Evidence map›Paper›PMID 38625342›Full record

ReviewProgress in additive manufacturing2022

Additive manufacturing for biomedical applications: a review on classification, energy consumption, and its appreciable role since COVID-19 pandemic.

Mudassar Rehman, Wang Yanen, Ray Tahir Mushtaq, Kashif Ishfaq, Sadaf Zahoor, Ammar Ahmed, M Saravana Kumar, Thierno Gueyee, Md Mazedur Rahman, Jakia Sultana

Erratum issuedAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Progress in additive manufacturing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Mudassar RehmanDepartment of Industry Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xian, 710072 China.
Wang YanenDepartment of Industry Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xian, 710072 China.ORCID 0000-0003-0092-8549
Ray Tahir MushtaqDepartment of Industry Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xian, 710072 China.
Kashif IshfaqDepartment of Industrial and Manufacturing Engineering, University of Engineering and Technology, Lahore, 54890 Pakistan.
Sadaf ZahoorDepartment of Industrial and Manufacturing Engineering, University of Engineering and Technology, Lahore, 54890 Pakistan.
Ammar AhmedDepartment of Industry Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xian, 710072 China.
M Saravana KumarGraduate Institute of Manufacturing Technology, National Taipei University of Technology, Taipei, 10608 Taiwan.
Thierno GueyeeDepartment of Industry Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xian, 710072 China.
Md Mazedur RahmanDepartment of Industry Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xian, 710072 China.
Jakia SultanaDepartment of Industry Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xian, 710072 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The exponential rise of healthcare problems like human aging and road traffic accidents have developed an intrinsic challenge to biomedical sectors concerning the arrangement of patient-specific biomedical products. The additively manufactured implants and scaffolds have captured global attention over the last two decades concerning their printing quality and ease of manufacturing. However, the inherent challenges associated with additive manufacturing (AM) technologies, namely process selection, level of complexity, printing speed, resolution, biomaterial choice, and consumed energy, still pose several limitations on their use. Recently, the whole world has faced severe supply chain disruptions of personal protective equipment and basic medical facilities due to a respiratory disease known as the coronavirus (COVID-19). In this regard, local and global AM manufacturers have printed biomedical products to level the supply-demand equation. The potential of AM technologies for biomedical applications before, during, and post-COVID-19 pandemic alongwith its relation to the industry 4.0 (I4.0) concept is discussed herein. Moreover, additive manufacturing technologies are studied in this work concerning their working principle, classification, materials, processing variables, output responses, merits, challenges, and biomedical applications. Different factors affecting the sustainable performance in AM for biomedical applications are discussed with more focus on the comparative examination of consumed energy to determine which process is more sustainable. The recent advancements in the field like 4D printing and 5D printing are useful for the successful implementation of I4.0 to combat any future pandemic scenario. The potential of hybrid printing, multi-materials printing, and printing with smart materials, has been identified as hot research areas to produce scaffolds and implants in regenerative medicine, tissue engineering, and orthopedic implants.

Indexed as

3D bioprintingAdditive manufacturingBiomedical applicationsCOVID-19Energy consumptionImplantsIndustry 4.0Tissue engineering

Identifiers

PMID38625342
PMCPMC9793824

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.