APPLICATION OF OFFICE INFORMATION TECHNOLOGIES TO SOLVE THE PROBLEMS OF OPTIMAL STRUCTURAL RESERVATION OF SYSTEMS

Problem statement. The problems of optimal structural redundancy of systems are usually formulated as a nonlinear problem of mathematical programming with integer variables, and to solve them, usually, various optimization methods are used, which requires the development of special algorithms and appropriate software. However, in the case of clarifying the original task of optimal redundancy, there is often a need to adjust the developed algorithms and software. All this greatly complicates obtaining the desired results. Another approach to solving problems of optimal redundancy of systems is the use of office information technology, the tool environment of which is adapted to solve mathematical problems, including optimization problems. This approach does not require the development of special algorithms and software. However, issues related to the effectiveness of the information technology used to solve this problem require further scientific and practical study. This article formulates a model of optimal design of redundant systems according to the criterion of minimum cost while ensuring the required level of reliability during a given time. This model is written in terms of a nonlinear problem of mathematical programming with integer variables and is numerically implemented in the operating environment of an Excel spreadsheet when the main object of the designed system consists of 6 elements. The optimal options for reserving this object according to the schemes of "hot" and "cold" redundancy are obtained. The purpose of the article is to show the effectiveness and efficiency of the MS Excel spreadsheet to solve problems of optimal structural redundancy of systems. Conclusions. This article discusses issues related to the problem of solving problems of optimal design of redundant systems in the tool environment of the MS Excel spreadsheet. Examples of solving the problems of separate "hot" and separate "cold" redundancy of a 6-element object prove the effectiveness and efficiency of the MS Excel spreadsheet to solve this problem. In addition, the developed optimization model can be successfully used in practical tasks to ensure the reliability of technical systems in the early stages of their design.

Optimal adaptive inspection and maintenance for redundant systems

Optimal exploration of engineering systems can be guided by the principle of Value of Information (VoI), which accounts for the topological important of components, their reliability and the management costs. For series systems, in most cases higher inspection priority should be given to unreliable components. For redundant systems such as parallel systems, analysis of one-shot decision problems shows that higher inspection priority should be given to more reliable components. This paper investigates the optimal exploration of redundant systems in long-term decision making with sequential inspection and repairing. When the expected, cumulated, discounted cost is considered, it may become more efficient to give higher inspection priority to less reliable components, in order to preserve system redundancy. To investigate this problem, we develop a Partially Observable Markov Decision Process (POMDP) framework for sequential inspection and maintenance of redundant systems, where the VoI analysis is embedded in the optimal selection of exploratory actions. We investigate the use of alternative approximate POMDP solvers for parallel and more general systems, compare their computation complexities and performance, and show how the inspection priorities depend on the economic discount factor, the degradation rate, the inspection precision, and the repair cost.