Industry 4.0 technologies in the manufacturing sector: Are we sure they are all relevant for environmental performance?

被引:131
作者
Chiarini, Andrea [1 ]
机构
[1] Univ Verona, Dept Business Adm, Via Cantarane 24, I-37129 Verona, Italy
关键词
cybertechnology; environmental performance; Industry; 4; 0; smart technology;
D O I
10.1002/bse.2797
中图分类号
F [经济];
学科分类号
02 ;
摘要
This research contributes to the debate about the relevance of Industry 4.0 technologies in improving environmental performance in the manufacturing industry. We employed a qualitative-quantitative approach in which 19 Italian operations managers were interviewed and 260 managers responded to an online questionnaire. The effects of various technologies were ranked using ordinal regression. Comments and suggestions gave context to the quantitative results. Sensors, radio-frequency identification, artificial intelligence and analytics were found to be most relevant in improving environmental performance, whereas simulation software contributed moderately. Additive manufacturing, cobots, robots, automated mobile robots and automated guided vehicles had a negative effect, augmented reality had no effect and other technologies indirectly affected environmental performance. We also found a lack of knowledge and application as well as scepticism about technologies such as artificial intelligence and augmented reality. Finally, there was concern about the disposal of electrical and electronic waste produced by these technologies.
引用
收藏
页码:3194 / 3207
页数:14
相关论文
共 72 条
[61]   Smart factory in Industry 4.0 [J].
Shi, Zhan ;
Xie, Yongping ;
Xue, Wei ;
Chen, Yong ;
Fu, Liuliu ;
Xu, Xiaobo .
SYSTEMS RESEARCH AND BEHAVIORAL SCIENCE, 2020, 37 (04) :607-617
[62]   Implementing Smart Factory of Industrie 4.0: An Outlook [J].
Wang, Shiyong ;
Wan, Jiafu ;
Li, Di ;
Zhang, Chunhua .
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2016,
[63]  
Shrouf F, 2014, IN C IND ENG ENG MAN, P697, DOI 10.1109/IEEM.2014.7058728
[64]   Energy management based on Internet of Things: practices and framework for adoption in production management [J].
Shrouf, Fadi ;
Miragliotta, Giovanni .
JOURNAL OF CLEANER PRODUCTION, 2015, 100 :235-246
[65]   Opportunities of Sustainable Manufacturing in Industry 4.0 [J].
Stock, T. ;
Seliger, G. .
13TH GLOBAL CONFERENCE ON SUSTAINABLE MANUFACTURING - DECOUPLING GROWTH FROM RESOURCE USE, 2016, 40 :536-541
[66]  
Strand S., 2011, Using statistical regression methods in educational research
[67]   Looking at energy through the lens of Industry 4.0: A systematic literature review of concerns and challenges [J].
Tesch da Silva, Fernanda Schafer ;
da Costa, Cristiano Andre ;
Paredes Crovato, Cesar David ;
Righi, Rodrigo da Rosa .
COMPUTERS & INDUSTRIAL ENGINEERING, 2020, 143
[68]   Energy efficient distributed analytics at the edge of the network for IoT environments [J].
Valerio, Lorenzo ;
Conti, Marco ;
Passarella, Andrea .
PERVASIVE AND MOBILE COMPUTING, 2018, 51 :27-42
[69]   Sustainability Outcomes of Green Processes in Relation to Industry 4.0 in Manufacturing: Systematic Review [J].
Vrchota, Jaroslav ;
Pech, Martin ;
Rolinek, Ladislav ;
Bednar, Jiri .
SUSTAINABILITY, 2020, 12 (15)
[70]   Investigating the effects of Smart Production Systems on sustainability elements [J].
Waibel, M. W. ;
Steenkamp, L. P. ;
Moloko, N. ;
Oosthuizen, G. A. .
14TH GLOBAL CONFERENCE ON SUSTAINABLE MANUFACTURING, GCSM 2016, 2017, 8 :731-737