ArticleScientific reports2025
LCD-AHP-TRIZ methodology enhances low-carbon principles in smart product design.
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.
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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.
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Who cites it
3 citing papers in PubMed.
- A need-driven design research of modular functional armchairs for young adults.Scientific reports · 2026Article
- Design of a user-centered intelligent shoe cabinet for smart home hygiene using Kano-AHP-TRIZ.Scientific reports · 2026Article
- Effectiveness of the Kano-AHP-TRIZ-TOPSIS integrated model for analyzing the healthcare emergency facility needs of the older adults.Frontiers in public health · 2026Article
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Authors and funding
2 authors.
Funding
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.
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Registered trials
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