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Technological Possibilities of the Carbide Tools Application for Precision Machining of WCLV Hardened Steel

Grabowski Marcin, Gawlik Józef, Krajewska-Śpiewak Joanna, Skoczypiec Sebastian, Tyczyński Piotr

Advances in Science and Technology. Research Journal

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2022

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Vol. 16, no 1

141--148

EN

Precision milling of free (curved) surfaces with the use of monolithic milling cutters is used in the production of hardened steel elements such as dies, molds, or press tools. Precision milling processes are carried out with the following milling parameters: axial cutting depth ap <0.3 mm, cutting width ae <0.5 mm and the required machining accuracy below 40 µm. The quality of the obtained surfaces in injection molds is directly transferred to the quality of the molded part. One of the key criteria for the manufactured elements is the surface quality which is mainly assessed by the roughness parameters. Due to the use of carbide tools high reliability and quality of machining is obtained which allows to eliminate the grinding process. In precision milling processes, due to the very small radius of the cutting edge and the cross-sections of the cutting layers, the conditions that must be met for the decohesion process to occur are fundamentally diff erent from macro-scale. The minimum value range of ap and ae parameters was determined in a carried-out experiment, which allows for stable and repeatable machining. The tests were carried out with double-edge shank cutters with a diameter of 6 mm on a workpiece made out of WCVL hardened steel 45–47 HRC. Recommended machining conditions have been defi ned to ensure the required technological quality of the surface layer. The research was fi nanced under the research project POIR.01.01.01-000890/17 co-fi nanced by the European Union from the European Regional Development Fund.

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Maintenance Supervision of the Dies Condition and Technological Quality of Forged Products in Industrial Conditions

Krajewska-Śpiewak Joanna, Turek Jan, Gawlik Józef

Management and Production Engineering Review

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2021

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Vol. 12, No. 2

27--32

EN

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

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Application of classification neural networks for identification of damage stages of degraded low alloy steel based on acoustic emission data analysis

Krajewska-Śpiewak Joanna, Lasota Igor, Kozub Barbara

Archives of Civil and Mechanical Engineering

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2020

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Vol. 20, no. 4

156--165

EN

The paper presents the influence of low alloy steel degradation on the acoustic emission (AE) generated during static tension of notched specimen. The material was cut from a technological pipeline long-term operated in the oil refinery industry. Comparative analysis of AE activity generated by damage process of degraded and new material has been carried out. The different AE parameters were used to detect different stages of fracture process of low alloy steel under quasi-static tensile test. Neural networks with three layers were created with Broyden–Fletcher–Goldfarb–Shanno learning algorithm for a database analysis. The different AE parameters were included in the input layer. Classification neural networks were created in order to determine the stages of material degradation. The results obtained from the carried out studies will be used as the basis for new methodology development of the assessment of the structural condition of in-service equipment.