Predictive Maintenance Of Industrial Robots

2020 ◽  
Author(s):  
Vansh Jatana
Author(s):  
Arash Golibagh Mahyari ◽  
Thomas Locher

Industrial robots play an increasingly important role in a growing number of fields. Since the breakdown of a single robot may have a negative impact on the entire process, predictive maintenance systems have gained importance as an essential component of robotics service offerings. The main shortcoming of such systems is that features extracted from a task typically differ significantly from the learnt model of a different task, incurring false alarms. In this paper, we propose a novel solution based on transfer learning which addresses a well-known challenge in predictive maintenance algorithms by passing the knowledge of the trained model from one task to another in order to prevent the need for retraining and to eliminate such false alarms. The deployment of the proposed algorithm on real-world datasets demonstrates that the algorithm can not only distinguish between tasks and mechanical condition change, it further yields a sharper deviation from the trained model in case of a mechanical condition change and thus detects mechanical issues with higher confidence.


Procedia CIRP ◽  
2021 ◽  
Vol 104 ◽  
pp. 62-67
Author(s):  
Corbinian Nentwich ◽  
Gunther Reinhart

2014 ◽  
Vol 2 (5) ◽  
pp. 152
Author(s):  
José Manuel Torres Farinha ◽  
Inácio Adelino Fonseca ◽  
Rúben Silva Oliveira ◽  
Fernando Maciel Barbosa

2012 ◽  
Vol 58 (4) ◽  
pp. 351-356
Author(s):  
Mincho B. Hadjiski ◽  
Lyubka A. Doukovska ◽  
Stefan L. Kojnov

Abstract Present paper considers nonlinear trend analysis for diagnostics and predictive maintenance. The subject is a device from Maritsa East 2 thermal power plant a mill fan. The choice of the given power plant is not occasional. This is the largest thermal power plant on the Balkan Peninsula. Mill fans are main part of the fuel preparation in the coal fired power plants. The possibility to predict eventual damages or wear out without switching off the device is significant for providing faultless and reliable work avoiding the losses caused by planned maintenance. This paper addresses the needs of the Maritsa East 2 Complex aiming to improve the ecological parameters of the electro energy production process.


Author(s):  
Marek Vagas

Urgency of the research. Automated workplaces are growing up in present, especially with implementation of industrial robots with feasibility of various dispositions, where safety and risk assessment is considered as most important issues. Target setting. The protection of workers must be at the first place, therefore safety and risk assessment at automated workplaces is most important problematic, which had presented in this article Actual scientific researches and issues analysis. Actual research is much more focused at standard workplaces without industrial robots. So, missing of information from the field of automated workplaces in connection with various dispositions can be considered as added value of article. Uninvestigated parts of general matters defining. Despite to lot of general safety instructions in this area, still is missed clear view only at automated workplace with industrial robots. The research objective. The aim of article is to provide general instructions directly from the field of automated workplaces The statement of basic materials. For success realization of automated workplace is good to have a helping hand and orientation requirements needed for risk assessment at the workplace. Conclusions. The results published in this article increase the awareness and information of such automated workplaces, together with industrial robots. In addition, presented general steps and requirements helps persons for better realization of these types of workplaces, where major role takes an industrial robot. Our proposed solution can be considered as relevant base for risk assessment such workplaces with safety fences or light barriers.


Author(s):  
Dionisio Martins ◽  
Thiago de Moura Prego ◽  
Amaro Lima ◽  
Douglas Hemerly ◽  
Fabrício Lopes e Silva

Author(s):  
V.G. Farhadov ◽  
◽  
A.A. Babaeva ◽  
A.T. Mamedova ◽  
◽  
...  

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