Siti Syahara Mad Yusoh; Dzuraidah Abd Wahab; Hiyam Adil Habeeb; Abdul Hadi Azman

doi:10.7717/peerj-cs.808

Intelligent systems for additive manufacturing-based repair in remanufacturing: a systematic review of its potential

PeerJ Comput Sci. 2021 Dec 10:7:e808. doi: 10.7717/peerj-cs.808. eCollection 2021.

Authors

Siti Syahara Mad Yusoh¹, Dzuraidah Abd Wahab^{1

2}, Hiyam Adil Habeeb^{1

3}, Abdul Hadi Azman^{1

2}

Affiliations

¹ Department of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
² Centre for Automotive Research, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM Bangi, Selangor, Malaysia.
³ Technical College Al-Mussaib, Al-Furat Al-Awsat Technical University, Babylon, Iraq.

Abstract

The conventional component repair in remanufacturing involves human decision making that is influenced by several factors such as conditions of incoming cores, modes of failure, severity of damage, features and geometric complexities of cores and types of reparation required. Repair can be enhanced through automation using additive manufacturing (AM) technology. Advancements in AM have led to the development of directed energy deposition and laser cladding technology for repair of damaged parts and components. The objective of this systematic literature review is to ascertain how intelligent systems can be integrated into AM-based repair, through artificial intelligence (AI) approaches capable of supporting the nature and process of decision making during repair. The integration of intelligent systems in AM repair is expected to enhance resource utilization and repair efficiency during remanufacturing. Based on a systematic literature review of articles published during 2005-2021, the study analyses the activities of conventional repair in remanufacturing, trends in the applications of AM for repair using the current state-of-the-art technology and how AI has been deployed to facilitate repair. The study concludes with suggestions on research areas and opportunities that will further enhance the automation of component repair during remanufacturing using intelligent AM systems.

Keywords: Additive manufacturing; Artificial intelligence; Conventional methods; Intelligent systems; Repair and restoration.

Grants and funding

The authors received funding from the Konsortium Kecemerlangan Penyelidikan (JPT(BKPI)1000/016/018/25(72)), provided by the Ministry of Higher Education of Malaysia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.