Evidence map›Paper›PMID 40127065›Full record

ArticlePloS one2025

Data-driven demand analysis and design reliability study of critical components of complex products.

Zhan Meng, Zhenggang Wang, Dapeng Gao, Wei Lu

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Zhan MengHenan Academy of Sciences, Zhengzhou, Henan, China.ORCID https://orcid.org/0000-0002-2449-141X
Zhenggang WangSchool of Management, Zhengzhou University, Zhengzhou, Henan, China.
Dapeng GaoLogistics Management Section, SAIC Motor Passenger Vehicle Company (Zhengzhou Branch), Zhengzhou, Henan, China.
Wei LuThe First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Distinguished from the traditional general framework of product design, under the background of digital intelligence, the complex product design method presents the characteristics of rapid iteration and high degree of integration, and adopts the simulation and modeling technology, advanced production methods, etc. to further improve the quality and reliability of complex product design. Therefore, the demand analysis and design reliability study of critical components of complex products need to consider the sustainability, resources and economy of design, manufacturing and service. In this paper, starting from the product requirement analysis, the Kano-QFD model is used to clarify the requirement identification path of the critical components of complex products and ensure that the quality characteristics of the critical components of complex products are consistent with the customer requirements. The multi-dimensional characteristics of product design parameters, manufacturing process and quality are integrated to construct a design manufacturing analysis (DMA) model, which it's based design reliability analysis method for critical components of complex products. Finally, the method proposed in this article was validated by taking the demand analysis and design reliability of critical components of automotive engines as an example. The study shows that the method proposed in this paper is highly compatible with the practice of complex product design and manufacturing at the early stage, and the method proposed in this paper also can provide product design and quality management reference for the research and development and manufacturing personnel of complex products to meet the changing needs and challenges of complex products.

Identifiers

PMID40127065
PMCPMC11932487

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Registered trials

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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.