Planilhas desenvolvidas para o artigo intitulado “Application of data reconciliation in a water balance as a tool for optimizing water use at a university in Brazil”. Ele foi submetido no 26th IJCIEOM – International Joint Conference on Industrial Engineering and Operations Management; 1. Na planilha “Database_IJCIEOM_2020” estão todos os dados usados na pesquisa. 2. A planilha denominada “Coverage test” refere-se ao teste estatistico feito com a media dos blocos MT e FS. 3. Em “IJCIEOM_2020.MT” e “IJCIEOM_2020.FS” encontra-se o desenvolvimento da incerteza das medições de vazão de água do CJA-UFSB. 4. As planilhas “nhemu_seiqué.MT” e “nhemu_seiqué.FS” são usadas no programa de KALID (2020). Para rodar no programa é necessário renomear para “nhemu_seiqué”. English: Spreadsheets developed for the article entitled “Application of data reconciliation in a water balance as a tool for optimizing water use at a university in Brazil”. He was submitted to the 26th IJCIEOM - International Joint Conference on Industrial Engineering and Operations Management; 1. In the spreadsheet “Database_IJCIEOM_2020” are all the data used in the research. 2. The spreadsheet called “Coverage test” refers to the statistical test done with the average of blocks MT and FS. 3. In “IJCIEOM_2020.MT” and “IJCIEOM_2020.FS” there is the development of the uncertainty of water flow measurements from CJA-UFSB. 4. The spreadsheets “nhemu_seiqué.MT” and “nhemu_seiqué.FS” are used in the KALID program (2020). To run the program it is necessary to rename it to “nhemu_seiqué”.

Article summary: This work proposes a data reconciliation (DR)-linked water balance at the Jorge Amado campus (CJA) of the Federal University of Southern Bahia (UFSB), located in the municipality of Itabuna, Bahia, Brazil. Thus, it is intended to support future policies to reduce water use at the university, as well as the establishment of strategies for continuous improvement and process control. To that end, this article maps, quantifies and qualifies water flows, taking into account measurement uncertainties, so that reconciliation can take place efficiently. As a result, inadequacies in the system were identified, such as the existence of under-measurement, the possibility of leaks or misuse of water in the institution. In addition, a more reliable mass balance was established, reducing system uncertainty and closing existing imbalances attesting the effectiveness of DR in the system. Finally, the statistical evaluation of the data reconciliation residue is detailed and ways of continuing the research are proposed.