ISSN 1507-2711
ISSN online 2956-3860

JOURNAL DOI: dx.doi.org/10.17531/ein

JCR Journal Profile


Członek(Member of): Europejskiej Federacji Narodowych Towarzystw Eksploatacyjnych  - European Federation of National Maintenance Societies  Wydawca(Publisher):Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne (Warszawa) - Polish Maintenance Society (Warsaw)   Patronat Naukowy(Scientific supervision): Polska Akademia Nauk o/Lublin  - Polish Akademy of Sciences Branch in Lublin  Członek(Member of): Europejskiej Federacji Narodowych Towarzystw Eksploatacyjnych  - European Federation of National Maintenance Societies


 We verify submissions originality with the use of iThenticate plagiarism checker


 All accepted articles are published Open Access under the Creative Commons Licence: CC-BY 4.0

Publisher:
Polish Maintenance Society
(Warsaw)

Scientific supervision:
Polish Academy of Sciences Branch in Lublin

Member of:
European Federation
of National Maintenance Societies


Attention!

In accordance with the requirements of citation databases, proper citation of publications appearing in our Quarterly should include the full name of the journal in Polish and English without Polish diacritical marks, i.e. "Eksploatacja i Niezawodnosc – Maintenance and Reliability".


 

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MOST CITED

Update: 2021-07-01

1. COMPUTER-AIDED MAINTENANCE AND RELIABILITY MANAGEMENT SYSTEMS FOR CONVEYOR BELTS
By: Mazurkiewicz, Dariusz

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume: 16   Issue: 3   Pages: 377-382   Published: 2014

Times Cited: 59
2. ON APPROACHES FOR NON-DIRECT DETERMINATION OF SYSTEM DETERIORATION
By: Valis, David; Koucky, Miroslav; Zak, Libor

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume 14, Issue: 1   Pages: 33-41   Published: 2012

Times Cited: 53
3. A NEW FAULT TREE ANALYSIS METHOD: FUZZY DYNAMIC FAULT TREE ANALYSIS
By: Li, Yan-Feng; Huang, Hong-Zhong; Liu, Yu; et al.

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume 14, Issue: 3 Pages: 208-214 Published: 2012

Times Cited: 51
4. INNOVATIVE METHODS OF NEURAL RECONSTRUCTION FOR TOMOGRAPHIC IMAGES IN MAINTENANCE OF TANK INDUSTRIAL REACTORS
By: Rymarczyk, Tomasz; Klosowski, Grzegorz

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume: 21 Issue: 2 Pages: 261-267 Published: 2019

Times Cited: 50
5. APPLICATION OF NEURAL RECONSTRUCTION OF TOMOGRAPHIC IMAGES IN THE PROBLEM OF RELIABILITY OF FLOOD PROTECTION FACILITIES
By: Rymarczyk, Tomasz; Klosowski, Grzegorz

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume: 20 Issue: 3 Pages: 425-434 Published: 2018

Times Cited: 45
6. ASSESSMENT MODEL OF CUTTING TOOL CONDITION FOR REAL-TIME SUPERVISION SYSTEM
By: Kozlowski, Edward; Mazurkiewicz, Dariusz; Zabinski, Tomasz; Prucnal, Slawomir; Sep, Jaroslaw

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume: 21 Issue: 4 Pages: 679-685 Published: 2019

Times Cited: 40
7. PREDICTING THE TOOL LIFE IN THE DRY MACHINING OF DUPLEX STAINLESS STEEL
By: Krolczyk, Grzegorz; Gajek, Maksymilian; Legutko, Stanislaw

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume: 15 Issue: 1 Pages: 62-65 Published: 2013

Times Cited: 39
8. MAINTENANCE DECISION MAKING BASED ON DIFFERENT TYPES OF DATA FUSION
By: Galar, Diego; Gustafson, Anna; Tormos, Bernardo; et al.
EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY 
Volume 14, Issue: 2   Pages: 135-144   Published:2012

Times Cited: 38
9. TESTS OF EXTENDABILITY AND STRENGTH OF ADHESIVE-SEALED JOINTS IN THE CONTEXT OF DEVELOPING A COMPUTER SYSTEM FOR MONITORING THE CONDITION OF BELT JOINTS DURING CONVEYOR OPERATION
By: Mazurkiewicz, Dariusz

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Issue: 3 Pages: 34-39 Published: 2010

Times Cited: 37
10. RELIABILITY ANALYSIS OF RECONFIGURABLE MANUFACTURING SYSTEM STRUCTURES USING COMPUTER SIMULATION METHODS
By: Gola, Arkadiusz

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume 21, Issue: 1, Pages: 90-102, Published: 2019

Times Cited: 36

 

 



Task „Implementation of procedures ensuring  the originality of scientific papers published in the quarterly „Eksploatacja i Niezawodność – Maintenance and Reliability” financed under contract 532/P-DUN/2018 from the funds of the Minister of Science and Higher Education for science dissemination activities.


Piotr Nikończuk

Wstępny model sedymentacji osadów lakierniczych w rekuperatorze kabiny lakierniczej

Odkładające się na lamelach rekuperatora osady lakiernicze powodują problemy eksploatacyjne. Przekroje poprzeczne kanałów rekuperatora stopniowo zmniejszają się i ostatecznie prowadzi to do zatkania rekuperatora. Oprócz oporów przepływu powietrza osady stanowią również opór termiczny przy wymianie ciepła. W artykule przedstawiono wstępne wyniki modelowania procesu sedymentacji drobin lakieru. Zaprezentowano model powstawania mgły lakierniczej zawierającej krople lakieru o określonej średnicy oraz stopień koncentracji drobin lakieru w kanale wentylacyjnym za filtrem. Wyniki symulacji porównano z wynikami pomiarów w rzeczywistych kabinach lakierniczych.

Preliminary modeling of overspray particles sedimentation at heat recovery unit in spray booth

Overspray sediments settling on the recuperator’s fins cause operational problems. The cross sections of the recuperator’s channels gradually decrease and finally it result in clogging of the recuperator. The layers of sediments cause air flow resistance and also heat transfer resistance. The paper presents preliminary results of sedimentation process modeling. The model of overspray creation takes into account a droplets size and particles concentration in air stream inside extraction ducting. Simulation results are compared with measurements conducted in three commercial spray booths.

Koncepcja miary niezawodności rekuperatora kabiny lakierniczej

Odkładające się na lamelach rekuperatora osady lakiernicze powodują stopniowe zmniejszanie przekroju poprzecznego kanałów rekuperatora. Skutkiem tego procesu są wzrosty oporów przepływu powietrza oraz oporu termicznego przy wymianie ciepła. Oba zjawiska wpływają negatywnie na niezawodność urządzenia. W artykule przedstawiono koncepcję miary niezawodności rekuperatora. W tym celu sformułowano podstawowe wymaganie niezawodnościowe (nieuszkadzalność) oraz zdefiniowano uszkodzenia utożsamiając je z utratą zapasu strumienia powietrza oraz zapasu efektywności wymiany ciepła. Na tym tle określono cechy zdatności urządzenia, granice ich obszarów oraz krytyczny czas utraty zdatności rekuperatora.

The Concept of Reliability Measure of Recuperator in Spray Booth

 

Overspray sediments deposited on the recuperator fins gradually reduce the cross-section of the recuperator channels. The result of this process is the increase in airflow resistance and thermal resistance during heat transfer. Both phenomena have a negative impact on the reliability of the device. This paper presents the concept of recuperator reliability measures. For this purpose, the essential requirement of reliability (indestructibility) was formulated and damage was defined by identifying it with the loss of air flow reserve and reserve of heat transfer efficiency. On this basis ability features of the heat recovery unit were assessed. Limits of features and critical time of recuperator loss of ability were also assessed.

 

 

An attempt at applying machine learning in diagnosing marine ship engine turbochargers

The article presents a diagnosis of turbochargers in the supercharging systems of marine engines in terms of maintenance decisions. The efficiency of turbocharger rotating machines was defined. The operating parameters of turbocharging systems used to monitor the correct operation and diagnose turbochargers were identified. A parametric diagnostic test was performed. Relationships between parameters for use in machine learning were selected. Their credibility was confirmed by the results of the parametric test of the turbocharger system and the main engine, verified by the coefficient of determination. A particularly good fit of the describing functions was confirmed. As determinants of the technical condition of a turbocharger, the relationship between the rotational speed of the engine shaft, the turbocharger rotor assembly and the charging air pressure was assumed. In the process of machine learning, relationships were created between the rotational speed of the engine shaft and the boost pressure, and the indicator of the need for maintenance. The accuracy of the maintenance decisions was confirmed by trends in changes in the efficiency of compressors.


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