Green scheduling to achieve green manufacturing: Pursuing a research agenda by mapping science

调度(生产过程) 新颖性 可持续发展 温室气体 业务 计算机科学 中国 绿色消费 能源消耗 环境经济学 工程类 运营管理 政治学 经济 生产(经济) 宏观经济学 法学 哲学 电气工程 生物 神学 生态学
作者
Izaskun Álvarez-Meaza,Enara Zarrabeitia Bilbao,Rosa María Río Belver,Gaizka Garechana
出处
期刊:Technology in Society [Elsevier BV]
卷期号:67: 101758-101758 被引量:21
标识
DOI:10.1016/j.techsoc.2021.101758
摘要

The strengthening of measures to reduce greenhouse gas emissions meant that manufacturing scheduling had to acquire a green approach. The need to reduce energy consumption becomes necessary for companies to achieve sustainable development. Therefore, a new challenge for the scientific community was foreseen, researching new algorithms or knowledge hubs to achieve green scheduling. Green scheduling may be considered one of the principles of green manufacturing, aimed at minimizing environmental damage and energy waste. A review of the literature shows that there are no research works that analyze the scientific development carried out in "green scheduling" through methodologies based on bibliometric analysis, thus the need and the novelty of this research. Based on a dataset formed by 420 scientific documents published from 2006 to 2020 a bibliometric and network analysis is carried out to find the scientific trends, the main relationships according to collaborations and intermediaries, and the research hubs that help to establish the research agenda. The results show that "green scheduling" is a growing research area in the scientific community and in recent years the number of new research topics has experienced considerable growth. This research is developed in Asia, Europe and America, but China stands out as the most productive, collaborative, intermediary, influential and active country at present, through its organizations which are mainly universities, such as Huanzhong University of Science and Technology and Tongji University. However, research development related to green scheduling is carried out in a collaborative environment between institutions located in different countries, allowing countries that are not scientific powerhouses to develop research in the area. The network analysis makes it possible to define the research framework through the clustering of the dataset's research keywords, highlighting that the main areas of research focus on the development of new methods through algorithms aimed at improving energy efficiency in production environments, in areas of computational development such as cloud computing, and in transportation. The most cited research papers, considered the main drivers of knowledge, are published in high-quality research journals, and are mainly developments in scheduling algorithms for different work environments with a green approach. Research findings can provide the academic community with relevant information about green scheduling to make appropriate decisions and become a research agenda for future research.

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