Mad Yusoh Siti Syahara, Abd Wahab Dzuraidah, Adil Habeeb Hiyam, Azman Abdul Hadi
Department of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Centre for Automotive Research, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM Bangi, Selangor, Malaysia.
PeerJ Comput Sci. 2021 Dec 10;7:e808. doi: 10.7717/peerj-cs.808. eCollection 2021.
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.
再制造中的传统部件修复涉及人为决策，这受到多个因素的影响，如进厂型芯的状况、失效模式、损坏程度、型芯的特征和几何复杂性以及所需的修复类型。可以通过使用增材制造（AM）技术实现自动化来加强修复。增材制造的进步推动了用于修复受损零部件的定向能量沉积和激光熔覆技术的发展。本系统文献综述的目的是确定如何通过能够支持修复过程中的决策性质和过程的人工智能（AI）方法，将智能系统集成到基于增材制造的修复中。智能系统在增材制造修复中的集成有望提高再制造过程中的资源利用率和修复效率。基于对2005年至2021年发表的文章的系统文献综述，该研究分析了再制造中传统修复的活动、使用当前最先进技术进行增材制造修复的应用趋势以及人工智能如何被用于促进修复。该研究最后对研究领域和机会提出了建议，这些领域和机会将进一步提高使用智能增材制造系统进行再制造过程中部件修复的自动化程度。
