Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/115661
Title: Optimized hierarchical and network approach to discover sustainable practices for micro-machining technologies
Authors: Yan, EH 
Chen, L 
Guo, F 
Chan, YK 
Zhou, H 
To, S 
Yip, WS 
Issue Date: Sep-2025
Source: Journal of environmental management, Sept 2025, v. 391, 126479
Abstract: Implementing sustainable practices in micro-machining technologies presents complex challenges that require a thorough understanding of field-specific sustainability information and environmental impacts. Currently, there is a lack of systematically developed methodologies for sustainable micro-machining. This study presents an enhanced approach that integrates text mining and hierarchical thematic network analysis to investigate sustainable practices in micro-machining. By analyzing a comprehensive range of scientific literature from recent decades, the study identifies key themes organized into a four-level hierarchical structure for sustainable micro-machining practices, categorized into three principal areas: “Feature,” “Methodology,” and “Target,” providing detailed insights into sustainable practices. Additionally, network theory is applied to construct a thematic network for each theme, evaluating critical metrics such as in-degree, out-degree, betweenness, and closeness, with a detailed interpretation of the theme content for sustainable practices. The proposed approach identifies essential sustainable practices in micro-machining and highlights their significance in advancing sustainability, offering valuable insights for developing effective micro-machining strategies.
Graphical abstract: [Figure not available: see fulltext.]
Keywords: Hierarchical network analysis
Manufacturing practices
Sustainable micro-machining
Text mining
Publisher: Elsevier BV
Journal: Journal of environmental management 
ISSN: 0301-4797
EISSN: 1095-8630
DOI: 10.1016/j.jenvman.2025.126479
Appears in Collections:Journal/Magazine Article

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Embargo End Date 2027-09-30
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