A Hybrid Energy-Saving Scheduling Method Integrating Machine Tool Intermittent State Control for Workshops

Hong Cheng, Haixiao Liu, Shuo Zhu (), Zhigang Jiang and Hua Zhang
Additional contact information
Hong Cheng: Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China
Haixiao Liu: Ordnance NCO Academy, Army Engineering University of PLA, Wuhan 430075, China
Shuo Zhu: Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China
Zhigang Jiang: Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
Hua Zhang: Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China

Sustainability, 2025, vol. 17, issue 13, 1-27

Abstract: Production scheduling and machine tool intermittent state control separately influence a workshop’s machining and intermittent energy consumption. Effective scheduling decisions and intermittent state control are crucial for optimizing the overall energy consumption in the workshop. However, the scheduling scheme determines the machine tool intermittent durations, which imposes strong constraints on the decision-making process for intermittent state control. This makes it difficult for intermittent state control to be used in providing feedback and optimizing scheduling decisions, significantly limiting the overall energy-saving potential of the workshop. To this end, a workshop energy-saving scheduling method is proposed integrating machine tool intermittent state control. Firstly, the variation characteristics of workshop machining energy consumption, machine tool intermittent durations, and intermittent energy consumption are analyzed, and an energy-saving optimization strategy is designed. Secondly, by incorporating variables such as intermittent durations, intermittent energy consumption, and variable operation start time, a multi-objective integrated optimization model is established. Thirdly, the energy-saving optimization strategy is integrated into chromosome encoding, and multiple crossover and mutation genetic operator strategies, along with a low-level selection strategy, are introduced to improve the NSGA-II algorithm. Finally, the effectiveness of the proposed method is verified through a machining case. Results show that the generated Gantt chart reflects both production scheduling and intermittent state control decision outcomes, resulting in a 1.51% reduction in makespan, and 3.90% reduction in total energy consumption.

Keywords: energy-saving scheduling; intermittent state control of machine tools; integrated optimization; workshop; improved NSGA-II algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/13/6207/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/13/6207/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:13:p:6207-:d:1696068

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().