A Multi-Criteria Model for the Techno-Economic Evaluation of Fat Removal Technologies From Dairy Waste

• Published in: SAGE open Vol. 13; no. 2
• Main Authors: Bolico Pletsch, Guilherme, Setti, Dalmarino, de Lima, José Donizetti, Adamczuk Oliveira, Gilson, Pimentel, Tatiana Colombo
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.06.2023; SAGE PUBLICATIONS, INC; SAGE Publishing
• Subjects: Dairy industry; dairy waste; investment analysis; 2-tuple; Monte Carlo simulation; expanded multi-index methodology; real options analysis
• ISSN: 2158-2440; 2158-2440
• DOI: 10.1177/21582440231179155

This paper presents a multi-criteria model to identify the best technology for separating fat from dairy waste and evaluates the economic feasibility of its implementation. Also, the model incorporates the analysis of the project specificities. The methodology was structured in four steps: (i) identification of criteria and technologies by systematic literature review; (ii) acquisition of qualitative information (linguistic variables) from Brazilian and international experts; (iii) application of the TOPSIS 2-tuple multi-criteria linguistic method to rank the technologies; and (iv) evaluation of the economic viability of the best technology identified using the EMIM (expanded multi-index methodology). Separation by centrifugal force, solvent, heating/decanting, acid hydrolysis, and combined methods were the separation technologies most used in the literature and, therefore the considered alternatives. The model was validated in a dairy industry that produces 3,000 m3/day of waste, with 3% fat. The performance of the technologies concerning five criteria was between medium poor and good for both groups of experts. Also, the experts indicate centrifugal force as the preferred technology. This technology is economically viable, as it presented a high degree of return and low levels of risks and sensitivities. It is estimated a potential profit of R$ 55 million (NPV) over the project’s entire life cycle, equivalent to an annual return of approximately R$ 14 million (ANPV). This represents an Additional Return on Investment—ROIA of 51.17% annually. The Payback discounted occurs in the first year of its implementation. Similar analyses may apply the model we propose for other contexts involving technologies selection.