*3.1.2 Data availability*

*Maintenance Management*

**3. Methodology**

experts error weekly for 1 year.

*3.1.1 System availability*

**3.1 Introduction of measured variables**

system will get out of order when it is needed [14–24].

model has a complex solution. (2) Simple analytic modeling can often be solved simply and obtains an exciting result. (3) The results of analytical modeling are much better than the previous two measurements, which can be predicted.

The disadvantages of fuzzy inference systems and neural networks are the reason why the neuro-fuzzy systems appeared, retaining the advantages of both methods and outweighing the disadvantages. The lack of fuzzy inference systems is solved by creating the knowledge about a problem from the neural inference system training data, while the complicated and hard-to-understand rules of neural networks are bypassed by using linguistic variables by means of which results are easily explained. A well-known neuro-fuzzy system is the adaptive neuro-fuzzy inference system (ANFIS) used in solving various problems. The fuzzy inference system of Sugeno type can be considered as an adaptive neuro-fuzzy inference system in the form similar to neural networks in which by training the system on input/output data set, the parameters of the fuzzy inference membership functions or antecedent parameters and the parameters of the Sugeno fuzzy system output function or

According to the research type, data and research variables from the automation system of one of the state-run companies have been collected over several successive years for evaluating the services and the percentage of estimated costs in the maintenance area. These data are used first to determine the parameters of information technology services and then to the cost variables. This modeling sample is selected with experimental data as the representative of the total available data and allows us to generalize the simulation results to the whole model. The results of this research can be used to develop organizational monitoring systems. Data and information collected by using libraries, databases, the Internet, published article in conferences, scientific and research journals related to information technology systems, interviews with experts of the department of automation maintenance of the organization, observation factors influencing their measurement, the historical data collection of the organization, as well as the information were obtained by the

Accessibility is defined as the probability that a system works desirable at any random point of time. In order to make the system always available, various factors make the system out of accessibility, which can be measured the percentage of availability including the definitive system failure with planned reasons, and the other sudden system failure. The downtime of the system should be lowered, or the

Measuring system availability is a growing process that evaluates the behavior of computer systems and the increasing dependence of organizations on the frequent use of operating systems and the emphasis on the design of tolerance. In this study, the measurement of the availability of hardware and software and their effect on

**2.6 Adaptive neuro-fuzzy inference system (ANFIS)**

consequent parameters (pi, qi i ri) are adapted [13].

**106**

The purpose of this variable is how data is available when stored in a particular way. It is often referred as storage resource through remote storage media. The speed of user's accessibility to the data and its access level in this variable are evaluated. The storage area network (SAN) is a network of external systems that communicates with the data source and network-attached storage (NAS) that stores data through the connection to the data network. Many factors are considered in this variable, including available bandwidth, security and availability level, file system type and access level, hardware and software storage type, and AST assigned to the system administrator. In this model, four effective indicators have been evaluated to measure the availability of data in the event of a malfunction and failure of the service.
