{"title":"An energy-consumption model for establishing an integrated energy-consumption process in a machining system","authors":"Wenbin Gu, Zhuohao Li, Zeyu Chen, Yuxin Li","doi":"10.1080/13873954.2020.1833045","DOIUrl":null,"url":null,"abstract":"ABSTRACT Manufacturing industry accounts for a significant part of world’s energy consumption and environmental pollutions. Machining process is a major process of manufacturing industries, plays an important role in energy saving and emission reduction. This paper established an energy-consumption model for machining processes considering the full states of machining processes. Firstly, machining processes are decomposed into activities and activity transitions according to the different characteristics of energy demand. Secondly, based on the decomposition of activities and activity transitions, the energy-consumption models of activities and activity transitions are established, respectively. Thirdly, combining with the established energy-consumption models of activities and activity transitions, this paper proposes an energy-consumption model for the entire machining processes that systematically reflects different machining states. Finally, the simulation results show that the proposed model can accurately calculate the energy consumption of machining processes and provide guidance for machine tool energy saving.","PeriodicalId":49871,"journal":{"name":"Mathematical and Computer Modelling of Dynamical Systems","volume":"26 1","pages":"534 - 561"},"PeriodicalIF":1.8000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/13873954.2020.1833045","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical and Computer Modelling of Dynamical Systems","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/13873954.2020.1833045","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 4
Abstract
ABSTRACT Manufacturing industry accounts for a significant part of world’s energy consumption and environmental pollutions. Machining process is a major process of manufacturing industries, plays an important role in energy saving and emission reduction. This paper established an energy-consumption model for machining processes considering the full states of machining processes. Firstly, machining processes are decomposed into activities and activity transitions according to the different characteristics of energy demand. Secondly, based on the decomposition of activities and activity transitions, the energy-consumption models of activities and activity transitions are established, respectively. Thirdly, combining with the established energy-consumption models of activities and activity transitions, this paper proposes an energy-consumption model for the entire machining processes that systematically reflects different machining states. Finally, the simulation results show that the proposed model can accurately calculate the energy consumption of machining processes and provide guidance for machine tool energy saving.
期刊介绍:
Mathematical and Computer Modelling of Dynamical Systems (MCMDS) publishes high quality international research that presents new ideas and approaches in the derivation, simplification, and validation of models and sub-models of relevance to complex (real-world) dynamical systems.
The journal brings together engineers and scientists working in different areas of application and/or theory where researchers can learn about recent developments across engineering, environmental systems, and biotechnology amongst other fields. As MCMDS covers a wide range of application areas, papers aim to be accessible to readers who are not necessarily experts in the specific area of application.
MCMDS welcomes original articles on a range of topics including:
-methods of modelling and simulation-
automation of modelling-
qualitative and modular modelling-
data-based and learning-based modelling-
uncertainties and the effects of modelling errors on system performance-
application of modelling to complex real-world systems.