Quality analysis of hydraulic systems in function of reliability theory

Efficiency; Hydraulic system performance; Maintenance; Reliability modelling; Simulation; Energy utilization; Hydraulic equipment; Reliability; Reliability analysis; Design stage; Hydraulic system; Statistical modeling; System efficiency; Reliability theory

Abstract :

[en] Through design of a hydraulic systems various methods can be used for increasing system efficiency. Increasing efficiency while at the same time maintaining reliability and energy consumption is far from an easy task. In this article author have used mathematical and empirical evidence while trying to accomplish aforementioned. Design of hydraulic system is based on reliability theory and results are compared with the data collected from empirical sources and articles from previous research in the field. Based on simulation it is possible to increase efficiency of a hydraulic system either at design stage or during exploitation. Results from statistical modeling and simulation show that it is possible to improve system efficiency and therefore achieve higher overall system performance.

Disciplines :

Mechanical engineering

Author, co-author :

OROSNJAK, Marko ; University of Novi Sad, Faculty of Technical Sciences, Trg Dositeja Obradovica 6, Serbia

Jocanović, M.

Karanović, V.

External co-authors :

yes

Language :

English

Title :

Quality analysis of hydraulic systems in function of reliability theory

Publication date :

2016

Event name :

27TH DAAAM INTERNATIONAL SYMPOSIUM ON INTELLIGENT MANUFACTURING AND AUTOMATION

Event organizer :

DAAAM International

Event place :

Mostar, Bosnia & Herzegovina

Event date :

From 26 to 29 October 2016

Event number :

Audience :

International

Main work title :

Proceedings of the 27th International DAAAM Symposium ''Intelligent Manufacturing & Automation''

Editor :

Katalinic B.

TU Wien, IFLT-IMS

Publisher :

Danube Adria Association for Automation and Manufacturing, DAAAM

Edition :

ISBN/EAN :

978-3-902734-08-2

Collection ISSN :

1726-9679

Peer reviewed :

Peer reviewed

Focus Area :

Computational Sciences

Additional URL :

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010817727&doi=10.2507%2f27th.daaam.proceedings.084&partnerID=40&md5=0df9b1f08a34cf71cdda3248e6c3b0cd

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since 20 January 2025

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