Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 215

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Industrial blockchain based framework for product lifecycle management in industry 4.0

Liu, X.L., Wang, W.M., Guo, Hanyang, Barenji, Ali Vatankhah, Li, Zhi, Huang, George Q.·2020·Robotics and Computer-Integrated Manufacturing

Abstract

Abstract Product lifecycle management (PLM) aims to seamlessly manage all products and information and knowledge generated throughout the product lifecycle for achieving business competitiveness. Conventionally, PLM is implemented based on standalone and centralized systems provided by software vendors. The information of PLM is hardly to be integrated and shared among the cooperating parties. It is difficult to meet the requirements of the openness, interoperability and decentralization of the Industry 4.0 era. To address these challenges, this paper proposed an industrial blockchain-based PLM framework to facilitate the data exchange and service sharing in the product lifecycle. Firstly, we proposed the concept of industrial blockchain as the use of blockchain technology in the industry with the integration of IoT, M2M, and efficient consensus algorithms. It provided an open but secured information storage and exchange platform for the multiple stakeholders to achieve the openness, interoperability and decentralization in era of industry 4.0. Secondly, we proposed and developed customized blockchain information service to fulfill the connection between a single node with the blockchain network. As a middleware, it can not only process the multi-source and heterogeneous data from varied stages in the product lifecycle, but also broadcast the processed data to the blockchain network. Moreover, smart contract is used to automate the alert services in the product lifecycles. Finally, we illustrated the blockchain-based application between the cooperating partners in four emerging product lifecycle stages, including co-design and co-creation, quick and accurate tracking and tracing, proactive maintenance, and regulated recycling. A simulation experiment demonstrated the effectiveness and efficiency of the proposed framework. The results showed that the proposed framework is scalable and efficient, and hence it is feasible to be adopted in industry. With the successful development of the proposed platform, it is promising to provide an effective PLM for improving interoperability and cooperation between stakeholders in the entire product lifecycle.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.rcim.2019.101897

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 5 references

Cited by

See all 215

Metadata

Authors
Liu, X. L., Wang, W. M., Guo, H., Barenji, A. V., Li, Z., & Huang, G. Q.
Venue
Robotics and Computer-Integrated Manufacturing
Publisher
Elsevier BV
Published
2020-06
Volume
63
Pages
101897
ISSN
0736-5845 (ISSN-L)
OpenAlex
W2989846875
Cited by
215
References
5
FWCI
34.68
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Industrial blockchain based framework for product lifecycle management in industry 4.0. https://app.cochat.ai/papers/10.1016/j.rcim.2019.101897
The paper
Liu, X. L., Wang, W. M., Guo, H., Barenji, A. V., Li, Z., & Huang, G. Q. (2020). Industrial blockchain based framework for product lifecycle management in industry 4.0. Robotics and Computer-Integrated Manufacturing. https://doi.org/10.1016/j.rcim.2019.101897

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.