Controle Estatístico da Qualidade na Bovinocultura de Corte: o estudo de caso de uma propriedade localizada na região sul do Brasil.

Abstract

Livestock has a large share in the Brazilian GDP, being one of the most important economic activities in the country and, despite the pandemic resulting from COVID-19, an optimistic scenario for global competitiveness in 2020 is presented. In the southern region of the country, the evolution of the activity is notorious, being one of the states with the highest number of slaughtering in Brazil. In parallel to this, the agricultural sector in the country has undergone major changes over the past few years, such as increased costs, greater competitiveness, the need to increase productivity with quality and the conservation of natural resources, factors that instigate a improvement in the specialization of producers, and generate a need for the implementation of new technologies in the sector. Faced with this scenario, the present work aims at the implementation of Statistical Quality Control tools, in a way that corroborates by providing subsidies for the decision making of the rural producer of the Girasol farm, located in the municipality of Quevedos. In order to achieve this objective, Statistical Quality Control combined with the PDCA methodology will be used, which will enable an analysis of the production process and the choice of the best control tool among those that suit the process. The working method of this research is associated with a case study and will be based on a quantitative research, Through the application of statistical techniques and data collection in the field to quantify information and generate subsidies. Data treatment and collection were performed using Microsoft Excel and Microsoft Power BI software. The indicators calculated are pregnancy rate, birth rate, average slaughter weight and average daily weight gain. After calculating the indicators and generating indicator panels, it was possible to propose productive improvements to help the rural producer. At the end of this work, the potential of using statistical process control techniques for the management of farms and rural properties can be seen, and how these can provide information for decision-making in rural properties.