**8. Further research**

98 Multivariate Analysis in Management, Engineering and the Sciences

data and that can be an indicator of problems with the rods.

would no longer be indicated.

belong to a same cluster.

that deserves greater attention.

one, identifying the effects of summer.

of summer.

would increase with the aid of a specialist for a better interpretation of the results. This specialist would detect that cluster 1, for example, is formed by rods that are extremely important for the monitoring of dams, and that all rods from this cluster should be automated. This type of analysis was not found in literatures, for this reason the contribution of this study is relevant. It is recommended that this Analysis (process of hierarquization) is repeated periodically (according to the needs indicated by the specialists in this field – in this case, by the engineers' team of Itaipu) what could be done, for example, every two years. This can show the appearance of new rods that are indicated by the performing of readings intensification (that should be investigated), the same could occur with rods that

When there are rods within the clusters with low communalities, it is recommended that they are investigated. Low communality indicates a high percentage of randomness in the

These identifications of similar rods can also be used in projecting the control values. In this case, the values of control for each rod can be associated to the readings of the rods that

The final factorial score performs the hierachization of the attributes. In this case the patterns are vectors of which the components (attributes) are the readings of the rods of the extensometers in a certain month. Therefore, the final factorial score performs the hierachization of the months showing whether there is any month that is rather relevant and

Table 4 shows the first 15 months with a higher final factorial score and the last 15 months with lower final factorial scores, considering the 72 rods of extensometers. The values of the 15 first months with a higher final factorial score reveal that all the months are important; there is no month that is rather relevant. Only the month of December does not appear in the first 15 months. Notice that 1995 was the most relevant year and in analyzing the ambient temperature during the period of study it was possible to verify that this occurred due to the high temperature variation. The values of the last 15 months with least final factorial scores revealed that the months of April, May, and June are the most important

As mentioned, cluster 1 shows the effect winter/summer in its readings. For this reason the final factorial score was calculated in order to perform a ranking of the months for cluster 1,

The first 15 months with a higher final factorial score and the last 15 months with least final factorial scores were observed considering only the 11 rods of the extensometer of cluster 1. The values of the 15 first months with higher final factorial scores reveal that the months of September, October, and November are the most relevant ones, identifying the effects of winter. The values of the last 15 months with least final factorial score reveal that the months of March, April, May and June are the most important ones, identifying the effects

to show whether there is any month or some months with greater relevance.

The application of this methodology is suggested for other instruments and other periods, and the implementation of it in order to define values of control and for anomaly detection. Once the process of ranking is repeated in several periods (every 2 years, for example.) it can show the appearance of new rods which are indicated for performing readings intensification or the appearance of rods that could no longer be indicated (these should be investigated).
