Fuzzy Petri Net Based Intelligent Machine Operation of Energy Efficient Manufacturing System

Fei, Zicheng; Li, Shiqi; Chang, Qing; Wang, Junfeng; Huang, Yaqin

doi:10.1109/coase.2018.8560366

Cited by 7 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Zhiyang Jia et al [161,162] applied the buffer-based policy to switch on/off machines in Bernoulli serial production line. A fuzzy Petri net was used to reduce the idle period by switching off/on the machines [163]. The state commutation is defined by a fuzzy controller evaluating the real-time buffer occupancy and machine status.…”

Section: Buffer-based Policiesmentioning

confidence: 99%

A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

Renna

Materi

2021

Applied Sciences

View full text Add to dashboard Cite

Climate change mitigation, the goal of reducing CO2 emissions, more stringent regulations and the increment in energy costs have pushed researchers to study energy efficiency and renewable energy sources. Manufacturing systems are large energy consumers and are thus responsible for huge greenhouse gas emissions; for these reasons, many studies have focused on this topic recently. This review aims to summarize the most important papers on energy efficiency and renewable energy sources in manufacturing systems published in the last fifteen years. The works are grouped together, considering the system typology, i.e., manufacturing system subclasses (single machine, flow shop, job shop, etc.) or the assembly line, the developed energy-saving policies and the implementation of the renewable energy sources in the studied contexts. A description of the main approaches used in the analyzed papers was discussed. The conclusion reports the main findings of the review and suggests future directions for the researchers in the integration of renewable energy in the manufacturing systems consumption models.

show abstract

Section: Buffer-based Policiesmentioning

confidence: 99%

A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

Renna

Materi

2021

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…The main applications of these approaches have been oriented to model flow lines with a serial movement of jobs among workstations, job shops with more flexibility, assembly lines, among others, which serve as a foundation for design, scheduling, and control. Some applications and deeper explanations about these modeling approaches can be found in [21,22,23]. Despite the great application of both MC and PN in the manufacturing systems, they have been focused on modeling the production states of the machine rather than modeling the energy consumption behavior of such systems.…”

Section: Model Identificationmentioning

confidence: 99%

An optimization-based control strategy for energy efficiency of discrete manufacturing systems

et al. 2019

View full text Add to dashboard Cite

In order to reduce the global energy consumption and avoid highest power peaks during operation of manufacturing systems, an optimization-based controller for selective switching on/off of peripheral devices in a test bench that emulates the energy consumption of a periodic system is proposed. First, energy consumption models for the test-bench devices are obtained based on data and subspace identification methods. Next, a control strategy is designed based on both optimization and receding horizon approach, considering the energy consumption models, operating constraints, and the real processes performed by peripheral devices. Thus, a control policy based on dynamical models of peripheral devices is proposed to reduce the energy consumption of the manufacturing systems without sacrificing the productivity. Afterward, the proposed strategy is validated in the test bench and comparing to a typical rule-based control scheme commonly used for these manufacturing systems. Based on the obtained results, reductions near 7% could be achieved allowing improvements in energy efficiency via minimization of the energy costs related to nominal power purchased.

show abstract

“…A small amount of literature has been found for real-time energy consumption control of machines based on the PNs method. Fei et al [35] proposed a fuzzy Petri net model for machine ON/OFF reasoning and decisions, where the elements of the fuzzy rules were described as places and transitions. However, the fuzzy rules are static and cannot be adjusted according to real-time production conditions.…”

Section: Related Workmentioning

confidence: 99%

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

et al. 2019

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Fuzzy Petri Net Based Intelligent Machine Operation of Energy Efficient Manufacturing System

Cited by 7 publications

References 12 publications

A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

An optimization-based control strategy for energy efficiency of discrete manufacturing systems

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

Contact Info

Product

Resources

About