Search of Optimum Conditions of Plating Using a Fuzzy Rule-Based Knowledge Model

Solovjev, D. S.; Арзамасцев, А. А.; Solovjeva, I. A.; Litovka, Yuri V.; Львов, А. А.; Melnikova, Nina

doi:10.1007/978-3-030-12072-6_46

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…Shahbazova 142 established a fuzzy knowledge base in the education domain through two types of fuzzy rules in the educational environment. Solovjev et al 138 used fuzzy rules to model the knowledge and experience of decision-makers to solve the problem of uneven thickness distribution during the plating process. Bäuml et al 139 introduced a prototypical representation for the planning of a kanban loop based on a modeling language and rule-based representation method suitable for the logistics planning process.…”

Section: Rule-based Methodsmentioning

confidence: 99%

Knowledge modeling: A survey of processes and techniques

Yun

Zhang

et al. 2021

Int J Intell Syst

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Section: Rule-based Methodsmentioning

confidence: 99%

Knowledge modeling: A survey of processes and techniques

Yun

Zhang

et al. 2021

Int J Intell Syst

View full text Add to dashboard Cite

show abstract

“…Therefore, the search for current control in real time with the presence of stochastic influences using these models is impossible. The use of fuzzy control to correct the current value is the way out of this situation [8,9]. The defuzzification method used is one of the key points that affect the fuzzy control quality.…”

Section: Introductionmentioning

confidence: 99%

Improving the Electroplating Coating Uniformity Based on Fuzzy Control of the Setting Value Using the Combined Defuzzification Method with the Presence of Stochastic Influences

Solovjev

2022

SSP

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The article describes a method to improve the uniformity of electroplating using fuzzy logic. This method provides for the replacement of the non-stationary model of the process dynamics in distributed coordinates with the quasi-stationary model of the process dynamics in lumped coordinates. The production knowledge model with "IF-THEN" rules is developed for the stochastic influences taken into account. The dynamic choice of the defuzzification method is justified by solving the problem of minimizing the absolute deviation of the coating thickness average value obtained from the non-stationary model from the predicted value according to the quasi-stationary model at const values of stochastic influences. As an example, fuzzy control of the current for nickel coating is considered, taking into account the stochastic influence of the electroplating time, detail area, temperature and acidity of the electrolyte. The experimental results prove the effectiveness of the combined defuzzification method in comparison with their independent use in the control process.

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Search of Optimum Conditions of Plating Using a Fuzzy Rule-Based Knowledge Model

Cited by 2 publications

References 6 publications

Knowledge modeling: A survey of processes and techniques

Knowledge modeling: A survey of processes and techniques

Improving the Electroplating Coating Uniformity Based on Fuzzy Control of the Setting Value Using the Combined Defuzzification Method with the Presence of Stochastic Influences

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