## 3 Materials and Methods
### Process Description  
Failure reports contain data describing the actual effects and causes of a technical facility failure. The failure report is initiated by the operator describing the consequences of the technical object's failure event, thus performing fault detection. On this basis, the technician carries out the remaining phases of the diagnosis of the technical object's condition--fault location and identification. Once the component that caused the failure has been located, the genesis of the technical condition is performed, determining its cause. Description of Maintenance department operation:  
* Notification in the computer system by the operator: location of the failure (department, line, segment, e.g., WP1, LP01 101, gluing machine 1 LP01), type of failure (e.g., adjustment), category (e.g., urgent), type (mechanical), description of the notification (e.g., failure of the crawler die);
* Report is displayed on a monitor in the UR workshop (if mechanical, in the mechanics' workshop, if electrical, in the electricians' workshop, if other, in both) -> for urgent malfunctions additionally a \"rooster\" is switched on;* Technician approaches the breakdown station and performs the diagnosis (often there are mistakes in the notification, i.e., not a mechanical breakdown but an electrical breakdown--in such a case, technicians are exchanged, which takes a lot of time);
* Repair is carried out, i.e., in-house or service is called, or they wait for parts, etc. ;
* Once the fault has been rectified, the technician enters the repair information into the system. An important element of the failure report is the technician's action time and failure diagnosis time, as well as the estimated time to fix the failure. The time for the technician to take action and the time for fault diagnosis are directly linked to the operator's report, and in particular to the technical facility operator's initial assessment of the consequences (and causes) of the fault. Ninety percent of reports relate to mechanical or electrical faults, so the referral of a technician with the required competence to the emergency event is crucial to minimize fault diagnosis time. It can be deduced from the CMMS data that technicians could not perform their work efficiently due to a lack of spare parts, materials and tools. The decrease in efficiency was also caused by waiting for external service or the need to involve technicians in other emergency events--crucial from the production point of view, i.e., the handling of the failure of one event was interrupted due to the occurrence of another emergency event of higher priority. These data indicate mismanagement of the resources required to deal with failures, resulting in specific losses. Eliminating these losses should significantly improve the availability and performance of technical facilities. In the first step of the activities, the critical causes and consequences of failure events were identified in the analysis and compared with the empirical data on failure events of the technical facilities under study. On this basis, the records contained in the database were verified, and input and output sheets for the neural networks were developed. The assumptions were as follows:  
* Inferring the type of failure i.e., indicating that it is a mechanical failure;
* Inference of possible actions to be taken--the technician with the most experience will be delegated. As a further development, it is possible (this will enable a more complete analysis) to assign data on the basis of descriptions in a separate field distinguishing the type of intervention: repair, adjustment, calibration and external service. The developed results of the analysis of emergency events are subject to a describable level of uncertainty due to the form of description of emergency notifications and work performed in the CMMS. In the absence of a defined dictionary of entries, it happens that the same failures are described in different ways.