TY - JOUR
T1 - Leveraging Industry 4.0 for Sustainable Manufacturing
T2 - A Quantitative Analysis Using FI-RST
AU - Li, Qingwen
AU - Tang, Waifan
AU - Li, Zhaobin
N1 - Publisher Copyright:
© 2024 by the authors.
PY - 2024/10
Y1 - 2024/10
N2 - The Fourth Industrial Revolution, also known as Industry 4.0, which is the intensified digitalization and automation in industry, embraces cyber–physical systems, the Internet of Things (IoT), and artificial intelligence, among others. This study utilizes Fuzzy Integration–Rough Set Theory (FI-RST) analysis to quantify the impacts of the imperative Industry 4.0 technologies for manufacturing firms located in Fujian Province, China, namely, Manufacturing Execution Systems (MES), the Industrial Internet of Things (IIoT), and Additive Manufacturing (AM), on the sustainable development performance of firms. The findings of the study indicate that these technologies greatly improve the effectiveness of the utilization of resources, reduce the costs of operations, and reduce the impact on the environment. In addition, they have a favorable influence on social considerations, such as preserving the well-being of employees and the outcome of training programs. This research work has convincingly provided an underlying strategic adoption of these technologies for sustainability production by raising important insights that could be valuable for industry managers and policymakers, especially those seeking sustainability at the global level.
AB - The Fourth Industrial Revolution, also known as Industry 4.0, which is the intensified digitalization and automation in industry, embraces cyber–physical systems, the Internet of Things (IoT), and artificial intelligence, among others. This study utilizes Fuzzy Integration–Rough Set Theory (FI-RST) analysis to quantify the impacts of the imperative Industry 4.0 technologies for manufacturing firms located in Fujian Province, China, namely, Manufacturing Execution Systems (MES), the Industrial Internet of Things (IIoT), and Additive Manufacturing (AM), on the sustainable development performance of firms. The findings of the study indicate that these technologies greatly improve the effectiveness of the utilization of resources, reduce the costs of operations, and reduce the impact on the environment. In addition, they have a favorable influence on social considerations, such as preserving the well-being of employees and the outcome of training programs. This research work has convincingly provided an underlying strategic adoption of these technologies for sustainability production by raising important insights that could be valuable for industry managers and policymakers, especially those seeking sustainability at the global level.
KW - fuzzy integration-rough set theory
KW - industrial internet of things
KW - industry 4.0
KW - manufacturing execution systems
KW - sustainable manufacturing
UR - http://www.scopus.com/inward/record.url?scp=85207336448&partnerID=8YFLogxK
U2 - 10.3390/app14209545
DO - 10.3390/app14209545
M3 - Article
AN - SCOPUS:85207336448
VL - 14
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
IS - 20
M1 - 9545
ER -