For an institution to take a more sustainable path in terms of water use, it is essential to implement a management plan that aims to monitor the use of the natural resource and apply measures for continuous improvement in its management. Thus, during the course of the study, the records of the five water meters installed at the CJA headquarters were collected and digitized. In addition, the information obtained about the equipment that makes up the hydrosanitary system of the CJA headquarters was stored and analyzed in an online database developed to assist water management on a university campus. However, the data collected served as a basis for research involving the use of water in university environments developed by authors interested in the subject. One of the surveys carried out to support the proposal for a water management plan for UFSB culminated in the creation of a flowchart of actions that uses the following tools: micromeasurement; assessment of the standard uncertainty associated with the data; data reconciliation - RD; environmental performance indicator; and assessment of the standard uncertainty associated with the indicator. The flowchart consists of seven steps and aims at water management with a focus on evaluations and continuous improvements of actions aimed at optimizing the use of water on a university campus. Through the results obtained for the per capita water use indicator prepared for the UFSB rectory building, it was possible to observe a large demand for water per user, with a per capita flow of (36 ± 5) L for the most favorable scenario /day and at worst (81 ± 17) L/day. Thus, the high per capita demand for water observed in the study highlights the need for commitment to carry out the actions proposed in the water management plan. The proposed water management plan is strategically presented to UFSB through the UFSB's Sustainable Logistics Plan.

Changes in an industrial process are associated with the need to improve levels of competitiveness. The reduction of failures and cost control are requirements that enable the sustainable permanence of the industry in the Market, in addition to well-standardized processes through the redefinition of low efficiency activities, the identification of failures in the task and consequent reduction of process losses. This work is a case study in a glass production industry using Fuzzy Logic in the identification and evaluation of the effect of critical variables of human factors and the impact of these variables in this manufacture, as a proposal of process efficiency. The model incorporates the knowledge of operators and managers in the elaboration of an action plan for regulation and improvement in the execution of the task. The simulations used the three input variables: Training, Stress Level and Commitment, and in the design of the rules in the Fuzzy Model, the weights named: High, Medium and Low were defined. In the simulation, the maximum value for the Training variable and the maximum value for Commitment, demonstrated the probability of reduction in the glass loss indicator from 50% to 13%, even in an environment of high stress level. The medium-sized Manufacturing Industry, using fuzzy tools, manages to direct actions to reduce process losses, indicating the benefit of scientific methods for the operation of the factory floor, thus contributing to its economic and environmental sustainability.

Oil exploration activities in the Brazilian pre-salt are in full expansion and have required significant investments in the construction of new offshore production platforms (FPSO), estimated at US$90 billion. These ocean structures are extremely complex, with high added value and their construction, in large part, has been contracted in Asian shipyards. The option of constructions abroad reveals questions about the competitiveness of the national industry and its relationship with the requirements of minimum local content (25%) established by law. This research was based on a consistent critical assessment of the current state of this segment in Brazil, assessing its competitiveness against international competitors. For this purpose, a mathematical modelling of demand forecast for FPSO was developed for the period of 10 years (2021 to 2030), whose result was used in the conversion of the demand forecast of the component parts of the structure, followed by the analysis of the construction industry offshore and definition of competitiveness parameters to meet the expected orders, which resulted in the possible construction of 30 platforms expected by this methodology in the indicated period, according to the current state of the technological art. The economic and social impacts of possible scenarios of offshore activities in the next 10 years were also evaluated. It appears that the methodology used in this research allowed to generate impressive results, contributing to break the paradigm of the impossibility of offshore construction capacity in Brazil on a scale to meet current national demands, as well as to evaluate the benefits of competitive continuity of this industry for future markets of alternative and renewable energy offshore.

The present work consists of the development and evaluation of a tool that helps in predicting the cost of building maintenance of an IFES This forecast, besides to contributing to the planning of maintenance services, assists IFES to comply with specific legislation that deals with budgetary planning of institutions and the Union. To ensure that the prediction of the cost of building maintenance has robustness, mathematical model were developed, using techniques with RLM that perform the prediction of the values of these costs, aiming to help IFES in carrying out a more efficient financial planning for performing maintenance tasks. As an object of study, was used the set of 63 Federal Universities in Brazil that were in operation in 2018 . Based on annual data from these IFES, information that influences the cost of building maintenance in the following year is analyzed. The final equation of the model in the studied period showed robustness in meeting the applied statistical assumptions, presenting indices R = 90, 4% and R2 = 81, 8%. A set of simulations with the final equation reveal satisfactory results for the developed tool.

The biscuit industry generated 136 billion dollars in sales and increased 9.68% in 2018. As companies in this segment, they need to adopt methods that enable them to optimize or improve their processes, in order to remain competitive in the market. One of the methods used to meet this objective is the Statistical Process Control (SPC) used to decrease the variability of a process based on statistical analysis. The main objective of this research was to implement statistical process control for monitoring of the biscuit manufacturing process, elaborating univariate and multivariate control charts. The biscuit production line was evaluatedat three collection points using two type of molds (A and B to assess the correlation, those impacted on the colleting points for five process variables: raw weight, roasted weight, thickness, length and width. Statistically significant differences were found between these sites when mold A is used, and it is recommended to collect it from the MEIO collection point. This same difference was not evidenced using the B mold. The Anderson-Darling test was performed to assess adherence of the variables to normality. The gravimetric variables (raw weight and roasted weight) are not normal variable (p-value < 0,05), while the dimensional variables (thickness, length and width) showed adherence to normality. The improvement made by process control reduces the quality losses. Before starting this work, the quality losses were 10.37%, when finished this study it was 7.52%, considering a reduction of 27.48%. Improvements were recommended for the company to provide future work.

RenovaBio is the new National Biofuel Policy in Brazil with the objective of contributing to the reduction of greenhouse gas emissions - GHG, promoting the expansion of production and encouraging the use of biofuels. Its principles are the contribution of the biofuels market to the generation of jobs, income and regional development and the promotion of value chains related to a sustainable bioeconomy. The main objective of this work is to carry out an exploratory study on the expansion of production and consumption of Ethanol Fuel in Brazil focusing on different Brazilian regions and, in view of RenovaBio's projections, carry out a regionalized
analysis of the results of the certification plan for this program. For this, a current and historical view of the production of this biofuel is presented, as well as the consumption related to the mitigation of greenhouse gases, to the development panoramas, presenting a forecast for regional growth in the production of this biofuel. This research is an exploratory, descriptive, quantitative, bibliographical and documentary study of the updated literature, based on an analysis of public information regarding the growth of the ethanol biofuel, its effects and
perspectives. This work concludes that RenovaBio is a milestone for supporting climate mitigation actions, stimulating the production and consumption of ethanol in Brazil and is partially adequate to generate sustainability for the growth of the biofuel market in Brazil as a whole. The high number of biofuel production units that joined the program indicates an expectation of success for the program by society. However, the Brazilian legislation for ethanol will require a greater regulatory effort to be successful in stimulating the production and consumption of ethanol, having as a great challenge the great differences between the regions of Brazil. As for the growth estimates, this work concludes that government estimates regarding the growth in ethanol production can be achieved, with greater attention being paid to regional aspects. This will require intense monitoring of the performance of regulation in the face of inequalities between regions that are less intensive in ethanol production and consumption.

Catalyst additives are substances added to the fuel that provide an improvement in burning, emission of pollutants and engine performance. These additives provide different results to the operation of a Diesel engine. However, its use applied to fuel is not regulated by tax agencies, which justifies the need to investigate and validate the effectiveness of its application. Thus, the objective of this work was to evaluate the effects of adding an additive (based on enzymes) to a binary mixture of mineral Diesel with 10 ppm of sulfur and biodiesel (S10), resulting in a B11 ratio. In addition to the 2 mixtures evaluated, with and without catalyst, pure mineral Diesel was evaluated for the purpose of validating the literature. The points evaluated by this study were the specific fuel consumption, the pollutant emissions (CO, CO2, NOx and particulate matter) emitted in the process of incomplete combustion of the study fuels. The test was carried out on an engine dynamometer, with a 22 kW and 70N two-cylinder Diesel engine. m. The equipment was maintained at a constant load and rotation regime (25% and 1700 rpm) so that the data could be extracted in triplicate to reduce any measurement and equipment errors. The additive proved to be ineffective, in the concentration and regime tested, so that it did not result in the reduction of specific fuel consumption and reduction of gaseous emissions. However, the analysis of the emission factor (FE) and the emission of particulate matter (PM) indicated that the additive increased the emissions of PM1.0 in relation to the B11 mixture, suggesting a more efficient burning of the larger particles (PM2.5) . The emission of PM masses also followed this behavior and the justifications are based on the same ones as the FE. The results of the particle size and concentration distribution indicated that there was a reduction of approximately 25% in the peak of the number of particles emitted by the engine for the biofuel mixture, in addition to providing significant reductions in the particles larger than 110 nm. In general, the evaluated additive brought interesting results for reductions in the indices related to PM, presenting viable characteristics for an eventual addition to the biofuels, reducing other undesired points. .

The Public Administration faces major challenges in its constitutional responsibility to
efficiently and effectively meet the demands of the Brazilian citizen. The general objective
of this work is to apply the concepts, principles and tools of the Lean Thinking in the
administrative area of the department that manages the air conditioning systems of the
Federal University of Bahia (UFBA). The problem situation that motivated the start of
the research was to increase the processing capacity of the sector in front of the high
demands of services requests for the air conditioning equipment of the university. The
contribution of this work is to encourage the implementation of best quality management
practices in Brazilian public institutions and to develop a research that presents a
relevant and beneficial contribution to the continuous improvement of the theoretical
reference of the subjects studied. The research method used was the descriptive researchaction
contemplating qualitative and quantitative approaches. In order to provide
support to the method adopted and to obtain the expected results, a literature review was
carried out on the topics discussed: Lean Thinking, Lean Office and Public
Administration. In this respect, Lean Office concepts and tools, such as the 5S system and
Value Stream Mapping (VSM) were used. Through the application of the acquired
knowledge it was possible to construct the Current State Map of the studied sector and to
design its Future State Map. In addition, improvements were identified for the
administrative process investigated and, consequently, an action plan was proposed to
obtain its Real State Map. The Lean Office implementation result was observed
qualitatively and quantitatively. In qualitative terms, it promoted the development of a
more organized work environment, leaner procedures and more motivated and
productive employees. In quantitative terms, were observed a 50% increase in the Value-
Added Rate (VAR) for the process studied and a reduction in Total Lead Time (TLT) of
client-citizen demand from 795 minutes to 30. Finally, through the results obtained and
the analyzes carried out, it can be concluded that the Lean Thinking has proved to be a
valid methodology for the improvement of administrative processes of a Public
Administration office.

In the pulp and paper production process, wood extractives are low molecular weight organic compounds that cause operational problems, environmental damage and loss of product quality. There is some research on the impact of extractives on biota, the characterization and removal of pitch, however, there is still a lack of studies investigating the cause of extractives content variability in eucalyptus wood. This research aimed to develop a model for predicting the extractives content in eucalyptus wood clones. Principal Component Analysis (PCA) was applied to assess the impact of the various variables on extractives content: planting region; soil type, amount of sand and clay, organic and inorganic matter, pH and soil management, age, basic density, lignin content and wood genetic material. An empirical neural network model was identified from experimental data, with the main components as input to monitor and predict extractives content, as laboratory measurements may take several days and become available only after wood. have already been processed. Experimental data were provided by a pulp company and contained information on eighteen eucalyptus clone species from five regions in the extreme south of Bahia, Brazil. After initial data screening, a set of 119 samples were collected and analyzed using Principal Component Analysis. The variability of the data was represented by eight main components, which indicated that the potential acidity, iron, aluminum saturation, magnesium, pH, sum of bases, remaining phosphorus, zinc, manganese and copper were the variables that most impacted the acid content. eucalyptus wood extractives. Thus, two neural network models were developed
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whose inputs were these most important variables for the extractives and the eight main components. The neural network models were compared to identify the model with the best performance and viability to be applied at industrial level. The effectiveness of the model was verified by statistical parameters, which indicated the reliability, with good quality of fit to the experimental data. Both models performed significantly by providing a systematic tool for predicting and monitoring the contents of eucalyptus wood extractives before low quality wood affects the process. The artificial neural network whose inputs were the ten significant variables obtained by the PCA technique enabled better quality of network adjustment to the experimental data and better viability as the industrial applicability. The approach developed here can help to monitor product quality as well as to prevent damage to the environment and equipment.

The compatibility of rubber used in automotive fuel system has been investigated with biodiesel in response to the increase of the biodiesel content in diesel. Elastomeric compounds based on nitrile rubbers (NBR) showed a lower resistance to degradation. Polyvinyl Chloride blended with Nitrile Rubber (PVC/NBR) has being used on fuel filler pipe and sender gasket in automotive fuel system. The change of the base polymer in rubber formulation such as fluorinated (FKM) and hydrogenated nitrile (HNBR) may increase the degradation resistance but with higher costs. Most research has shown the resistance of rubber compounds against biodiesel based on polymer chain comparison without considering other additives. The main aim of this work was to identify the mechanical property, swell and hardness changes of PVC/NBR (Polyvinyl Chloride blended with Nitrile Rubber) compounds reinforced with carbon black, silica and calcium carbonate plasticized with di-2-ethylhexyl terephthalate (DEHT) and tri-2-ethylhexyl-trimellitate (TOTM) after biodiesel B30 (30% biodiesel in diesel) interactions under 80∘C. Through mechanical and chemical properties, the effect of B30 on the degradation of polyvinyl chloride (PVC) and nitrile (NBR) blend was evaluated during 5040h immersion at 80°C. The results showed that PVC/NBR reinforced with silica improved the resistance to B30 with better stabilization of biodiesel. DEHT plasticizer showed better results when reinforced with carbon black and TOTM when reinforced with silica.