• SCIENCE

    ANALYSIS OF THE DRUG PRODUCT QUALITY PARAMETERS THROUGH STATISTICAL METHODS

    Science. Business. Society., Vol. 3 (2018), Issue 2, pg(s) 55-58

    Correlations between some basic quality parameters of a drug product, which are very important for the pharmaceutical manufacture of solid dosage forms are studied, on the base of experimental data from 135 batches. Factor analysis, control charts and histograms are implemented for the quality parameters – strength of tablet, assay of the active substance, acid resistance, disintegration), water content, drug dissolution after 150 minutes and drug dissolution after 165 minutes.. The parameter drug dissolution after 120 minutes is dropped from the analysis, because it was observed to have a zero value for all measurements. The main aim of this article is to search for a possible underlying structure in the variables with exploratory factor analysis, to monitor whether the quality parameters’ variation is consistent and the empirical distributions of the most important quality parameters using control charts and histograms.

  • TECHNOLOGIES

    GRAPHICAL USER INTERFACE FOR OPTIMIZATION OF ELECTRON BEAM WELDING BY NEURAL AND REGRESSION MODELS FOR OBTAINING DEFECTFREE WELDS

    Machines. Technologies. Materials., Vol. 12 (2018), Issue 2, pg(s) 76-79

    This paper considers the process electron beam welding of stainless steel type 1H18NT in vacuum. Based on experimental data, the influence of the variations of the following process parameters: electron beam power, welding velocity, the distances from the magnetic lens of the electron gun to the beam focus and to the surface of the treated sample is investigated.

    Neural and regression models for the geometry characteristics of the welded joints: surface of the weld cross-sections, weld depths and mean weld widths of the samples are estimated, as well as models for defining the areas of the process parameters, where the appearance of defects is or is not expected. The obtained models are used for developing the graphical user interface aiming investigation and prediction of the electron beam welding characteristics and process parameter optimization. This software can be implemented for supporting the operator’s choice of appropriate work regimes, obtaining the required welds quality standards, for education and investigations.

  • TECHNOLOGIES

    FUNCTIONAL AREAS AND ARCHITECTURAL FRAMEWORK FOR THE MANAGEMENT OF THE ELECTRON BEAM WELDING INSTALATION

    Machines. Technologies. Materials., Vol. 12 (2018), Issue 1, pg(s) 28-30

    Abstract: Management is the process of processing the information aiming decision making to resolve problem or to achieve the target. High advanced automated processes, including the vacuum system with pump and pressure control, management of the cooling system, management of the manipulator, high voltage control and emission current, the control of the electron beam movement and its characteristics, as well as computer-based automatic control ofthe beam power distribution, must be integrated on the basis of the use of systems for operational management of production. The present work presents the hierarchical structure and architectural framework for the management of an installation for electron beam welding, evaporation and surface modification.

  • TECHNOLOGIES

    ROBUST DESIGN AND MULTIPLE CRITERIA OPTIMIZATION OF ELECTRON BEAM GRAFTING OF CORN STARCH

    Machines. Technologies. Materials., Vol. 11 (2017), Issue 12, pg(s) 583-586

    Electron beam (EB) irradiation has the ability to modify polymer substrates by process of graft copolymerization to synthesize water-soluble copolymers having flocculating potential. Models – depicting the dependencies of the described quality characteristics (their means and variances) from process parameters – are estimated by implementation of the robust engineering methodology for quality improvement. Multiple criteria optimization based on the desirability function approach, involving requirements for economic efficiency, assurance of low toxicity, high copolymer efficiency in flocculation process, good solubility in water, bias, robustness, quality of prediction and the relative importance of responses, is presented.

  • MATHEMATICAL MODELLING OF TECHNOLOGICAL PROCESSES AND SYSTEMS

    MODELLING OF THE FORM OF ELECTRON BEAM WELDING JOINTS

    Mathematical Modeling, Vol. 2 (2018), Issue 1, pg(s) 13-16

    This article discusses a modelling approach for the welded seam form obtained by electron beam welding based on experimental data and types of mathematical functions. The process of electron beam welding is carried out by dividing the electron beam into two parts, resulting in the formation of two liquid baths. The samples that are welded are made of stainless steel with a change in process parameters: the distance between the two electron beam parts and the ratio of the power distribution between the two beam parts, the frequency of the deflection signal, the beam current, and the welding speed. Focusing current is of constant value. The weld cross sections shown in different process parameters are used to evaluate their shape using standard mathematical function – Gaussian functions.

  • TECHNOLOGIES

    ELECTRON BEAM LITHOGRAPHY METHOD FOR HIGH-RESOLUTION NANOFABRICATION

    Machines. Technologies. Materials., Vol. 11 (2017), Issue 3, pg(s) 106-109

    Electron beam lithography (EBL) is one of the few “top-down” methods and EBL is becoming increasingly widespread in R&D and small volume production due to its flexibility and mask-less nature, very high (sub-10 nm) resolution and accuracy and in many cases EBL is the only possible alternative. In this paper, obtained experimental and simulation results for EBL nano-patterning using the high-resolution electron beam resist Hydrogen Silsesquioxane (HSQ) are presented and discussed. The influence of EBL process parameters such as exposure dose, resist thickness and development process conditions on the obtained developed images is studied. The applied simulation tool for the resists’ characteristics evaluation is suitable for a precise control of obtained image dimensions in the resist applied as a masking layer for nano-patterning. This investigation and simulation of the characteristics of the studied e-beam resist aim to improve the resolution of the nano-dimensioned electron beam lithography and results for nano-lithography applications are also presented.

  • INVESTIGATION AND OPTIMIZATION OF ELECTRON BEAM GRAFTING OF CORN STARCH

    Machines. Technologies. Materials., Vol. 10 (2016), Issue 3, pg(s) 52-55

    Experimental investigation of the modification of starch by grafting acrylamide using electron beam irradiation in order to synthesize water-soluble copolymers having flocculation abilities is performed. The influence of the variation of the parameters acrylamide/starch (AMD/St) weight ratio, electron beam irradiation dose and dose rate, as well as the presence or absence of metallic silver nanoparticles is investigated. The characterization of graft copolymers was carried out by monomer conversion coefficient, residual monomer concentration, intrinsic viscosity and Huggins’ constant. Models, describing the dependencies of the quality characteristics (their means and variances) from the process parameters, are estimated by implementation of the robust engineering approach in the case of qualitative and quantitative factors. Multi-criteria optimization involving requirements for economic efficiency, assurance of low toxicity, high copolymer efficiency in flocculation process and good solubility in water is also presented.

  • TECHNOLOGICAL BASIS OF “INDUSTRY 4.0”

    NEURAL NETWORKS FOR DEFECTIVENESS MODELING AT ELECTRON BEAM WELDING

    Industry 4.0, Vol. 2 (2017), Issue 1, pg(s) 5-8

    This paper considers the process electron beam welding in vacuum of stainless steel 1H18NT. Neural network based models are developed and used for the description of the defectiveness, depending on the process parameters – electron beam power, welding velocity, the distance between the main surface of the magnetic lens of the electron gun and the beam focusing plane and the distance between the main surface of the magnetic lens of the electron gun and the sample surface. Neural network (NN) models, based on a multi-layered feedforward neural network, trained with Levenberg-Marquardt error backpropagation algorithm are compared with NN models, based on Pattern recording neural network, trained with Conjugate Gradient Algorithm. The neural networks are trained, verified and tested using a set of experimental data. The obtained models are implemented to predict areas of process parameters, where the appearance of defects is most probable and the location of welding regimes that should be avoided.