Adapting Petri Nets to DES: Stochastic Modelling of Manufacturing Systems

Simon, E.; Oyekan, John; Hutabarat, Windo; Tiwari, Ashutosh; Turner, Christopher

doi:10.2507/ijsimm17(1)403

Cited by 10 publications

(5 citation statements)

References 28 publications

(37 reference statements)

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“…The credit degree value for commodity distribution The distribution period for commodity (q 8 1 ) w(p 8 ) 1 0.02 The distribution credit value for commodity (q 8 2 ) w(p 8 ) 2 0.05 p 9 The credit degree value for after-sales service acceptance (q 9 ) w(p 9 ) 0.01 p 10 The credit degree value for after-sales service (q 10 ) w(p 10 ) 0.02 p 11 The credit degree value for accepting to return and repair commodity (q 11 ) w(p 11 ) 0.02 p 12 The credit degree value for returning and repairing commodity (q 12 ) w(p 12 ) 0.02 p 13 The credit degree value for the durability and constancy of commodity using (q 13 ) w(p 13 ) 0.05 Table 4 The importance (v(p i ) j ) and credit value (…”

Section: Figure 5 B2c Transaction Process' Cwpsn Modelmentioning

confidence: 99%

“…Such as Meng and Yan [10] with the help of knowledgeable manufacturing systems' knowledge base, handling and training multi attribute fuzzy Petri net attribute, and regularization processing the irregular model, constructing the subsequent products' multi attribute fuzzy Petri net model on the basis of the original products' multi attribute fuzzy Petri net model. Simon, Oyekan, Hutabarat, et al [11] constructed the Petri net model for the manufacturing systems.…”

Section: Introductionmentioning

confidence: 99%

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Network Supplier Credit Management: Models Based on Petri Net

Zhu

2019

Teh. vjesn.

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In current credit evaluation methods, the credit condition of the network supplier and the credit degree of each index cannot be described well, and the credit evaluation data only source of the transaction platform have much limitation. This research proposes the method of calculating the importance and the value of the credit evaluation indexes, and proposes to put credit evaluation into big data environment. This research uses the transaction process of B2C as the case, and constructs multiple attribute weighted Petri net credit index subnet (CWPSN) for realizing the credit evaluation of the network supplier, and for presenting the correlations among the evaluation results of the credit evaluation indexes, and for presenting the importance of the indexes and the credit degree of each index, and describes the cost optimization process with credit cost optimization investment process Petri net (CCOIPPN). By the case to verify the credit evaluation method based on Petri net and the cost optimization method based on Petri net. The researches have provided methods for clearly and concretely describing the process of credit evaluation and cost optimization of network supplier, and have guidance significance for similar other researches.

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Section: Figure 5 B2c Transaction Process' Cwpsn Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Network Supplier Credit Management: Models Based on Petri Net

Zhu

2019

Teh. vjesn.

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“…However, Petri net calculations are inherently complex, and Petri nets lack the software capability to demonstrate the potential of DEDS. Hence, some scholars combine the Petri net with other simulation software, such as Witness (Simon et al, 2018), Flexsim (Wang and Chen, 2016), to simulate DEDS to obtain more flexible and effective solutions. AnyLogic simulation software was developed by XJ Technologies with the Java platform.…”

Section: Introductionmentioning

confidence: 99%

Simulation and optimization of mining-separating-backfilling integrated coal mine production logistics system

Wang

Long

Meng

2022

Energy Exploration & Exploitation

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As a new collaborative mining technology, the integration of mining-separating-backfilling (IMSB) enables the coal industry to realize safe, efficient, and green mining of coal resources at the expense of making the underground coal mine production more complex. In coal mining, the primary problem is to eliminate the production logistics system bottleneck to increase coal output. The key to synergetic mining is to realize that the mining capacity of the fully mechanized face should match the underground raw coal separating and gangue backfilling capacities. Considering a coal mine with IMSB in Henan Province, AnyLogic simulation software was used to simulate and optimize the production logistics system based on a generalized stochastic Petri net (GSPN). The main simulation results show that: (1) the raw coal separating capacity of this deep mine matches its mining capacity, and the gangue backfilling capacity can almost meet the demand for backfilling after raw coal mining; (2) belt conveyors 1 and 6 are the transportation bottlenecks of increasing production in the mine, and the lifting capacity of the main shaft is insufficient; (3) after optimization, the clean coal output of this coal mine increased by 3087 t monthly. This research promotes synergetic mining in the coal industry and can serve as a reference for the optimization of similar coal mine production logistics systems.

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“…To meet this need, a new simulation model of OWT maintenance is developed using Petri nets (PNs) in this paper. The reason for choosing to use PNs is that, in contrast to conventional Discrete Event Simulation (DES) models, the PN model provides an intuitive graphical representation of a system of interest and it has been proven to be more flexible and computationally efficient, especially when modelling complex systems [15][16][17]. Recently, the PN has also demonstrated success in simulating the degradation and maintenance of wind turbines [18,19].…”

Section: Introductionmentioning

confidence: 99%

Improving the Strategy of Maintaining Offshore Wind Turbines through Petri Net Modelling

Yan

Dunnett

2021

Applied Sciences

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In order to improve the operation and maintenance (O&M) of offshore wind turbines, a new Petri net (PN)-based offshore wind turbine maintenance model is developed in this paper to simulate the O&M activities in an offshore wind farm. With the aid of the PN model developed, three new potential wind turbine maintenance strategies are studied. They are (1) carrying out periodic maintenance of the wind turbine components at different frequencies according to their specific reliability features; (2) conducting a full inspection of the entire wind turbine system following a major repair; and (3) equipping the wind turbine with a condition monitoring system (CMS) that has powerful fault detection capability. From the research results, it is found that periodic maintenance is essential, but in order to ensure that the turbine is operated economically, this maintenance needs to be carried out at an optimal frequency. Conducting a full inspection of the entire wind turbine system following a major repair enables efficient utilisation of the maintenance resources. If periodic maintenance is performed infrequently, this measure leads to less unexpected shutdowns, lower downtime, and lower maintenance costs. It has been shown that to install the wind turbine with a CMS is helpful to relieve the burden of periodic maintenance. Moreover, the higher the quality of the CMS, the more the downtime and maintenance costs can be reduced. However, the cost of the CMS needs to be considered, as a high cost may make the operation of the offshore wind turbine uneconomical.

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Adapting Petri Nets to DES: Stochastic Modelling of Manufacturing Systems

Cited by 10 publications

References 28 publications

Network Supplier Credit Management: Models Based on Petri Net

Network Supplier Credit Management: Models Based on Petri Net

Simulation and optimization of mining-separating-backfilling integrated coal mine production logistics system

Improving the Strategy of Maintaining Offshore Wind Turbines through Petri Net Modelling

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