Energy Saving Operation of Manufacturing System Based on Dynamic Adaptive Fuzzy Reasoning Petri Net

Junfeng Wang, Zicheng Fei, Qing Chang and Shiqi Li
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Junfeng Wang: Department of Industrial and Manufacturing System Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Zicheng Fei: Department of Industrial and Manufacturing System Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Qing Chang: Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA 22904 USA
Shiqi Li: Department of Industrial and Manufacturing System Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

Energies, 2019, vol. 12, issue 11, 1-17

Abstract: The energy efficient operation of a manufacturing system is important for sustainable development of industry. Apart from the device and process level, energy saving methods at the system level has attracted increasing attention with the rapid growth of the industrial Internet of things technology, which makes it possible to sense and collect real-time data from the production line and provide more opportunities for online control for energy saving purposes. In this paper, a dynamic adaptive fuzzy reasoning Petri net is proposed to decide the machine energy saving state considering the production information of a discrete stochastic manufacturing system. Fuzzy knowledge for energy saving operations of a machine is represented in weighted fuzzy production rules with certain values. The rules describe uncertain, imprecise, and ambiguous knowledge of machine state decisions. This makes an energy saving sleep decision in advance when a machine has the inclination of starvation or blockage, which is based on the real-time production rates and level of connected buffers. A dynamic adaptive fuzzy reasoning Petri net is formally defined to implement the reasoning process of the machine state decision. A manufacturing system case is used to demonstrate the application of our method and the results indicate its effectiveness for energy saving operation purposes.

Keywords: knowledge representation; fuzzy reasoning Petri net; energy efficient operation; manufacturing system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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