The availability assessment of machines in mines is of high importance, as it allows to plan their maintenance and to provide a continuous flux in the optimum exploitation of those mines.

This paper presents a method of availability estimation using the experts' opinion, but minimising the subjectivity of human factor by fuzzy inference, and the Analytic Hierarchy Process (AHP) ranking method. A case study of machinery working in EPS (Electric Power Industry of Serbia) mines is provided.

The paper retake the subject presented in a previously published paper of the authors in the same journal (Energies, doi: 10.3390/en12122245, reference [16] in current paper), applying the same AHP theory. From here most of equations are repeated in the present paper. Nevertheless, I consider this paper as useful for availability prediction of machinery. The presented case study is a novelty.

The article could be improved and I have some suggestions and questions for the authors. grouped in 6 points of minor revision.

1. Most of cited references (about ten) were published or presented by the same authors. The novelty of the current research must be emphasized in Introduction section, with respect to all previously published paper, especially to the cited reference [16].

2. Line 264-265 and equation (19) are in contradiction, as eq. (19) computes a mean value of λ.

3. How did you established Random Consistency Index values from Table 2? There is any mathematical equation?

4. Line 153: please define the supportability S.

5. "A" is denoted twice, as availability and also as the first linguistic variable. From here, some confusions could appear in equation (15). This point should be amended.

6. Please check some possible minor errors: line 102, t22 is t232; line 220: wrong reference to equation 15; line 318: achine=machine.