The purpose of this article is to analyze the performance of companies in the slaughterhouse industry in health and safety issues. The research method is quantitative modeling. The main research technique uses a mixed method based on multi-attribute utility method (MAUT) and artificial neural networks (ANN). The research object is 34 slaughterhouse companies located in Southern Brazil. Then, we ranked the companies and modeled their decision trees using the MAUT method. | 48 Int. J Sup. Chain. Mgt Vol. 8 No. 5 Oct 2019 Performance Analysis on Health and Safety Issues of Companies from the Slaughterhouse Industry Ismael Cristofer Baierle 1 Miguel Afonso Sellitto 2 Jones Luís Schaefer 3 Jaqueline de Moraes 4 Jairo Koncimal 5 Elpidio Oscar Benitez Nara 6 1-2 Production and Systems Engineering Graduate Program University of Vale do Rio dos Sinos Brazil 3-4-5-6 Industrial Systems and Process Graduate Program University of Santa Cruz do Sul Brazil 1ismaelb@ 2sellitto@ 3engjlschaefer@ 4jaquelinemoraes@ 5jairokoncimal@ 6elpidio@ Abstract - The purpose of this article is to analyze the Assessing competitiveness is an important step in performance of companies in the slaughterhouse industry in strategic management 6 . To assess the competitiveness of health and safety issues. The research method is quantitative a company we use key performance parameters KPI to modeling. The main research technique uses a mixed method help managers to improve productivity quality based on multi-attribute utility method MAUT and artificial neural networks ANN . The research object is 34 operational performance and efficiency 7 . KPIs are slaughterhouse companies located in Southern Brazil. Then defined by the strategic objectives of the company 8 . we ranked the companies and modeled their decision trees This study used data from the slaughterhouse industry. using the MAUT method. From these results neural The industry suffers the consequences of accidents. networks were used to benchmark and compare the methods. Therefore monitoring and controlling performance This resulted in a linear equation that represents the closest indicators related to health and safety can be relevant to solution to the ideal and percentage error in the decision competitiveness. The selection of KPI s is an MCDM tree s resolution. Thus neural networks are most efficient multi-criteria decision-making problem 4 and
