Tehran University of Medical Sciences Journal of Food Safety and Hygiene 2476-3241 4 1/2 2019 03 30 27 40 Malek Hassanpour Department of Environmental science, UCS, Osmania University, Telangana State, India 2018 10 04 2019 02 16 Clustering is a recognized data mining practice, which comprises the devising of a set of objects into a suitable classification of compatible cases. Current cluster study of Iranian food manufacturing industries encompassed food manufacturing and processing practices regarding the number of employees, energy consumed, input and output materials streams, flow-diagram of processes and also the land area used individually. It was used SPSS Software along with Delphi Fuzzy set theory (incorporated with simple additive weighting) to classify about 57 Food Manufacturing and Processing Industries (FMPI) as a hierarchical cluster. According to the t-test analysis, there is no significant difference among 57 FMPI and their criteria such as employees, power, water, land, and fuel. The obtained results were revealed the ranks values (weights) around 2.17, 3.95, 1.64, 2.26 and 4.98 for employees, power, water, fuel, and land criteria extracted from both Kendall's W and Friedman tests respectively. Also, it was found values around 180.749 and 0.793 for Chi-square and Kendall's Coefficient of Concordance in the Friedman and Kendall's W tests respectively. Mean Cronbach's Alpha based on the mean Eigenvalue was acquired about α=1. Pearson correlation analysis had shown the highest correlation between both factors of land and employees about 0.798. Finally, a hierarchical cluster classification was developed for the 57 FMPI. https://jfsh.tums.ac.ir/index.php/jfsh/article/view/142 https://jfsh.tums.ac.ir/index.php/jfsh/article/download/142/88