Elements of mathematical reliability theory
Course: Applied Mathematics
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Elements of mathematical reliability theory
        
    
            Code
        
        
            ДВС.3.06.03.02
        
    
            Module type 
        
        
            Вибіркова дисципліна для ОП
        
    
            Educational cycle
        
        
            First
        
    
            Year of study when the component is delivered
        
        
            2022/2023
        
    
            Semester/trimester when the component is delivered
        
        
            8 Semester
        
    
            Number of ECTS credits allocated
        
        
            3
        
    
            Learning outcomes
        
        
            PLO21.3. Understand the fundamental areas of mathematics and computer science, to the extent necessary for learning mathematical disciplines, applied disciplines and using their methods in a chosen profession.
PLO22.3. Understand the main areas of mathematical logic, theory of algorithms and computational theory, programming theory, probability theory and mathematical statistics.
PLO23.3. Be able to use professional knowledge, skills and abilities in the field of fundamental sections of mathematics and computer science for research of real processes of different nature.
PLO24.3. Be able to independently analyze the relevant subject area, be able to develop mathematical and structural algorithmic models.
        
    
            Form of study
        
        
            Prerequisites and co-requisites
        
        
            To successfully learn the discipline “Elements of mathematical reliability theory” the student should satisfy the following requirements. 
They know (a) fundamentals  of mathematical methods for construction, verification and investigation of qualitative characteristics of deterministic and stochastic mathematical models; (b) classical methods of Calculus, Algebra and Probability Theory.
They can (a) investigate qualitative characteristics of available mathematical models; (b) apply classical methods for solving applied problems in deterministic and stochastic models.
They should be able to (a) apply classical methods of Calculus and Probability Theory; (b) seek information in open sources and properly analyze it. 
        
    
            Course content
        
        
            Poisson flow. Characteristic property of exponential distribution. 
The main characteristics of reliability. Recovery processes and their application in reliability theory. Alternating processes. Statistical estimates for reliability test plans of type [N, B, R], [N, B, T]. Method of simulation modeling in reliability theory.
Reliability of systems with independent elements. Scheme of death and reproduction and its application in the theory of reliability. Backup systems without recovery. Duplicate with recovery. General redundant system with recovery. 
        
    
            Recommended or required reading and other learning resources/tools
        
        
                        1.  Gnedenko  B.V.,Ushakov  I.A. Probabilistic mеtods  in reliability,   New York,    Wiley, 1995.  - 515 p.
2. Gnedenko B. V., Belyayev Yu. K., Solovyev A. D., Mathematical Methods of Reliability Theory, Academic Press, 1969. -471 p.
3.  Barlow R.E., Proschan F., Stistical theory of Reliabiluty and life testing probability models, Holt, Rinehart and Winston, Inc., 2008.  -328 p.
4.  Томаschevsky V.М.  Моdelyuvanya  system. Кyiv: BHV, 2005.  .  -352 p.
            5. Law A.M., Kelton W.D. Simulation  modeling and analysis, Osborne, 2001. -  848 p.
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, seminars, consultations, test works, independent work. 
        
    
            Assessment methods and criteria
        
        
            Intermediate assesement:
Maximum number of points that can be obtained by a student: 100 points:
1. Test No1: 30/18 points.
2. Test No 2: 30/18 points.
3. Test No 3: 40/24 points.
Final assessment (in the form of test):
Not provided
        
    
            Language of instruction
        
        
            Ukrainian
        
    Lecturers
This discipline is taught by the following teachers
                    Ivan 
                    K.
                    Matsak 
                
                
                    Operations Research  
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
                        Operations Research 
                    
                    
                        Faculty of Computer Science and Cybernetics