ISSN 1507-2711
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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The average number of weeks from article submission to the final decision: 4 weeks




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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.


LAST ADDED

Specification of estimation of a passenger car ride smoothness under various exploitation conditions

DOI: 10.17531/ein.2021.4.14

Article citation info: 
Vaičiūnas G, Steišūnas S, Bureika G. Specification of estimation of a passenger car ride smoothness under various exploitation conditions. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021; 23 (4): 719–725, http://doi.org/10.17531/ein.2021.4.14.

 

Abstract: 

The stability and smoothness of rolling stock running could be defined accurately by universal Sperling's comfort index. The divergences of variation of Sperling's comfort index of a passenger car under specific operating conditions of running gear are examining in this paper. Numerical simulations of a passenger car running with independently rotating wheels under various conditions have been performing. Gained results showed that divergences of the Sperling's comfort index variation are particularly significant due to running gear component oscillations in the horizontal plane (lateral direction). A field experiment of a passenger car with a solid (traditional) wheelset with a flat running surface proved this hypothesis. The obtained results of this experiment confirmed this assumption. Therefore, the study of the regularities of lateral oscillations of a passenger car is the logical direction of further research.

The study on the automated storage and retrieval system dependability

DOI: 10.17531/ein.2021.4.13

Article citation info: 
Lewczuk K. The study on the automated storage and retrieval system dependability. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021; 23 (4): 709–718, http://doi.org/10.17531/ein.2021.4.13.

 

Abstract: 

Automated storage systems have become the basis of warehouse logistics. The article presents a discussion on the reliability and dependability of Automated Storage and Retrieval Systems (ASRS), which are perceived as solutions with high technical reliability. Still, their role in the dependability of the entire warehouse system is to be discussed. The concepts of reliability and dependability in logistics systems like ASRS are defined, and a literature review in this area is presented. On this basis, the factors influencing the dependability of ASRS are discussed in a way not present in the discussion on this topic so far. Then, the ASRS simulation model (based on FlexSim simulation software) is presented. The model tests the influence of ASRS configuration and assigned resources on the dependability of the warehouse as a master system. The summary includes observations on defining the reliability and dependability of ASRS.

Application of machine learning and rough set theory in lean maintenance decision support system development

DOI: 10.17531/ein.2021.4.12

Article citation info: 
Antosz K, Jasiulewicz-Kaczmarek M, Paśko Ł, Zhang C, Wang S. Application of machine learning and rough set theory in lean maintenance decision support system development. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021; 23 (4): 695–708, http://doi.org/10.17531/ein.2021.4.12.

 

Abstract: 

Lean maintenance concept is crucial to increase the reliability and availability of maintenance equipment in the manufacturing companies. Due the elimination of losses in maintenance processes this concept reduce the number of unplanned downtime and unexpected failures, simultaneously influence a company’s operational and economic performance. Despite the widespread use of lean maintenance, there is no structured approach to support the choice of methods and tools used for the maintenance function improvement. Therefore, in this paper by using machine learning methods and rough set theory a new approach was proposed. This approach supports the decision makers in the selection of methods and tools for the effective implementation of Lean Maintenance.

Remaining useful life prediction of bearings with different failure types based on multi-feature and deep convolution transfer learning

DOI: 10.17531/ein.2021.4.11

Article citation info: 
Wu C, Sun H, Lin S, Gao S. Remaining useful life prediction of bearings with different failure types based on multi-feature and deep convolution transfer learning. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021; 23 (4): 685–694, http://doi.org/10.17531/ein.2021.4.11.

 

Abstract: 

The accurate prediction of the remaining useful life (RUL) of rolling bearings is of immense importance in ensuring the safe and smooth operation of machinery and equipment. Although the prediction accuracy has been improved by a predictive model based on deep learning, it is still limited in engineering because lots of models use single-scale features to predict and assume that the degradation data of each bearing has a consistent distribution. In this paper, A deep convolutional migration network based on spatial pyramid pooling (SPP-CNNTL) is proposed to obtain higher prediction accuracy with self-extraction of multi-feature from the original vibrating signal. And to consider the differences of the data distribution in different failure types, transfer learning (TL) added with maximum mean difference (MMD) measurement function is used in the RUL prediction part. Finally, the data of IEEE PHM 2012 Challenge is used for verification, and the results show that the method in this paper has high prediction accuracy.


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