Towards Automated Remanufacturing Process With Additive Manufacturing

Aprilia, Ayu Riana Devi; Nguyen, Keith Wei Liang; Khairyanto, Ahmad; Pang, Wee Ching; Tor, Shu Beng; Seet, Gerald

doi:10.25341/d4sw2n

Cited by 3 publications

(4 citation statements)

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“…These problems generate the gap to achieve an automated repairing process. Aprilia et al [16] concluded an urgent need to develop algorithms for damage detection, localization, and tool-path generation that do not require human involvement.…”

Section: Introductionmentioning

confidence: 99%

Vision-based spatial damage localization method for autonomous robotic laser cladding repair processes

Imam

Al-Musaibeli

Zheng

et al. 2023

Robotics and Computer-Integrated Manufacturing

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Section: Introductionmentioning

confidence: 99%

Vision-based spatial damage localization method for autonomous robotic laser cladding repair processes

Imam

Al-Musaibeli

Zheng

et al. 2023

Robotics and Computer-Integrated Manufacturing

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“…These components have been the subject of several studies considering that they are critical parts in turbine engines and suffer diverse damages over time, such as deformations, wear, and cracks [4], [6], [10]- [12]. Mainly, these works allowed the definition of the steps of the repair process chain, which include: the damaged part 3D scanning; the identification of the defect; the recognition of the defect geometry and volume through a boolean comparison between the nominal model and the scanned model; the reconstruction of the nominal model in the case that does not exist; the generation of trajectories; simulation; the rebuilding process by LMD; and finishing processes by milling processes [8], [10], [12], [13]. Even with the repair process of metal parts chain well defined, this type of repair process has yet to be widespread in the industry since, in most studies, the methodologies presented by many researchers focus the investigation on specific parts to reconstruct, for which the geometry and functions are known a priori, such as turbine blades of aero-engines.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Metallic Parts Defects to Determine Repair Process Strategies through Laser Metal Deposition

da Cruz,

Afonso,

de Oliveira

2023

KEM

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With technological advances, additive manufacturing processes have been gaining prominence in several industrial areas including maintenance, repair, and overhaul (MRO) processes. A process with great potential for repairing and rebuilding metal parts is laser metal deposition (LMD) technology. Despite the high potential, LMD implementation in the repair industry is not straightforward, due to the geometry variability of parts and damages to be repaired. This paper presents a repairability study that evaluates the remaining volume of the repair of different types of damages in AISI 316L parts by LMD, and determines the most appropriate deposition strategies to adapt to the repair process. This study involves the characterization and classification of common defects in metallic parts and the development of a design of experiments, in which, given the damage geometry, volume, and location, the best repair toolpath to be adopted and the ideal parameterization for the repair process are determined. The ability to correct part damage is assessed from a geometric, mechanical and energetic approach, and explores the possibility of including LMD in an adaptive and intelligent MRO system. The result of this work establishes a new deposition strategy approach based on a modified contour-parallel deposition strategy for repairing metal parts. This study also demonstrates that in surface damage cases, a fixed point strategy is highly effective, especially when using higher laser power values and larger laser spot diameters, enabling an easier process automation. However, in edge and corner damage cases, the best repair approach is using trajectory strategies that constitute material support between deposition tracks and layers. Additionally, it is demonstrated that the corners are the most critical zones that require temperature control throughout the entire repair process.

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“… Yusop, Wahab & Saibani (2015) described remanufacturing as one of the factors in achieving environmental sustainability and has a direct positive effect on economic growth in terms of cost saving and profit obligations. Aprilia et al (2018) noted that high-value components such as turbine blades, impeller and shafts are preferred to be remanufactured rather than replaced with new ones.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, automating the process is crucial such that productivity and process consistency can be controlled and improved. Aprilia et al (2018) noted that manual remanufacturing is prone to human error, inconsistency in output quality and labour intensive with a high cost. Automating the activity is crucial to enhance productivity and process consistency.…”

Section: Introductionmentioning

confidence: 99%

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

Yusoh

Wahab

Habeeb

et al. 2021

PeerJ Computer Science

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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.

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Towards Automated Remanufacturing Process With Additive Manufacturing

Cited by 3 publications

References 0 publications

Vision-based spatial damage localization method for autonomous robotic laser cladding repair processes

Vision-based spatial damage localization method for autonomous robotic laser cladding repair processes

Evaluation of Metallic Parts Defects to Determine Repair Process Strategies through Laser Metal Deposition

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

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