@ARTICLE{Krajewska-Spiewak_Joanna_Maintenance_2021,
 author={Krajewska-Spiewak, Joanna and Turek, Jan and Gawlik, Józef},
 volume={vol. 12},
 number={No 2},
 journal={Management and Production Engineering Review},
 howpublished={online},
 year={2021},
 publisher={Production Engineering Committee of the Polish Academy of Sciences, Polish Association for Production Management},
 abstract={Wear of the working surfaces of the forging dies in the process of manufacturing products with the die forging technique leads to deterioration of their operational properties as well as their technological quality. A characteristic feature of production in small and medium-sized enterprises is the high variability of the product range and short production series, which can be repeated in the case of re-orders by customers. In this type of production conditions, a technological criterion in form of – a change in the characteristic and selected dimension of forging is usually used to assess the quality of products. An important problem is, whether by taking up another order for a series of the same type of product, it will be possible to implement it with the existing die, or should a new die be made? As a result of the research carried out in the company implementing this type of contract, a procedure was proposed for forecasting the abrasive wear of die working surfaces on the basis of a technological criterion, easy to determine in the conditions of small and medium-sized enterprises. The paper presents the results of the wear assessment of a die made out of hot-work tool steel X37CrMoV5-1 (WCL) and dies made of 42CrMo4 alloy structural steel with hardfacing working surfaces by F-818 wire. To determine and forecast the process of die wear, a mathematical model in the form of neural networks was used. Their task was to forecast the ratio of the increment in introduced wear intensity indicator to the number of forgings made during the process. Taking into account},
 type={Article},
 title={Maintenance Supervision of the Dies Condition and Technological Quality of Forged Products in Industrial Conditions},
 URL={http://ochroma.man.poznan.pl/Content/120061/3_595_cor.pdf},
 doi={10.24425/mper.2021.137675},
 keywords={intensity of die wear, forging technological quality, neural networks},
}