Process control of profile extrusion using thermal method. Part I: Mathematical modeling and system analysis

1988 ◽  
Vol 28 (11) ◽  
pp. 697-707 ◽  
Author(s):  
B. Yang ◽  
L. J. Lee
Keyword(s):  
Mathematical Modeling ◽  
Process Control ◽  
System Analysis ◽  
Thermal Method

scholarly journals The system analysis and mathematical modeling road accidents in the metropolis

2019 ◽  
pp. 4-8
Author(s):  
A. G. Davidovsky ◽  
A. M. Linnik
Keyword(s):  
Mathematical Modeling ◽  
Traffic Safety ◽  
System Analysis ◽  
Safety Management ◽  
Road Traffic ◽  
Time Of Day ◽  
Road Accidents ◽  
Traffic Incidents ◽  
Day Of The Week ◽  
Pedestrian Collisions

The article presents the results of correlation analysis of the causes of road accidents in such a modern metropolis as Minsk. Has been identified the most frequent causes of road accidents, including pedestrian collisions caused by drivers, collisions at intersections, incidents at controlled and unregulated pedestrian crossings, as well as on the roadway. The dependence of transport incidents on the time of day, day of the week and month of the year was investigated. Shows the periods when road traffic incidents occur from 3.00 to 6.00 h, from 15.00 to 18.00 and from 21.00 to 24.00 on Monday, Friday and Sunday in January, March, June, September, October and November. Methods of correlation and multiple regression analysis can be the basis of preventive traffic safety management in a modern metropolis.

System analysis of the assessment of the influence of multiplicative interference on the Conditions signal resolutions based on statistical criteria using mathematical modeling

2020 ◽  
pp. 82-95
Author(s):  
В.И. Воловач
Keyword(s):  
Mathematical Modeling ◽  
Frequency Shift ◽  
Delay Time ◽  
System Analysis ◽  
Statistical Characteristics ◽  
Statistical Criterion ◽  
Multiplicative Interference ◽  
Statistical Criteria

Проведен системный анализ влияния мультипликативных помех на условия разрешения сигналов на основе статистического критерия с помощью математического моделирования. Показано, что интервалы разрешения по времени запаздывания и частотному сдвигу при известных статистических характеристиках сигналов, аддитивных и мультипликативных помех однозначно определяются вероятностями правильного и ложного разрешения. A system analysis of the influence of multiplicative interference on the signal resolution conditions based on a statistical criterion using mathematical modeling is performed. It is shown that the resolution intervals for delay time and frequency shift with known statistical characteristics of signals, additive and multiplicative interference are uniquely determined by the probabilities of correct and false resolution.

Measurement System Analysis Combined with Shewhart’s Approach

2015 ◽  
Vol 637 ◽  
pp. 7-11 ◽  
Author(s):  
Magdalena Diering ◽  
Adam Hamrol ◽  
Agnieszka Kujawińska
Keyword(s):  
Process Control ◽  
Control Chart ◽  
Measurement System ◽  
Manufacturing Process ◽  
Control Charts ◽  
System Analysis ◽  
Standard Procedure ◽  
Reference Value ◽  
Measurement Systems ◽  
On Line

The paper presents new procedure of methodology for statistical assessment of measurement systems variation (methodology known in the literature as Measurement Systems Analysis, MSA). This procedure allows for calculation and monitoring in real time (that is on-line) of measurement system (MS) characteristics which determine its usability for manufacturing process control. The presented solution pointed out the gap in process control, which consists in lack of methods for monitoring measurement processes in the on-line way. Their key point consists of taking samples that are also needed for the process control chart for the needs of the MSA method. This means that the samples are taken directly from the production line and during the production process. The method is combined with the standard procedure of statistical process control (SPC) with the use of process control charts. It is based on two control charts. The first one is called AD-chart (Average Difference chart) and it allows to estimate the variation between the operators and stability of the monitored measurement system. The second control chart illustrates the %R&R index (Repeatability and Reproducibility) and allows to monitor the MS capability.The paper also presents authors’ proposal of guidelines about the reference value for the %R&R index calculation and assessment. Recommendations and guidelines for choosing the reference value are based on two criteria: information about sample and manufacturing process variation and the purpose of using MS (product or process control).

scholarly journals ECONOMIC AND STATISTICAL ANALYSIS OF FARMERS' ACTIVITY

2018 ◽  
pp. 287-294
Author(s):  
Natalia Ruchynska
Keyword(s):  
Mathematical Modeling ◽  
Statistical Analysis ◽  
System Analysis ◽  
Production Costs ◽  
Mathematical Methods ◽  
Index Method ◽  
Managerial Decisions ◽  
Scientific Approach ◽  
Factor Estimation

Introduction. Improvement of the process of making managerial decisions and, accordingly, improvement of the quality of the decisions made is achieved through the use of scientific approach, models and methods of decision-making. Methods of economic and mathematical modeling allow to solve a number of issues related to the development of alternative areas of activity, optimization of the structure, production costs and sales of farm products. Therefore, it is expedient to use them for making managerial decisions at farms. Purpose. The article aims to carry out the economic and statistical analysis of the activity of the farm and the feasibility of applying economic and mathematical methods in the process of managing farms in modern conditions of farming. The application of economic and mathematical methods and models for making managerial decisions is considered on the example of the activity of the farm "Horizon" of the Veselinovsky district of the Mykolaiv region, which specializes in the cultivation of grain crops (except rice), legumes and seeds of oilseeds. Methods. In the course of the study, methods of system analysis, index method of factor estimation, and economic and mathematical modeling have been used. Results. On the basis of economic indicators of the activity of the farm "Horizon" during the reporting period, the economic and mathematical model of optimization of sown areas has been created. It contributes to the correction of managerial decisions for improving the efficiency of economic activity.

scholarly journals Mathematical modeling of processes of interaction of functional and which contaminate microorganisms in biotechnology system

2019 ◽  
Vol 81 (1) ◽  
pp. 252-255
Author(s):  
A. V. Skrypnikov ◽  
E. V. Belokurova ◽  
N. V. Sotnikov
Keyword(s):  
Mathematical Modeling ◽  
System Analysis ◽  
System Model ◽  
Microbial Populations ◽  
Simultaneous Occurrence ◽  
Technological Parameters ◽  
Microbiological Processes ◽  
Microbiological Process ◽  
Common Resource

Mathematical modeling of processes occurring in the biotechnological system, including those describing the interaction of functional microorganisms with contaminating microflora, is currently a promising scientific direction. The article discusses the issues of system analysis of the processes occurring in the biotechnological system during fermentation. By "microbiological system" is meant a microbiological process consisting of two subsystems or populations of microorganisms. During a given technological process, these populations interact with each other by using a common resource. Systems analysis and mathematical modeling of microbiological processes is a complex task. It is necessary to take into account a lot of factors, such as the simultaneous occurrence of several non-stationary processes; many state parameters, including analysis of the links between them; change in real time of technological parameters, in particular, the main resource, consideration of various properties of microbial populations affecting the behavior of microbiological systems (mortality, fertility, the existence of extraneous microflora, etc.), and other factors that have a direct impact on the quality of the finished product. In turn, a quantitative analysis of these interactions will lead to the development of scientifically based methods and approaches that minimize the effect of contamination. The analysis was carried out and a system model was constructed reflecting the entire spectrum of interactions between useful and extraneous populations of microorganisms in the production of bakery products. The presented system model allows to continue the study of the questions posed in the work, by further studying its components.

scholarly journals Mathematical modeling of a strain gauge measurement system in MATLAB SIMULINK program

2020 ◽  
Vol 6 (2) ◽  
pp. 85-93
Author(s):  
Timur A. Raianov
Keyword(s):  
Mathematical Modeling ◽  
Measurement System ◽  
Strain Gauge ◽  
System Analysis ◽  
Force Measurement ◽  
Operating Conditions ◽  
Matlab Simulink ◽  
Software Model ◽  
Output Characteristics ◽  
Gauge Measurement

Background: In recent years, modern strain gauge systems for measuring, which are used in automobile, railway, aviation, and ship transport, as well as in the pulp, paper, and metallurgical industries, have become extremely popular. These metrological systems provide accurate measurement in difficult operating conditions. The most popular among sensors are strain gauges, they are increasingly used in various areas of marine operations and legal proceedings. They are the optimal solution in the field of torque measurement. Aim: The program creates a model of a strain gauge measurement system. Analysis of power output characteristics. Methods: The article describes the construction of a mathematical model of the strain gauge measurement system. The MATLAB SIMULINK library was used for simulation. The work is based on mathematical modeling and is aimed at creating a computer-based strain gauge model. The output characteristics are analyzed. The accuracy of the software model measurement was verified by checking the convergence of the actual and measured values. Results: A software model of the strain gauge force measurement system was created to create a real computer strain gauge measurement system. Output characteristics are obtained. Conclusions: A software model of the strain gauge measurement system is proposed; The output characteristics were studied and the measurement accuracy was checked.

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