.png){kind=icon}
Return
Collaborative status control-based energy-aware scheduling for distributed hybrid machine shop using utilization-efficient intermingled optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.swevo.2025.102197.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Distributed hybrid machine shop (DHMS) generally has more shops and machine tools, which consume significant energy with low efficiency. Therefore, it is crucial to save energy for DHMS. However, as the main energy consumers, certain machine tools incur substantial energy waste for waiting workpieces. It is hopeful to collaboratively switch machine tools in distributed shops among multiple operating states with varying power consumption for enhancing industrial sustainability in the machining sector. Therefore, a collaborative status control-based energy-aware scheduling approach using a utilization-efficient intermingled optimization is proposed for DHMSs in this paper. First, a collaborative status control strategy that categories machine tools into seven statuses is proposed, and an energy-aware scheduling model is developed. Then, a utilization-efficient intermingled optimization method, which is jointly enabled by distributed computing and multi-thread computing strategies with the advantages of different heuristic algorithms, is proposed to maximize the efficiency of decision-making. A case study is conducted to exemplify the effectiveness and the advantages of the proposed approach through verification and comparisons. The outcomes indicate that the proposed approach can generate optimized production schedules for machining sectors with reduced energy consumption and improved production efficiency.
Journal
IF:
8.5
Papers:
2.2K
Citations:
1.0W
Organization
View more organizations
Cited Papers
No cited papers available