Agroindustrial best practices that contribute to technical efficiency in Brazilian sugar and ethanol production mills
Introduction
Brazil currently holds a prominent global position in the field of biofuel production and technology and contributes to the emerging low-carbon economy and growing global demand for alternative and renewable energy sources mainly through industrialization of sugarcane crops [1]. The United States and Brazil lead the replacement of oil by biofuels in power plants; together, they account for 89% of the global production and 88% of the world's ethanol consumption [2].
According to the Brazilian Sugarcane Industry Association, Brazil is the world's largest producer of sugarcane (with 607 million tons harvested in 2016/2017), and is a leading exporter of sugar and ethanol (US$ 11.16 billion/FOB in 2016). Brazil has a great competitive advantage in these sectors in terms of production [3].
It should be noted that a wide variety of products are derived from Brazilian sugarcane, including food (sugar and related products), bioenergy (ethanol and bioenergy), bioplastics, and even substances that are used in pharmaceutical field [4].
The 2017/2018 projections indicate a milling harvest of 585 million tons, which is a decrease of 22.14 million tons compared with the previous year's harvest; this is mainly because of the slight decrease in the area available for cultivation and the expected decrease in the agricultural productivity of the sugarcane to be harvested during the 2017/2018 season [3].
The macroeconomic environment, structural aspects, and environmental constraints affect the production costs, increase the indebtedness of producers, reduce investments, and limit the application of new technologies to sugarcane varieties, cultural treatments, and the renewal of sugarcane plantations [5].
This decrease in productivity affects financial resources. For the survival of the sugar and ethanol mills and to improve the technical efficiency of the sugar-energy industry, it is crucial to know which sectors to invest in, how to increase the production, which production areas need to be studied, and how to develop a new production technology [6].
At the same time, climatic variations had affected recent sugarcane harvests, bringing a lot of difficulty to sugar and ethanol production. Both public and private actors should play an active role in formulating and implementing actions [7] that can increase the agricultural and industrial areas and in implementing actions that improve, in the best sense of the word, the agroindustrial sector, which enable the production units (mills) to achieve a high technical efficiency, based on the best practices developed in this research.
Assuming that resources are scarce and need to be optimized, especially in times of crisis [8], this work aims to propose the agricultural and industrial best practices for increasing the efficiency of Brazilian mills producing sugarcane, sugar, and ethanol. These practices will enable the mills to manage their resources that are directly linked to the efficiency and thereby remain competitive even in times of difficulty, thus improving the performance of the organization and the sector. This improvement in the allocation of resources through the good practices provided by this study can benefit both the company and the society [9].
Although many studies have identified the factors capable of improving the efficiency of a sugar-ethanol mill, as accelerated and development of sugarcane crop [10], sugarcane yield [11], industrial capacity [12], supply chain management [13], energy development [14] and financial investments [15], this work presents an unprecedented contribution in terms to propose best practices. Based on operational-level information of the production process, this work was able to identify the operational aspects directly related to the efficiency and direct the allocation of resources in the plants, since resources are limited and need to be optimized.
In addition, the present study provides a method of efficiency measuring by combining the existing techniques and the explanatory factors. This contribution is fundamental and represents knowledge generation, since the work tends to evaluate the industrial efficiency and the agricultural efficiency.
Section snippets
Materials and methods
In the sense of explaining to the reader the whole methodological process, sections 2.1 Efficiency, 2.2 Agricultural and industrial efficiencies, 2.3 Agricultural and industrial processes occurring in sugar and ethanol mills contain the concepts with the respective literature that was used in this article as a theoretical basis.
Quantitative step
By applying the DEA technique with output orientation, two efficiency models were used. The total milling yield harvest of the crop (t) and the amount of TRS (t) were used as the inputs. and the sugar (t) and ethanol (m3) yields were used as the outputs. The distribution of the data used to evaluate the technical efficiency is provided in Table 4.
Based on the two efficiency levels obtained by using DEA analysis, the DMU variation was calculated, resulting in a θf that can be used to analyze its
Discussion
Once the results were obtained through both quantitative analysis, which provided the most relevant aspects, and qualitative analysis, which revealed the management methods, it was necessary to compile and analyze them in order to identify the best agroindustrial practices. The highlights of these practices are structural, operational, and management factors.
First, there are factors that are directly related to the field, such as rainfall, temperature, sugarcane ART in the digester, and
Conclusions
In this study, the agricultural and industrial indicators contributing to the global efficiency of sugar and ethanol production mills were identified based on qualitative–quantitative analysis. Within the limitations of this resource, the results suggest that these indicators contribute to the overall efficiency of the sugar-energy industry.
The comparison among mills, it was done through benchmark mills, becoming possible use the data collected as reference, being a reach driver, that
Acknowledgments
The authors are grateful for the financial support of the Coordination Higher Education Staff Development (CAPES) and for the valuable comments of the anonymous reviewers.
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