Full-factor matrix model of accuracy of dimensions performed on multi-purpose CNC machines

Introduction. One of the main reasons that modern multi-purpose CNC machines do not use the capabilities of multi-tool processing is the lack of recommendations for design in this direction and, accordingly, for adjustment schemes. The study of the possibilities of multi-tool processing on multi-purpose machines is the subject of the work. The purpose of research: The problem of developing full-factor matrix models of dimensional accuracy and its sensitivity to the machining process is considered to increase the machining efficiency while ensuring machining accuracy using the technological capabilities of multi-tool machining on modern multi-purpose CNC machines. For this purpose, full-factor matrix models of the size scattering fields performed on multi-tool double-carriage adjustments have been developed, taking into account the cases of processing parts with dimensions that differ sharply in different directions, which are often encountered in practice, and in this case, the significant influence of the turns of the workpiece on the processing error, especially in directions with sharply different overall dimensions. Results of research: The developed accuracy models make it possible to calculate not only plane-parallel displacements of the technological system for double-carriage adjustments, but also angular displacements around base points, take into account the combined effect of many factors – a complex characteristic of the subsystems of the technological system (plane-parallel matrix of compliance and angular matrix of compliance), the geometry of the cutting tool , the amount of bluntness of the tool, cutting conditions, etc. As a result, based on the developed accuracy models, it is possible to obtain several ways to control multi-tool machining, including improving the structure of multi-tool adjustments, calculating the limiting values of cutting conditions. Based on the developed full-factor matrix models, it became possible to develop recommendations for the design of adjustments and the creation of an automated design system for multi-tool machining for a group of modern multi-purpose CNC lathes. Scope of the results: The results obtained can be used to create mathematical support for the design of operations in CAD-systems provided for multi-tool multi-carriage machining performed on multi-purpose machines. Conclusions: The developed models and methodology for simulating the machining accuracy make it possible to increase the accuracy and efficiency of simultaneous machining, to predict the machining accuracy within the specified conditions.

Distributed Kalman filter for UWB/INS integrated pedestrian localization under colored measurement noise

Colored Measurement Noise (CMN) has a great impact on the accuracy of human localization in indoor environments with Inertial Navigation System (INS) integrated with Ultra Wide Band (UWB). To mitigate its influence, a distributed Kalman Filter (dKF) is developed for Gauss–Markov CMN with switching Colouredness Factor Matrix (CFM). In the proposed scheme, a data fusion filter employs the difference between the INS- and UWB-based distance measurements. The main filter produces a final optimal estimate of the human position by fusing the estimates from local filters. The effect of CMN is overcome by using measurement differencing of noisy observations. The tests show that the proposed dKF developed for CMN with CFM can reduce the localization error compared to the original dKF, and thus effectively improve the localization accuracy.

Tensor-Based DOA Estimation for Array Virtual Translation

In order to make up for the problem that the tensor-based spatial smoothing DOA estimation algorithm cannot make good use of the physical aperture of the array, this paper proposes a tensor-based array virtual translation DOA estimation algorithm. Under the framework of the tensor-based DOA estimation algorithm, the algorithm applies the array virtual translation technique to the factor matrix obtained after tensor decomposition, which can be expanded into signal subspace and approximately has a Vandermonde structure. Furthermore, the available array aperture of the algorithm is expanded, the estimation accuracy is improved, and the limitation of the physical array aperture on the algorithm’s multi-target estimation ability is broken. Since the processing technique proposed in this paper has nothing to do with the construction of tensors, this technique is suitable for all DOA estimation algorithms based on tensors. Theoretical analysis and numerical simulation verify the effectiveness of the algorithm proposed in this paper.

Probabilistic Non-Negative Matrix Factorization with Binary Components

Non-negative matrix factorization is used to find a basic matrix and a weight matrix to approximate the non-negative matrix. It has proven to be a powerful low-rank decomposition technique for non-negative multivariate data. However, its performance largely depends on the assumption of a fixed number of features. This work proposes a new probabilistic non-negative matrix factorization which factorizes a non-negative matrix into a low-rank factor matrix with constraints and a non-negative weight matrix. In order to automatically learn the potential binary features and feature number, a deterministic Indian buffet process variational inference is introduced to obtain the binary factor matrix. Further, the weight matrix is set to satisfy the exponential prior. To obtain the real posterior distribution of the two factor matrices, a variational Bayesian exponential Gaussian inference model is established. The comparative experiments on the synthetic and real-world datasets show the efficacy of the proposed method.

Analisis Strategi Marketing dan Daya Saing Organisasi di Balai Diklat Tambang Bawah Tanah

The Organization of Underground Mining Training Center (BDTBT) which operates in the field of training services requires a strategy to maintain its survival. Competition between organizations is also getting tougher in this era. This condition requires an organization to have a good strategy. BDTBT which focuses on underground mining, makes this organization limited in its market share. The purpose of this study is to determine the current position of BDTBT and obtain organizational strategies that can be implemented properly in BDTBT. In an effort to get a good strategy, it takes a method that is able to beapplied properly in this organization. Data collection was carried out through a questionnaire. Data processing is done through the input process through the SWOT matrix, then evaluation of the internal factor matrix and external factors. With Ifas and Efas scores, the determination of strategies that must be carried out by BDTBT can be done. ABSTRAKOrganisasi Balai Diklat Tambang Bawah Tanah (BDTBT) yang bergerak di bidang jasa training membutuhkan strategi untuk mempertahankan keberlangsungan hidupnya. Persaingan antar organisasi juga semakin ketat di era sekarang ini. Kondisi ini mengharuskan sebuah organisasi memiliki strategi yang baik. BDTBT yang fokus pada tambang bawah tanah, membuat organisasi ini terbatas pangsa pasarnya. Tujuan penelitian ini adalah untuk mengetahui posisi BDTBT saat ini dan mendapatkan strategiorganisasi yang dapat diimplementasikan dengan baik di BDTBT. Dalam upaya mendapatkan strategi yang baik, dibutuhkan metode yang mampu diterapkan secara baik diorganisasi ini. Pengumpulan data dilakukan melalui kuesioner. Pengolahan data dilakukan melalui proses input melalui matrik SWOT, kemudian evaluasi matrik internal faktor dan ekternal faktor. Dengan score Ifas dan Efas maka penentuan strategi yang harus dilakukan oleh BDTBT dapat dilakukan.

Perbandingan Metode AHP dan Metode SAW Dalam Kelayakan Pemberian Kredit Motor

In this study, two methods were used to determine the feasibility of giving motorbike credit, namely the Analytical Hierarchy Process (AHP) and the Simple Additive Weighting (SAW) method to determine the weight of the accuracy value in the feasibility of granting motor loans. Results based on the Hierarchical Weighted Factor Matrix with AHP for all criteria normalized hierarchical weighting for all criteria with the elements in each column divided by the total number in the respective column, then you will get the normalized relative weight. The eigenvector value generated from the average relative weight value for each row shows that the most important criterion for customers who wish to apply for credit. Income with a weight of 0.649 or 64.9%, then followed by a family card with a weight of 0.088 or 8.8%, and domicile is 0.21 or 21%. Whereas the results based on ranking using the SAW method for all Kritera whose weighting is normalized is that the V1 ranking is the first rank because it has a value greater than the other values of 1.03 where V1 is the preference value of alternative A1, so that A1 in this case is Yogi Danuarta who be the best alternative or selected prospective customers to get motorbike loans.

Modélisation mathématique du séchage dans un four (air chaud) de tranches de mangue (Mangiféra indica L.)

Ce travail vise à étudier le séchage de la mangue à différentes épaisseurs et températures en vue de valorisation. Les expériences ont été menées à partir d’une matrice factorielle par la méthode gravimétrique statique. Les valeurs expérimentales ont été ajustées à huit modèles empiriques par la méthode du gradient afin d’estimer les paramètres et coefficients des modèles. Les critères statistiques que sont le R², l’erreur quadratique moyenne (EQM) et le χ² ont servi à justifier le choix du modèle de séchage. Le séchage a duré 16-18 ; 23-27 et 29-33 minutes respectivement aux températures 60, 50 et 40°C pour les épaisseurs 1,5 et 1 cm. Le modèle logarithmique est retenu et présente les valeurs du R² (0,9984 ; 0,9984 ; 0,9981 ; 0,9987 ; 0,9988 ; 0,9985) les plus élevées et les plus faibles valeurs de χ² (2,43 e-07 ; 1,58 e-07 ; 1,25 e-06 ; 2,02 e-07 ; 4,56 e-06 et 1,37 e-06) et EQM (2,42 e-04 ; 1,95 e-07 ; 5,47 e-04 ; 2,20 e-04 ; 0,0010 et 5,69 e-04). Le coefficient de diffusion varie de 8,615 e-09 à 9,155 e-09 m² / s et dépend fortement de la température de séchage. L’énergie d’activation est estimée entre 22,430 – 25,358 KJ / mol.Mots clés : Séchage, mangue, modèle, coefficient de diffusion, énergie d’activation. English Title: Mathematical modeling of the drying in an oven (hot air) of slices of mango (Mangifera indica L.)This work aims to study the drying of mango at different thicknesses and temperatures a view to valorization. The experiments were carried out from a factor matrix by the static gravimetric method. The experimental values were fitted to eight empirical models by the gradient method in order to estimate the parameters and coefficients of the models. The statistical criteria of R², mean square error (MSE) and χ² were used to justify the choice of the drying model. Drying lasted 16-18; 23-27 and 29-33 minutes respectively at temperatures 60, 50 and 40 °C for thicknesses 1.5 and 1 cm. The logarithmic model is retained and presents the highest values of R² (0.9984; 0.9984; 0.9981; 0.9987; 0.9988; 0.9985) and the lowest values of χ² (2.43 e-07; 1.58 e-07; 1.25 e-06; 2.02 e-07; 4.56 e-06 and 1.37 e-06) and MSE (2.42 e-04; 1.95 e-07; 5.47 e-04; 2.20 e-04; 0.0010 and 5.69 e-04). The diffusion coefficient varies from 8.615 e-09 to 9.155 e-09 m² / s and strongly depends on the drying temperature. The activation energy is estimated to be 22.430 - 25.358 KJ / mol.Keywords : Drying, mango, models, diffusion coefficient, activation energy.

Artificial Neural Networks in Radiation Heat Transfer Analysis

In the Monte Carlo ray-trace (MCRT) method, millions of rays are emitted and traced throughout an enclosure following the laws of geometrical optics. Each ray represents the path of a discrete quantum of energy emitted from surface element i and eventually absorbed by surface element j. The distribution of rays absorbed by the n surface elements making up the enclosure is interpreted in terms of a radiation distribution factor matrix whose elements represent the probability that energy emitted by element i will be absorbed by element j. Once obtained, the distribution factor matrix may be used to compute the net heat flux distribution on the walls of an enclosure corresponding to a specified surface temperature distribution. It is computationally very expensive to obtain high accuracy in the heat transfer calculation when high spatial resolution is required. This is especially true if a manifold of emissivities is to be considered in a parametric study in which each value of surface emissivity requires a new ray-trace to determine the corresponding distribution factor matrix. Artificial neural networks (ANNs) offer an alternative approach whose computational cost is greatly inferior to that of the traditional MCRT method. Significant computational efficiency is realized by eliminating the need to perform a new ray trace for each value of emissivity. The current contribution introduces and demonstrates through case studies estimation of radiation distribution factor matrices using ANNs and their subsequent use in radiation heat transfer calculations.