Modelo multicritério para seleção e avaliação econômica de tecnologias de separação de resíduos lácteos

Abstract

Effluents with high levels of organic load are discharged into water bodies without proper treatment, causing serious environmental problems. The growth of the dairy industry and the increase in the emission of greenhouse gases caused by its waste have been the focus of several studies, which propose alternatives for the use of this waste in the development of various by-products, such as: biofuels, biofertilizers and soil cover. However, there is still a need for the development of models that help in the identification of the best technological alternative and evaluate the added value for the organization. In this context, the general objective of this dissertation was to apply a multi-criteria modelto identify the best dairy fat separation technology and to evaluate the economic viability of implementing this technology, incorporating the project's specificities into the analysis.The methodology used in the development of the technical-economic model for the separation of milk fat was structured in four stages: (i) identification of criteria and technologies for dairy fat separation through a systematic review of the literature; (ii) acquisition of qualitative information (linguistic variables) fromnational and international specialists; (iii) application of the multicriteria linguistic TOPSIS 2-tuple method to classify the technologies; and (iv) economic evaluation of the technology best classified in the previous stage. The proposed model was applied in an agroindustry that produces 3,000 m³/day of waste, with 3% fat. The centrifugal force technology was chosen by both groups of experts, which was submitted to economic feasibility analysis by expanded multi-index methodology (EMIM). Based on the analysis made, it is concluded that the implementation of this technology is economically viable, because it presents a high degree of return (greater than 66.66%), which occurs in the first year of implementation. The project still presents low levels of risks and sensibilities, the latter being above 66.66%. The main contribution of this study was the construction of a multicriteria model to help dairy companies in making decisions about their effluents generated.