A comparative study and measuring performance of manufacturing systems with Mamdani fuzzy inference system

Pourjavad, Ehsan; Mayorga, René V.

doi:10.1007/s10845-017-1307-5

Cited by 87 publications

(44 citation statements)

References 47 publications

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“…FIS is an applied tool in various areas, such as risk management (Ilbahar et al, 2018;Chung et al, 2019), supplier selection (Amindoust et al, 2012;, manufacturing systems evaluation (Pourjavad and Mayorga, 2019), healthcare supply chain (Nazari et al, 2018), and so forth.…”

Section: Fuzzy Inference Systemmentioning

confidence: 99%

A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)

Govindan

Mina

Alavi

2020

Transportation Research Part E: Logistics and Transportation Re

515

351

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The disasters caused by epidemic outbreaks is different from other disasters due to two specific features: their long-term disruption and their increasing propagation. Not controlling such disasters brings about severe disruptions in the supply chains and communities and, thereby, irreparable losses will come into play. Coronavirus disease 2019 (COVID-19) is one of these disasters that has caused severe disruptions across the world and in many supply chains, particularly in the healthcare supply chain. Therefore, this paper, for the first time, develops a practical decision support system based on physicians' knowledge and fuzzy inference system (FIS) in order to help with the demand management in the healthcare supply chain, to reduce stress in the community, to break down the COVID-19 propagation chain, and, generally, to mitigate the epidemic outbreaks for healthcare supply chain disruptions. This approach first divides community residents into four groups based on the risk level of their immune system (namely, very sensitive, sensitive, slightly sensitive, and normal) and by two indicators of age and pre-existing diseases (such as diabetes, heart problems, or high blood pressure). Then, these individuals are classified and are required to observe the regulations of their class. Finally, the efficiency of the proposed approach was measured in the real world using the information from four users and the results showed the effectiveness and accuracy of the proposed approach.

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Section: Fuzzy Inference Systemmentioning

confidence: 99%

A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)

Govindan

Mina

Alavi

2020

Transportation Research Part E: Logistics and Transportation Re

515

351

View full text Add to dashboard Cite

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“…30, and the value of the correlation function, Eq. (31). The values of the measures were determined taking into consideration the values calculated using the real collected data and the values calculated by the models for testing data set.…”

Section: The Analysis Of the Model Accuracy And The Results Of Simulamentioning

confidence: 99%

“…The inputs-output models are constructed employing the fuzzy sets theory. They can use inference of Mamdani type [31], of Takagi-Sugeno-Kang type [32] or be of relational type [33]. In order to solve the issue under consideration the fuzzy models with use of the Mamdani type inference are chosen because thanks to their generalized structure the accurate knowledge about the structure of the modeled object is not required [34].…”

Section: Structure and The Operation Of The Model Of The Operational mentioning

confidence: 99%

Fuzzy Model of the Operational Potential Consumption Process of a Complex Technical System

Pająk

2020

FU Mech Eng

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During the operation process of a system its technical state is changed. The changes take place because of the wearing factors impact. The impact depends on the flow and intensity of the operation process what is characterized by the time histories of the working parameters. Simultaneously, the changes of the technical state are correlated with the changes of the amount of the operational potential included in a system. In order to avoid the inability state occurrence the amount of this potential should be higher than the boundary value. The amount of the operational potential included in a system is determined by the values of the cardinal features of it but in the case of the real technical system the values cannot always be measured. Therefore, the amount of the operational potential and the technical state of the system cannot always be determined online. To solve this problem the model of the operational potential consumption process was created and presented in the paper. The model uses artificial intelligence techniques to calculate the change of the operational potential amount by determining the changes of the cardinal features of the system on the basis of the time histories of the working parameters. The verification of the model quality was performed using the pulverized boiler OP-650k-040 operating in the power plant. The description of the conducted research and the results of the verification were presented in the end of the paper proving the adequacy of the model implementation in the case of industrial objects.

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“…"The Fuzzy Inferior Device uses smooth inputs and outputs to add a nonlinear projection from its input space to its output space." Source: (Pourjavad & Mayorga, 2019) Why Why Because Logical Analysis (WWBLA) worksheet is a probing approach that contributes to the discovery of a problem's underlying cause(s). What is the intention of an examination of why-why?…”

Section: Intelligent System (Is)mentioning

confidence: 99%

Improving Production System Performance Using Overall Equipment Effectiveness

Clarence¹,

Daud²

2020

IJIM

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In the competition among organization on the global market, no organization will tolerate losses. Overall Equipment Effectiveness (OEE) overall is a new process in which the efficiency of a system is calculated and complicated manufacturing issues are truly simplified to simple and intuitive knowledge delivery. It thinks about the exceptionally important measures of productivity. An endeavour has been done to measure and analyse existing Overall Equipment Effectiveness (OEE) at company Kirino in hope to reduce unplanned downtime losses on equipment failure and tooling damage to maximize the productivity. The methods used to analyse these various causes were analysis tools and Intelligence Systems. After knowing the causes of various activities that leads to high rates of defects, then recommendations for improvements that could be used by company Kirino were ready to be made using intelligent system as a medium of solution

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A comparative study and measuring performance of manufacturing systems with Mamdani fuzzy inference system

Cited by 87 publications

References 47 publications

A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)

A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)

Fuzzy Model of the Operational Potential Consumption Process of a Complex Technical System

Improving Production System Performance Using Overall Equipment Effectiveness

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