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

Објеката

Тип
Поглавље у монографији
Верзија рада
објављена
Језик
енглески
Креатор
Predrag Jovančić, Miloš Tanasijević, Vladimir Milisavljević, Aleksandar Cvjetić, Dejan Ivezić, Uglješa Bugarić
Извор
Applications and Challenges of Maintenance and Safety Engineering in Industry 4.0
Уредник
Alberto Martinetti, Micaela Demichela, Sarbjeet Singh
Издавач
Pennsylvania : IGI Global
Датум издавања
2020
Опис
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.
почетак странице
142
крај странице
165
doi
10.4018/978-1-7998-3904-0
isbn
978-1-7998-3904-0
Шира категорија рада
M10
Ужа категорија рада
М14
Права
Затворени приступ
Лиценца
Creative Commons – Attribution 4.0 International
Формат
.pdf

Predrag Jovančić, Miloš Tanasijević, Vladimir Milisavljević, Aleksandar Cvjetić, Dejan Ivezić, Uglješa Bugarić. "Applying the Fuzzy Inference Model in Maintenance Centered to Safety: Case Study – Bucket Wheel Excavator" in Applications and Challenges of Maintenance and Safety Engineering in Industry 4.0 , Pennsylvania : IGI Global (2020). https://doi.org/10.4018/978-1-7998-3904-0

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