ArticlePeerJ. Computer science2021
Intelligent systems for additive manufacturing-based repair in remanufacturing: a systematic review of its potential.
Article in PeerJ. Computer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Functional Materials for Additive Manufacturing: Materials Design, Processing, and Emerging Applications.Nanomaterials (Basel, Switzerland) · 2026Review
- Nursing Care Systematization with Case-Based Reasoning and Artificial Intelligence.Journal of healthcare engineering · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.