## 4 Conclusions  
The conducted research shows that the condition of a complex technical system can be adequately represented by a numerical value, or an ordered set of values, that represents a qualitative assessment of the system condition and that an insight into the system state can be gained on this assessment. The development of this proposed model of maintenance by condition assessment requires the previous experience of experts and maintainers, certain elements of which are incorporated into the proposed methods and procedures. The proposed model can be easily adapted to be used in plants of another technical and technological framework. The first step in the maintenance model for technical systems is to decompose the system and determine the parameters essential for the proper operation of a particular plant by evaluating its condition. Decomposition is followed by the measurement of the physical quantities, inspection and data acquisition by the installed measuring devices. The aggregation procedure is carried out based on an improved evidential reasoning algorithm, which is a way to objectively consider the weights of each baseline attribute, its influence on the general attributes, the overall assessment and the uncertainty of the input assessment itself. After the aggregation procedure, the final evaluation of the state of the observed object is obtained, which is represented as a probability distribution of all input evaluations. This type of representation is quite complex, so for mutual comparison of the condition of the observed object, the final score, represented by a numerical value, and the dispersion interval of the final score are used. The improved evidential reasoning algorithm can adequately deal with incomplete information about a baseline or general attributes. This is an important feature that provides an insight into the impact of incomplete knowledge of information related to the baseline attributes on the overall uncertainty in the evaluation of the entire technical system. The result of the condition assessment can be displayed as a single numerical value with an interval between the minimum and maximum values, rather than an assessment spread over several predefined grades. Such a numerical value allows an easy insight into the system state and the comparison of the state of the observed system with other similar systems or with the state of the same technical system at another time. Special attention must be paid to the correct interpretation of the physical quantities obtained from the measurements of the system parameters. It is necessary to adequately process the collected quantitative information and translate it into the qualitative domain. This information is ranked and used as input to the aggregation process. If the information collection and condition assessment are done continuously or at regular time intervals, sufficient information is available to represent the state of the observed object as a function of time. Based on the analysis of such a time function, it is possible to make decisions regarding maintenance. In cases where the state of the technical system is described with the help of a time function and a suitable knowledge base, it is possible to predict situations suitable for faults. This significantly reduces the possibility of malfunctions with serious consequences for the condition of the system. The lower limit of the system condition, at which intervention is not yet required but preparation for maintenance of the system should be started, is rated as \"sufficient\", i.e. when the overall system rating drops or approaches the predefined lower value, preparations for maintenance of the components with the worst condition must be started and maintenance performed before the system rating drops to the unsatisfactory value, i.e. before the overall system rating drops below the allowable critical low value.