Effect of Ultra-Fine Grinding on the Structure of Plant Raw Materials and the Kinetics of Melanin Extraction

Enhancing the extraction rate is one of the key objectives in optimization of extraction of substances from biogenic raw materials. Ultra-fine grinding of plant raw materials (to achieve particle size less than 300 µm) is a very appealing method for increasing the extraction rate using relatively simple equipment. However, this approach often fails to yield the desired result. This study focuses on the kinetics of melanin extraction from two types of raw materials: fungus Ganoderma applanatum and buckwheat husk. Particle size is shown to be just one of the key factors. The degree of order of plant-based feedstock strongly affects the intraparticle diffusion constants and can be a parameter controlling the diffusion rate. It has been shown that there exist optimal degrees of disorder of the crystal structure of plant raw materials, which have a dome-shaped dependence pattern and allow one to increase the diffusion coefficient by several dozen times. The kinetics of melanin extraction was described by some kinetic models that include the first order equation, the Baker and Lonsdale model, the Axelrud equation, and the Ritger–Peppas model.

Research into thickening processes of concentrates of gold-bearing ores

The aim was to improve the thickening of an ultra-fine flotation concentrate by efficient flocculants when processing refractory sulphide gold-bearing ores from South Urals deposits. The chemical ore composition was studied using gravimetric, atomic absorption, chemical, X-ray fluorescent, assay test and electron microprobe analytical methods. Particle size analysis of the ultra-fine flotation concentrate under study was performed using a Malvern Hydro Mastersizer 2000MU analyser (Malvern Panalytical Ltd, UK). In thickening experiments, samples with the same composition after the ultra-fine grinding process were used. The gold content in the ore was determined (22.8 g/t) based on analytical studies on the material composition of samples. At least 92% of the final grain size class is -20 microns. Laboratory tests performed on eight samples containing polyacrylamide-based flocculants revealed an optimal A44 flocculant (produced in China). The flocculant meets the requirements for minimum flow rate, deposition rate and L:S ratio. The specific performance of the JX20 radial thickener (JPMFex Corp. Ltd., China) was calculated. The optimal flocculant flow rate is 200 g/t per 1 t of thickened material, leading to thickening 50 t of pulp per 1 m2 of thickener per day. The A44 flocculant is recommended for pilot testing. Thus, developing, testing and implementing fundamentally new reagents and improving existing technologies of processing gold-containing ores and concentrates are necessary to intensify the ore dewatering processes after ultra-fine grinding.

Multi-Objective Optimization of Process Parameters to Enhance Efficiency in the Shoe-Type Centerless Grinding Operation for Internal Raceway of Ball Bearings

In this article, new research on the multi-objective optimization of the process parameters applied to enhance the efficiency in the shoe-type centerless grinding operation for the inner ring raceway of the ball bearing made from SUJ2 alloy steel is presented. The four important input parameters for this process, which included the normal feed rate of fine grinding (Snf), the speed of the workpiece (Vw), the cutting depth of fine grinding (af), and the number of ground parts (Np), were investigated. The aim of the study was to find the most appropriate value set of process parameters in order to, simultaneously minimize the grindstone wear (Gw), maximize the material removal rate (MRR) and the total number of ground parts in a grinding cycle (N’p), while guaranteeing other technology requirements such as surface roughness Ra ≤ 0.5 (µm), oval level Op ≤ 3 (µm), etc. In order to solve the problem, based on the experimental data, in which the grindstone wear was measured online by a measuring system consisting of two pneumatic probes, the optimization of the target functions of Gw, N’p, and MRR and mathematical models that express the dependencies of outcome parameters Gw, Ra, Op, MRR, etc. on the process parameters were determined. Therefore, a global optimal solution of such a discrete and nonlinear multi-objective optimization problem was solved by using a genetic algorithm, presenting the most appropriate process parameters as follows: Snf = 15.38 (µm/s), Vw = 6.00 (m/min), af = 11.76 (µm), and Np = 20 (parts/cycle). In addition, the impact of the four process parameters (Snf, Vw, af, Np) on the wear of the grinding wheel (Gw), the oval level of parts (Op), and the surface roughness of parts (Ra) was evaluated. The discovered technology mode has been applied to the real machining process for the inner ring raceway of the 6208_ball bearing made from SUJ2 alloy steel, and the outcome showed a much better result in comparison with default setting modes, while still ensuring the technology requirements. The difference between the predicted values and the real values of the parameters Gw, Ra, Op, and MRR were controlled within 5% of the ranges.

Predictive modeling of surface finish in fine grinding

Predictive modeling of surface finish in fine grinding

Predictive modeling of surface finish in fine grinding

Predictive modeling of surface finish in fine grinding