Vol 22, No 1 (2020)

The article develops the second part of a set of algorithms for digital support of the identification process, the search for causes and solutions to problems in the field of quality of engineering products.

The purpose of the work is to investigate the application of the QFD methodology (structuring or deploying the quality function, quality house) for standardizing the parameters of a metal-cutting tool on the example of turning tools, to determine the most important technical characteristics of the product for the consumer. In the course of work, the quality House was built using a turning cutting tool for roughing and finishing. The stages of collecting consumer characteristics, technical characteristics, determining the relationships between them, as well as creating a correlation matrix to determine the positive/negative relationship between technical characteristics, consumer and technical benchmarking were performed sequentially. According to the obtained data, the most priority technical characteristics necessary for further development of the cutting tool were identified. Based on the stages of building a quality House, a list of technical parameters of turning tools aimed at meeting customer requirements is determined.

The possibility of developing a technique for calculating the wear of the flank surface of mills is shown on the basis of a generalized friction model, taking into account the entire complex of the main external factors acting and the physical and mechanical characteristics of the materials of the interacting surfaces of the tool and the workpiece. The calculated dependence of the wear values, the influence of some hard-to-consider factors is supposed to be taken into account by the experimentally determined proportionality coefficients and the index of the calculated ratio, has been proposed.

The article proposes a solution to the problem of processing point clouds whose size exceeds available RAM by using Point Cloud Library (PCL). The problem of lack of RAM is solved using the dynamic allocation mechanism on the mapped memory. The methods of introducing such a mechanism into the PCL library are analyzed, and the performance of processing point clouds and the amount of memory consumed using RAM or mapped (external) memory is evaluated.

The paper analyzes the efficiency of suppressing oscillations of the working medium in pipeline circuits with dampers of the acoustic filter type. Based on the analysis of these indicators, analytical dependencies are obtained that allow us to estimate the change in the wave process in the pipeline chain before and after the damper. Recommendations are developed for selecting generalized parameters of dampers that provide the necessary degree of attenuation of pressure oscillation.

The article is devoted to methods for analyzing object-attribute data in low structured areas. Specifically, a demonstrational example of biclusterization of similar data in the field of agricultural crops selection is considered. It is shown what opportunities are appearing for the systematization of empirical data. The data biclusterization method under consideration - a classical formal concept analysis - is an applied branch of lattice theory; a brief reference is given on its mathematical foundations. The source material for the demonstrational example was borrowed from the catalog of innovative developments of the Samara Research Institute of Agricultural Sciences named after N.M. Tulaykov. Sorts of soft spring wheat were chosen as objects, and several properties which are describing them were chosen as attributes. A number of these properties are scaled in accordance with state standard 9353-2016 for wheat. Based on the selected and adjusted material, the initial table “objects-properties”, or a formal context for the formal concept analysis, is formed. To process this data, we used the free software package ConExp, which implements a methodical complex for formal concept analysis. The main results that these methods give for selection data structuring are demonstrated. These results include a lattice of formal concepts, implications and associative rules on a set of attributes. Moreover, the result of the OntoWorker software package being developed at ICCS RAS - SamSC RAS is demonstrated. The outcome consists in transforming and reducing the lattice of formal concepts into a special taxonomy of formal concepts (classes) that is more convenient for the user to perceive and interpret. It is noted that advanced methods of formal concept analysis can take into account the incompleteness of the considered data, determined by the series multiplicity of measurement experiments with different degrees of results reliability, and by the presence of competing measurement procedures with different degrees of confidence in their results. This reflects the realities of the empirical information accumulation directly during multidimensional observations and measurements in selection probations. It was emphasized that the effective application of the considered methods is possible only in cooperation of knowledge data expert and specialists in the field of formal concept analysis.

A method of discovery of stock function is applied to study of multitempo linear systems. Dissipability of multiparameter linear systems is investigated. The application of the method is illustrated on example.

This paper describes application of diagnostic model, created with ontological modelling methods and machine learning text classification algorithms, for fault detection, based on system log messages data, in enterprise-level storage system. Proposed fault detection model uses external procedures for the description ofthe relations between parameters and states of storage systems, based on the implementation of the machine learning algorithms. As an example of such relation, author describes application of the text classification method for the task of software log analysis.