Contribution to the development of the method of forecasting the frequency and duration of "failure" of technical systems

An active approach to the market means the full adaptation of the production system to the demands of the consumers, and the high profitability. To realize the above, production system should create the conditions for the simulation of the behavior of the system in real conditions. In the opposite the behavior of the system will be highly uncertain because of the disturbance in the system. The simulation of the behavior of the system in real conditions includes the existence of reliable information, obtained based on previous research. A series of such information also includes the information on the production cycle of a series of products. The components of the production cycle are also different disturbances. This paper analyses the failures of the technical system. This fact points to the significance of creating the conditions for forecasting the frequency and duration of the "failure". This paper, based on research of two formatisers, presents the methodology of carrying out the forecasting in real conditions

Simulation of primary log cutting plan (PPRT) in sawmill wood processing

A specification of sawn timber is realized based on the previously designed log cutting plan, primary and secondary. The plan of primary log cutting (PPRT) has its verbal and mathematical interpretations. The theoretical aspect of PPRT design reported in the literature has great disadvantages. As it is based on the description and empirical combinations, such PPRT could hardly be evaluated as optimal. In addition to the above weakness, there is another one, i.e., the fact that the problem of PPRT design is reduced to a mono-criterion problem, i.e. the minimisation of total waste. If the problem of PPRT design is approached systematically, it is clear that the minimisation of total waste is only one out of a series of goals that a PPRT should fulfil. Nevertheless, the procedure presented in the literature is deeply rooted in practice. This paper, based on the on simulation principle, presents a modern procedure of PPRT design which consists of a number of phases. The first phase includes computer support in the design procedure of log cutting plans and also, a mono-criterion decision making in the selection of log cutting plans which ensure the minimal total waste per PPRT. The second phase includes the definition of another two criteria which are decisive for the optimal quality of PPRT. They are the log prices and the profit. Altogether 84 (eighty-four) cutting plans were designed and 4 (four) PPRTs. The solution of the problem, i.e. the design of an optimal PPRT in the conditions of three criteria, is based on multicriteria decision making using the method of Analytical Hierarchy Processes - AHP. The calculation is computed by the software Program Criterion Decision Plus - Version 3.0 Student version, InfoHarvest.Inc. In the study simulation of PPRT design, the optimal plan was PPRT3. The presented three criteria are not the final number. The inclusion of additional relevant criteria will depend on the inventiveness of the manager

Forecasting of the processing time as the base of simulation of the production system behavior in real conditions

The absence of precise information on the magnitudes that determine the behavior of the production system generates the disturbances of the system. The consequence is the low efficacy of the system and the high costs. Therefore, it is necessary to create the base for the prediction of individual magnitudes and thus enable the simulation of the production system behavior in real conditions. The information on time norms has a special significance. It is the base of planning the terms and of defining a part of direct costs. Modern approach in the identification of standard times should be established on new foundations. It should appreciate the specificities of the present moment, as well as the future tendencies in wood processing. They are the production system dynamistic, conditioned predominantly by discontinuous production, as well as by the necessity of cooperation of the production systems. In this study, the approach to the identification of standard times is original, supporting the modern tendencies in wood processing and it has an applicative character

Implementation of SMED method in wood processing

The solution of problems in production is mainly tackled by the management based on the hardware component, i.e. by the introduction of work centres of recent generation. In this way, it ensures the continuity of quality reduced consumption of energy, humanization of work, etc. However, the interaction between technical-technological and organizational-economic aspects of production is neglected. This means that the new-generation equipment requires a modern approach to planning, organization, and management of production, as well as to economy of production. Consequently it is very important to ensure the implementation of modern organizational methods in wood processing. This paper deals with the problem of implementation of SMED method (SMED - Single Digit Minute Exchange of Die) in the aim of rationalization of set-up-end-up operations. It is known that in the conditions of discontinuous production, set-up-end-up time is a significant limiting factor in the increase of flexibility of production systems

Cloud Based Metalearning System for Predictive Modeling of Biomedical Data

Rapid growth and storage of biomedical data enabled many opportunities for predictive modeling and improvement of healthcare processes. On the other side analysis of such large amounts of data is a difficult and computationally intensive task for most existing data mining algorithms. This problem is addressed by proposing a cloud based system that integrates metalearning framework for ranking and selection of best predictive algorithms for data at hand and open source big data technologies for analysis of biomedical data

Ecological Analysis of the Dendroflora of Futoški Park in the City of Novi Sad

The purpose of this paper is to analyze the floristic composition, abundance, biological spectrum and ecological effects of Futoški Park trees and shrubs on the basis of bioindicators. The field research was conducted in Futoški Park, which is one of the oldest and largest parks in the City of Novi Sad, covering an area of 81,306 m2. Upon determining the floristic composition of Futoški Park and the protection zone around the Park hotel, a total of 121 genotypes were recorded, out of which 34 species and lower taxa belong to the Gymnosperm phylum (Pinophyta) and 87 species and lower taxa belong to the Angiosperm phylum (Magnoliophyta). A total of 5,228 representatives of dendroflora were found. The biological range of trees and shrubs in the study area mostly includes deciduous nanophanerophytes (34.98%) and evergreen nanophanerophytes (33.72%), whereas the remainder includes evergreen phanerophytes (16.35%) and the least prevalent deciduous phanerophytes (14.94%). The analysis of ecological indices shows that the greatest number of species meet the environmental requirements, and are successfully acclimated to the climatic and soil conditions. On the basis of the overall vitality and ornamental features of the dendroflora analyzed, it can be argued that Futoški Park is a unique ecological and environmental entity in the urban structure of the city

Performance comparison of nonlinear and linear regression algorithms coupled with different attribute selection methods for quantitative structure - retention relationships modelling in micellar liquid chromatography

In micellar liquid chromatography (MLC), the addition of a surfactant to the mobile phase in excess is accompanied by an alteration of its solubilising capacity and a change in the stationary phase’s properties. As an implication, the prediction of the analytes’ retention in MLC mode becomes a challenging task. Mixed Quantitative Structure –Retention Relationships (QSRR) modelling represents a powerful tool for estimating the analytes’ retention. This study compares 48 successfully developed mixed QSRR models with respect to their ability to predict retention of aripiprazole and its five impurities from molecular structures and factors that de- scribe the Brij - acetonitrile system. The development of the models was based on an automatic com- bining of six attribute (feature) selection methods with eight predictive algorithms and the optimiza- tion of hyper-parameters. The feature selection methods included Principal Component Analysis (PCA), Non-negative Matrix Factorization (NMF), ReliefF, Multiple Linear Regression (MLR), Mutual Info and F- Regression. The series of investigated predictive algorithms comprised Linear Regressions (LR), Ridge Re- gression, Lasso Regression, Artificial Neural Networks (ANN), Support Vector Regression (SVR), Random Forest (RF), Gradient Boosted Trees (GBT) and K-Nearest neighbourhood (k-NN). A sufficient amount of data for building the model (78 cases in total) was provided by conducting 13 experiments for each of the 6 analytes and collecting the target responses afterwards. Different experi- mental settings were established by varying the values of the concentration of Brij L23, pH of the aqueous phase and acetonitrile content in the mobile phase according to the Box-Behnken design. In addition to the chromatographic parameters, the pool of independent variables was expanded by 27 molecular de- scriptors from all major groups (physicochemical, quantum chemical, topological and spatial structural descriptors). The best model was chosen by taking into consideration the Root Mean Square Error ( RMSE ) and cross-validation (CV) correlation coefficient ( Q 2 ) values. Interestingly, the comparative analysis indicated that a change in the set of input variables had a minor impact on the performance of the final models. On the other hand, different regression algorithms showed great diversity in the ability to learn patterns conserved in the data. In this regard, testing many regression algorithms is necessary in order to find the most suitable technique for model building. In the specific case, GBT-based models have demonstrated the best ability to predict the retention factor in the MLC mode. Steric factors and dipole-dipole interactions have proven to be relevant to the observed retention behaviour. This study, although being of a smaller scale, is a most promising starting point for comprehensive MLC retention prediction