Evidence map›Paper›PMID 40074862›Full record

ArticleScientific reports2025

LCD-AHP-TRIZ methodology enhances low-carbon principles in smart product design.

Hui Zhen Xu, Jun Chen

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

2 authors.

Hui Zhen XuFair Friend Institute of Intelligent Manufacturing, Hangzhou Vocational& Technical College, Hangzhou, Zhejiang, P. R. China. 308872895@qq.com.
Jun ChenResearch and Development Design Department, Hang Zhou Great Star Industrial Co., Ltd, Hangzhou, Zhejiang, P. R. China.

Funding

2023 Zhejiang Provincial Department of Education Visiting Engineer School-Enterprise Cooperation Project for Higher Education Institution FG2023042
6 · The paper itself

Abstract

With the rapid development of the Internet of Things (IoT) and Artificial Intelligence (AI) technologies, their manufacturing processes have led to an increase in greenhouse gas (GHG) emissions and a significant increase in electronic waste, which adversely affects the global environment. Consequently, green and low-carbon transformation of smart products is imperative. To address the limitations of combining low-carbon principles with complex smart product design, this study proposes an innovative "LCD-AHP-TRIZ" methodology that integrates the full life cycle design (LCD), analytic hierarchy process (AHP), and theory of inventive problem solving (TRIZ) to systematically resolve low-carbon smart conflicts in product design and propose solutions. The method utilizes LCD to construct a low-carbon demand table for the life cycle of smart products, AHP to quantitatively assess the importance of indicators, and TRIZ theory to resolve conflicts, thereby successfully integrating low-carbon demand into smart product design. The applicability and effectiveness of this method were verified using a smart dehumidifier as a case study. The results demonstrate that the method can systematically identify low-carbon design requirements, solve innovation problems, and provide scientific strategies for sustainable development of smart products.

Indexed as

Green low carbon transitionLCD-AHP-TRIZ integrated approachLow carbon designSmart products

Identifiers

PMID40074862
PMCPMC11903995

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.