Evidence map›Paper›PMID 36616753›Full record

ReviewSensors (Basel, Switzerland)2022

A Comprehensive Review of Blockchain Technology-Enabled Smart Manufacturing: A Framework, Challenges and Future Research Directions.

Xin Guo, Geng Zhang, Yingfeng Zhang

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xin GuoSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
Geng ZhangSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
Yingfeng ZhangSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.

Funding

Key Project of National Natural Science Foundation of China U2001201
6 · The paper itself

Abstract

As a new generation of information technology, blockchain plays an important role in business and industrial innovation. The employment of blockchain technologies in industry has increased transparency, security and traceability, improved efficiency, and reduced costs of production activities. Many studies on blockchain technology-enabled system construction and performance optimization in Industry 4.0 have been carried out. However, blockchain technology and smart manufacturing have been individually researched in academia and industry, according to the literature. This survey aims to summarize the existing research to provide theoretical foundations for applying blockchain technology to smart manufacturing, thus creating a more reliable and authentic smart manufacturing system. In this regard, the literature related to four types of critical issues in smart manufacturing is introduced: data security, data sharing, trust mechanisms and system coordination issues. The corresponding blockchain solutions were reviewed and analyzed. Based on the insights obtained from the above analysis, a reference framework for blockchain technology-enabled smart manufacturing systems is put forward. The challenges and future research directions are also discussed to provide potential guides for achieving better utilization of this technology in smart manufacturing.

Indexed as

BlockchainCommerceComputer SecurityIndustryTechnologyblockchaindata securitydata sharingsmart manufacturingtrust mechanism

Identifiers

PMID36616753
PMCPMC9824102

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.