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Ontology based social life cycle assessment for product development

Authors :
Zhen Shang
Meidan Wang
Daizhong Su
Qinhui Liu
Shifan Zhu
Source :
Advances in Mechanical Engineering, Vol 10 (2018)
Publication Year :
2018
Publisher :
SAGE Publishing, 2018.

Abstract

Social life cycle assessment is an important method to assess products’ social impacts throughout their life cycles. There are already some indicators and software to assist conducting social life cycle assessment. However, it is hard for users to share or reuse assessment results because of different application data structures. To resolve this problem, a knowledge-based social life cycle assessment–aided design method is developed in this research. With this method, all elements in the social life cycle assessment process are analyzed and represented as classes, their relationships are described as object properties, and the data structure is represented as data properties to construct an ontology system for social life cycle assessment. Based on the ontology, a social life cycle assessment–aided product development web is developed. According to the data property structure, a bidirectional mapping between database and ontology is realized using JENA and ontology-based data access, which enables the result data to be automatically inputted into ontology individuals. Thus, the result data can be accumulated, shared, and reused among users. A case study with a floor product as well as a user test is carried out to prove the feasibility and usability of the web. The ontology-based social life cycle assessment–aided design method provides users with a new high-efficiency approach, setting the foundation for the intellectualization of life cycle assessment.

Details

Language :
English
ISSN :
16878140
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Advances in Mechanical Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.200d45fbdacf44ca94203e8f24b4809c
Document Type :
article
Full Text :
https://doi.org/10.1177/1687814018812277