Temat: Predictive Maintenance

Skocz do pozycji: 1.

Tytuł:: Detection of wear parameters using existing sensors in the machines environment to reach higher machine precision
Autorzy:: Schmitt, R. R.
Decressin, R.
Dietrich, F.
Dröder, K.
Tematy:: predictive maintenance
analysis
precision
predictive model; Pokaż więcej
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Powiązania:: https://bibliotekanauki.pl/articles/99855.pdf Link otwiera się w nowym oknie
Opis:: This paper presents methods to plan predictive maintenance for precision assembly tasks. One of the key aspects of this approach is handling the abnormalities during the development phase, i.e. before and during process implementation. The goal is to identify abnormalities which are prone to failure and finding methods to monitor them. To achieve this, an example assembly system is presented. A Failure Mode and Effects Analysis is then applied to this assembly system to show which key elements influence the overall product quality. Methods to monitor these elements are presented. A unique aspect of this approach is exploring additional routines which can be incorporated in the process to identify machine specific problems. As explained within the paper, the Failure Mode and Effects Analysis shows that the resulting quality in a case study from a precision assembly task is dependent on the precision of the rotational axis. Although the rotational axis plays a significant role in the resulting error, it is hard to explicitly find a correlation between its degradation and produced parts. To overcome this, an additional routine is added to the production process, which directly collects information about the rotational axis. In addition to the overall concept, this routine is discussed and its ability to monitor the rotational axis is confirmed in the paper.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 2.

Tytuł:: General overview of maintenance strategies – concepts and approaches
Autorzy:: Gackowiec, Paulina
Tematy:: maintenance
maintenance strategies
maintenance management
predictive maintenance; Pokaż więcej
Wydawca:: STE GROUP
Powiązania:: https://bibliotekanauki.pl/articles/2064749.pdf Link otwiera się w nowym oknie
Opis:: This paper presents a literature review of maintenance strategies formulation. The purpose of this article is to provide an overview of different published concepts of maintenance strategies, distinguish the most common approaches to this issue and find a general tendency in strategies classification. Furthermore, the review is aimed to point out the importance of unscheduled downtime which might occur during equipment runtime in a production plant. The paper classifies the existing maintenance concepts and emphasizes key assumptions of the analysed strategies. The literature study and carried out analysis could be useful to find appropriate reliability assurance methods. In addition, defined maintenance approaches might help in decision making process in a company. The paper is a comprehensive overview of discussed strategies, which indicates the most frequent maintenance models in the analysed papers.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 3.

Tytuł:: Life cycle costing used for justifying transition to predictive maintenance strategies
Autorzy:: Mikler, J.
Tematy:: reliability
life cycle costing
predictive maintenance; Pokaż więcej
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Powiązania:: https://bibliotekanauki.pl/articles/99511.pdf Link otwiera się w nowym oknie
Opis:: As the market imposes constantly increasing levels of reliability and availability of production equipment, it is necessary to shift the focus of maintenance toward predictive strategies. However, as any other investment, implementation of the required condition monitoring systems has to be cost justified. This paper presents a case study showing use of LCC calculations to assess changes of maintenance strategy for a CNC machining centre. It was proven that replacing reactive maintenance tasks with simple condition monitoring and preventive activities results in lower whole life cycle cost of the analysed machining centre.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 4.

Tytuł:: A data-driven predictive maintenance strategy based on accurate failure prognostics
Autorzy:: Chen, Chuang
Wang, Cunsong
Lu, Ningyun
Jiang, Bin
Xing, Yin
Tematy:: predictive maintenance
failure prognostics
performance degradation
maintenance cost; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Powiązania:: https://bibliotekanauki.pl/articles/1841691.pdf Link otwiera się w nowym oknie
Opis:: Maintenance is fundamental to ensure the safety, reliability and availability of engineering systems, and predictive maintenance is the leading one in maintenance technology. This paper aims to develop a novel data-driven predictive maintenance strategy that can make appropriate maintenance decisions for repairable complex engineering systems. The proposed strategy includes degradation feature selection and degradation prognostic modeling modules to achieve accurate failure prognostics. For maintenance decision-making, the perfect time for taking maintenance activities is determined by evaluating the maintenance cost online that has taken into account of the failure prognostic results of performance degradation. The feasibility and effectiveness of the proposed strategy is confirmed using the NASA data set of aero-engines. Results show that the proposed strategy outperforms the two benchmark maintenance strategies: classical periodic maintenance and emerging dynamic predictive maintenance.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 5.

Tytuł:: Assessment of explainable anomaly detection for monitoring of cold rolling process
Autorzy:: Jakubowski, Jakub
Stanisz, Przemysław
Nalepa, Grzegorz
Bobek, Szymon
Opis:: The detection and explanation of anomalies within the industrial context remains a difficult task, which requires the use of well-designed methods. In this study, we focus on evaluating the performance of Explainable Anomaly Detection (XAD) algorithms in the context of a complex industrial process, specifically cold rolling. We train several state-of-the-art anomaly detection algorithms on the synthetic data from the cold rolling process and optimize their hyperparameters to maximize its predictive capabilities. Then we employ various model-agnostic Explainable AI (XAI) methods to generate explanations for the abnormal observations. The explanations are evaluated using a set of XAI metrics specifically selected for the anomaly detection task in industrial setting. The results provide insights into the impact of the selection of both machine learning and XAI methods on the overall performance of the model, emphasizing the importance of interpretability in industrial applications. For the detection of anomalies in cold rolling, we found that autoencoder-based approaches outperformed other methods, with the SHAP method providing the best explanations according to the evaluation metrics used.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

Inne

na półce

Skocz do pozycji: 6.

Tytuł:: Performance of explainable AI methods in asset failure prediction
Autorzy:: Bobek, Szymon
Jakubowski, Jakub
Nalepa, Grzegorz
Stanisz, Przemysław
Wydawca:: Springer
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

Inne

na półce

Skocz do pozycji: 7.

Tytuł:: Nowe rozwiązania inteligentnych maszyn dla górnictwa
New solutions of intelligent machines for the mining industry
Autorzy:: Winkler, T.
Drwięga, A.
Tematy:: Information Technology (IT)
Predictive Maintenance
kombajn ścianowy
przenośnik zgrzebłowy
Information technology (IT)
predictive maintenance
longwall shearer
flight-bar conveyors; Pokaż więcej
Wydawca:: Instytut Techniki Górniczej KOMAG
Powiązania:: https://bibliotekanauki.pl/articles/199574.pdf Link otwiera się w nowym oknie
Opis:: W artykule zaprezentowano przykładowe rozwiązania konstrukcyjne i organizacyjne opracowane w Instytucie Techniki Górniczej KOMAG wykorzystujące metody i narzędzia objęte wspólną nazwą Information Technology (IT). Przedstawiono przykładowe maszyny i urządzenia, których praca jest kontrolowana i nadzorowana przez zaawansowane systemy mechatroniczne, takie jak kombajn ścianowy KSW-800NE i przenośnik zgrzebłowy.
Examples of design and organizational solutions developed at the KOMAG Institute of Mining Technology, which use the Information Technology (IT) methods and tools, are given. Examples of machines and devices such as KSW-800NE longwall shearer and flight-bar conveyor, operation of which is controlled by advanced mechatronic systems, are presented.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 8.

Tytuł:: Machine tool ability representation: a review
Autorzy:: Sadasivam, L.
Archenti, A.
Sandberg, U.
Tematy:: machine tool
ability
health
predictive maintenance
accuracy; Pokaż więcej
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Powiązania:: https://bibliotekanauki.pl/articles/99804.pdf Link otwiera się w nowym oknie
Opis:: Smart manufacturing and predictive maintenance are current trends in the manufacturing industry. However, the holistic understanding of the machine tool health condition in terms of accuracy, functions, process and availability is still unclear. This uncertainty renders the development of models and the data acquisition related to machine tool health condition ineffective. This paper proposes the term machine tool ability as an interconnection between the accuracy, functions, the process and the availability to overcome the lack of the holistic understanding of the machine tool. This will facilitate the further development of qualitative or quantitative methods as well as models. The research highlights the challenges and gaps to understand the machine tool ability.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 9.

Tytuł:: Predictive Maintenance Sensors Placement by Combinatorial Optimization
Autorzy:: Borissova, D. I.
Mustakerov, I. C.
Doukovska, L. A.
Tematy:: predictive maintenance
optimal sensors placement
combinatorial optimization; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/227278.pdf Link otwiera się w nowym oknie
Opis:: The strategy of predictive maintenance monitoring is important for successful system damage detection. Maintenance monitoring utilizes dynamic response information to identify the possibility of damage. The basic factors of faults detection analysis are related to properties of the structure under inspection, collect the signals and appropriate signals processing. In vibration control, structures response sensing is limited by the number of sensors or the number of input channels of the data acquisition system. An essential problem in predictive maintenance monitoring is the optimal sensor placement. The paper addresses that problem by using mixed integer linear programming tasks solving. The proposed optimal sensors location approach is based on the difference between sensor information if sensor is present and information calculated by linear interpolation if sensor is not present. The tasks results define the optimal sensors locations for a given number of sensors. The results of chosen sensors locations give as close as possible repeating the curve of structure dynamic response function. The proposed approach is implemented in an algorithm for predictive maintenance and the numerical results indicate that together with intelligent signal processing it could be suitable for practical application.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 10.

Tytuł:: Fault Detection and Prediction for a Wood Chip Screw Conveyor
Autorzy:: Henriques, Lucas
Farinha, Torres
Mendes, Mateus
Tematy:: industrial equipment
machine learning
predictive maintenance
screw conveyor; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Powiązania:: https://bibliotekanauki.pl/articles/59113213.pdf Link otwiera się w nowym oknie
Opis:: Equipment maintenance is a key aspect to maximize its availability. Nowadays, much of the functioning and condition monitoring data from industrial machines is collected through sensors and stored, for off-line analysis. The present work focuses on data analysis of a screw conveyor of a biomass industry. The screw velocity and load were monitored and analysed, in order to detect and predict possible faults. A machine learning approach was used to detect anomalies, where different algorithms were tested with the data available, in order to train an anomaly classifier. The anomaly classifier was able to accurately identify most anomalies, based on historical data, temporal patterns and information of the maintenance interventions performed. The research carried out allowed to conclude that the Extra Trees Classifier algorithm achieved the best performance, among all algorithms tested, with 0.7974 F-score in the test set. The anomaly classifier has been shown to achieve remarkable accuracy in identifying anomalies. This research not only improves understanding of the performance of screw conveyors in biomass industries, but also highlights the practical utility of employing machine learning for proactive fault detection.
Dostawca treści:: Biblioteka Nauki

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