Applying the Fuzzy Inference Model in Maintenance Centered to Safety: Case Study – Bucket Wheel Excavator

Applying the Fuzzy Inference Model in Maintenance Centered to Safety: Case Study – Bucket Wheel Excavator

Predrag D. Jovančić (Faculty of Mining and Geology, University of Belgrade, Serbia), Miloš Tanasijević (Faculty of Mining and Geology, University of Belgrade, Serbia), Vladimir Milisavljević (Faculty of Mining and Geology, University of Belgrade, Serbia), Aleksandar Cvjetić (Faculty of Mining and Geology, University of Belgrade, Serbia), Dejan Ivezić (Faculty of Mining and Geology, University of Belgrade, Serbia), and Uglješa Srbislav Bugarić (Faculty of Mechanical Engineering, University of Belgrade, Serbia)
Copyright: © 2020 |Pages: 24
DOI: 10.4018/978-1-7998-3904-0.ch009
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Abstract

The main idea of this chapter is to promote maintenance centered to safety, in accordance to adaptive fuzzy inference model, which has online adjustment to working conditions. Input data for this model are quality of service indicators of analyzed engineering system: reliability, maintainability, failure consequence, and severity and detectability. Indicators in final form are obtained with permanent monitoring of the engineering system and statistical processing. Level of safety is established by composition and ranking of indicators according to fuzzy inference engine. The problem of monitoring and processing of indicators comprising safety is solved by using the features that Industry4.0 provides. Maintenance centered to safety is important for complex, multi-hierarchy engineering systems. Sudden failures on such systems could have significant financial and environmental effect. Developed model will be tested in the final part of the chapter, in the case study of bucket wheel excavator.
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Concepts And Indictors In Maintenance Engineering

This part of the article provides an analysis of indicators and concepts used for description of maintenance engineering and quality of service, as well as life cycles of engineering systems. Indicators are of partial character, while the concepts are overall, i.e. of synthesis origin. Indicators are defined in detail, while the exact structure of concepts is mainly lacking.

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