Publications by authors named "Marcin Szpunar"

Single point incremental forming (SPIF) is becoming more and more widely used in the metal industry due to its high production flexibility and the possibility of obtaining larger material deformations than during conventional sheet metal forming processes. This paper presents the results of the numerical modeling of friction stir rotation-assisted SPIF of commercially pure 0.4 mm-thick titanium sheets.

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The article presents the results of the analysis of the influence of incremental sheet forming process parameters on surface roughness measured on both sides of conical drawpieces made from pure titanium Grade 2 sheets. The experimental plan was created on the basis of a central composite design. The study assumed the variability of feed rate, spindle speed, and incremental step size in the following range: 500-2000 mm/min, 0-600 rpm, and 0.

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Incremental sheet forming of titanium and its alloys has a significant role in modern manufacturing techniques because it allows for the production of high-quality products with complex shapes at low production costs. Stamping processes are a major contributor to plastic working techniques in industries such as automotive, aerospace and medicine. This article reviews the development of the single-point incremental forming (SPIF) technique in titanium and its alloys.

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The aim of the research described in this paper is to analyse the synergistic effect of types of synthetic oil and their density on the value of the coefficient of friction (COF) of Ti-6Al-4V titanium alloy sheets. Lubrication performance of commercial synthetic oils (machine, gear, engine and hydraulic) was tested in a strip draw friction test. The friction tests consisted of pulling a strip specimen between two cylindrical fixed countersamples.

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Single point incremental forming (SPIF) is an emerging process that is well-known to be suited for fabrication in small series production. The aim of this paper was to determine the optimal input parameters of the process in order to minimise the maximum of both the axial and the in-plane components of the forming force achieved during SPIF and the surface roughness of the internal surface of truncated-cone drawpieces. Grade 2 pure titanium sheets with a thickness of 0.

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This paper presents the application of multi-layer artificial neural networks (ANNs) and backward elimination regression for the prediction of values of the coefficient of friction (COF) of Ti-6Al-4V titanium alloy sheets. The results of the strip drawing test were used as data for the training networks. The strip drawing test was carried out under conditions of variable load and variable friction.

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