The subject of the presented work was the analysis of the influence of the distance between the electrodes using in the coating process on the tribological properties of oxide coatings. Oxide coatings were prepared on EN AW-5251 aluminum alloy samples. The samples surfaces were subjected to hard anodizing process in a multicomponent electrolyte based on sulfuric acid with an addition of organic acids. Anodizing was carried out with a constant electric charge density of 180 A•min/dm2 . The distances between the electrodes for subsequent samples increased every 0.125 m up to 1 m. The tribological partner in a sliding couple with oxide layers was pin of PEEK/BG. Tribological tests were conducted on a T-17 tester in reciprocating motion, in technically dry friction conditions. Before and after tribological test, examination of the geometrical structure of counter-specimens’ surface was carried out using the Form Talysurf contact profilographometer, via a 3D method. The most satisfactory tribological parameters were obtained for the PEEK/BG association with the coating produced at a distance between the electrodes equal to 0.25 m.
Faced with ever-increasing customer demands and global competition, companies are forced to look for production reserves, increase efficiency and productivity. Hence, the need to monitor the use of the machine park has arisen, making it possible to identify waste and production reserves in the implemented technological processes. The aim of the article is to evaluate the effectiveness of the production line of internal frame doors and to analyze the correctness of the use of selected key indicators of the production process effectiveness. This article proposes a response to the problems formulated in manufacturing companies, including practical aspects of the use of specific measures to assess the effectiveness of the use of technical infrastructure. The solutions presented in the article can be used in practice for improvements in production units.
The bootstrap method is a well-known method to gather a full probability distribution from the dataset of a small sample. The simple bootstrap i.e. resampling from the raw dataset often leads to a significant irregularities in a shape of resulting empirical distribution due to the discontinuity of a support. The remedy for these irregularities is the smoothed bootstrap: a small random shift of source points before each resampling. This shift is controlled by specifically selected distributions. The key issue is such parameter settings of these distributions to achieve the desired characteristics of the empirical distribution. This paper describes an example of this procedure.
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