Mathematical model and enhanced cooperative co-evolutionary algorithm for scheduling energy-efficient manufacturing cell

2021 ◽  
pp. 129248
Author(s):  
Lixin Cheng ◽  
Qiuhua Tang ◽  
Liping Zhang ◽  
Kai Meng
Keyword(s):  
Mathematical Model ◽  
Evolutionary Algorithm ◽  
Energy Efficient ◽  
Manufacturing Cell ◽  
Efficient Manufacturing ◽  
Energy Efficient Manufacturing

scholarly journals Quantifying adoption rates and energy savings over time for advanced energy-efficient manufacturing technologies

2019 ◽  
Vol 232 ◽  
pp. 925-939 ◽  
Author(s):  
Rebecca Hanes ◽  
Alberta Carpenter ◽  
Matthew Riddle ◽  
Diane J. Graziano ◽  
Joe Cresko
Keyword(s):  
Energy Efficient ◽  
Energy Savings ◽  
Manufacturing Technologies ◽  
Efficient Manufacturing ◽  
Energy Efficient Manufacturing ◽  
Over Time

scholarly journals Integrated Material and Energy Flow Analysis towards Energy Efficient Manufacturing

Procedia CIRP ◽  
2014 ◽  
Vol 15 ◽  
pp. 117-122 ◽  
Author(s):  
Pouya Ghadimi ◽  
Wen Li ◽  
Sami Kara ◽  
Christoph Herrmann
Keyword(s):  
Energy Efficient ◽  
Energy Flow ◽  
Flow Analysis ◽  
Energy Flow Analysis ◽  
Efficient Manufacturing ◽  
Energy Efficient Manufacturing

scholarly journals Use of arc plasma in metal casting as a new approach towards energy efficient manufacturing

2019 ◽  
Vol 47 (1) ◽  
pp. 36-41
Author(s):  
Stefano Cucchetti ◽  
Emanuele Savini ◽  
Giuseppe Lucisano
Keyword(s):  
Energy Efficient ◽  
Metal Casting ◽  
Arc Plasma ◽  
New Approach ◽  
Efficient Manufacturing ◽  
Energy Efficient Manufacturing

scholarly journals Event-Driven Online Machine State Decision for Energy-Efficient Manufacturing System Based on Digital Twin Using Max-Plus Algebra

2019 ◽  
Vol 11 (18) ◽  
pp. 5036 ◽  
Author(s):  
Junfeng Wang ◽  
Yaqin Huang ◽  
Qing Chang ◽  
Shiqi Li
Keyword(s):  
Energy Saving ◽  
Energy Efficient ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Production Data ◽  
Physical Systems ◽  
Digital Twin ◽  
Saving Decisions ◽  
Efficient Manufacturing ◽  
Energy Efficient Manufacturing

Energy-efficient manufacturing is an important aspect of sustainable development in current society. The rapid development of sensing technologies can collect real-time production data from shop floors, which provides more opportunities for making energy saving decisions about manufacturing systems. In this paper, a digital twin-based bidirectional operation framework is proposed to realize energy-efficient manufacturing systems. The data view, model view, and service view of a digital twin manufacturing system are formulated to describe the physical systems in virtual space, to perform simulation analysis, to make decisions, and to control the physical systems for various energy-saving purposes. For online energy-saving decisions about machines in serial manufacturing systems, an event-driven estimation method of an energy-saving window based on Max-plus Algebra is presented to put the target machine to sleep, considering real-time production data of a system segment. A practical, simplified automotive production line is used to illustrate the effectiveness of the proposed method by simulation experiments. Our method has no restriction on machine failure mode and predefined parameters for energy-saving decision of machines. The proposed approach has potential use in synchronous and asynchronous manufacturing systems.

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