TY - JOUR
T1 - Industrial internet of things enabled supply-side energy modelling for refined energy management in aluminium extrusions manufacturing
AU - Peng, Chen
AU - Peng, Tao
AU - Liu, Yang
AU - Geissdoerfer, Martin
AU - Evans, Steve
AU - Tang, Renzhong
N1 - Funding Information:
This research is financially supported by the National Natural Science Foundation of China (Grant No. U151248 ) and FlexSUS: Flexibility for Smart Urban Energy Systems (Project No. 91352 ), which has received funding in the framework of the joint programming initiative ERA-Net Smart Energy Systems’ focus initiative Integrated , Regional Energy Systems , with support from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 775970 . The usual disclaimer applies.
Funding Information:
This research is financially supported by the National Natural Science Foundation of China (Grant No. U151248) and FlexSUS: Flexibility for Smart Urban Energy Systems (Project No. 91352), which has received funding in the framework of the joint programming initiative ERA-Net Smart Energy Systems? focus initiative Integrated, Regional Energy Systems, with support from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 775970. The usual disclaimer applies.
Publisher Copyright:
© 2021 The Author(s)
PY - 2021/6/10
Y1 - 2021/6/10
N2 - To improve industrial sustainability performance in manufacturing, energy management and optimisation are key levers. This is particularly true for aluminium extrusions manufacturing —an energy-intensive production system with considerable environmental impacts. Many energy management and optimisation approaches have been studied to relieve such negative impact. However, the effectiveness of these approaches is compromised without the support of refined supply-side energy consumption information. Industrial internet of things provides opportunities to acquire refined energy consumption information in its data-rich environment but also poses a range of difficulties in implementation. The existing sensors cannot directly obtain the energy consumption at the granularity of a specific job. To acquire that refined energy consumption information, a supply-side energy modelling method based on existing industrial internet of things devices for energy-intensive production systems is proposed in this paper. First, the job-specified production event concept is proposed, and the layout of the data acquisition network is designed to obtain the event elements. Second, the mathematical models are developed to calculate the energy consumption of the production event in three process modes. Third, the energy consumption information of multiple manufacturing element dimensions can be derived from the mathematical models, and therefore, the energy consumption information on multiple dimensions is easily scaled. Finally, a case of refined energy cost accounting is studied to demonstrate the feasibility of the proposed models.
AB - To improve industrial sustainability performance in manufacturing, energy management and optimisation are key levers. This is particularly true for aluminium extrusions manufacturing —an energy-intensive production system with considerable environmental impacts. Many energy management and optimisation approaches have been studied to relieve such negative impact. However, the effectiveness of these approaches is compromised without the support of refined supply-side energy consumption information. Industrial internet of things provides opportunities to acquire refined energy consumption information in its data-rich environment but also poses a range of difficulties in implementation. The existing sensors cannot directly obtain the energy consumption at the granularity of a specific job. To acquire that refined energy consumption information, a supply-side energy modelling method based on existing industrial internet of things devices for energy-intensive production systems is proposed in this paper. First, the job-specified production event concept is proposed, and the layout of the data acquisition network is designed to obtain the event elements. Second, the mathematical models are developed to calculate the energy consumption of the production event in three process modes. Third, the energy consumption information of multiple manufacturing element dimensions can be derived from the mathematical models, and therefore, the energy consumption information on multiple dimensions is easily scaled. Finally, a case of refined energy cost accounting is studied to demonstrate the feasibility of the proposed models.
KW - Aluminium extrusions manufacturing
KW - Industrial internet of things
KW - Mixed manufacturing system
KW - Refined energy management
KW - Supply-side energy modelling
UR - http://www.scopus.com/inward/record.url?scp=85103962889&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2021.126882
DO - 10.1016/j.jclepro.2021.126882
M3 - Article
AN - SCOPUS:85103962889
SN - 0959-6526
VL - 301
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 126882
ER -