This study addressed the development of a pilot plant for pyrolysis of scrap tires to obtain carbon black and other byproducts. The work was motivated by the goal of contributing to the development and dissemination of knowledge about existing technologies that allow modern economies to transform waste into valuable products, by documenting and discussing an empirical application in Brazil. Thispaper describes the development of a market for steel scrap, pyrolytic oil and carbon black products obtained from a vacuum pyrolysis process. The research work was conducted in Brazil, and was guided by the twofold purpose of reducing the environmental impacts, while gaining economical sustainability. Modern economies increasingly need to devise strategies to address energy generation while preserving natural ecosystems. These strategies include leveraging the use of renewable energy sources. Acknowledging that scrap tires hold an enormous potential as a sustainable energy option, this study aimed to contribute to the development and maturity of eco-friendly processing approaches to realize its full potential. The work involved a preliminary phase concerned with the operation of vacuum pyrolysis of scrap tires at a laboratorial scale, followed by the design of the pilot plant that operated for 10 years, at the time of the study, with a 100 kg/h batch flow. Results show that the yield of the pyrolysis process was 41% pyrolytic oil, 38% carbon black, 12% gas, and 8.9% steel scrap, with a calorific value of 36 MJ/kg per tire. The carbon black was composed of 90% carbon, and the pyrolytic oil was composed of 66% gasoline and 33% other oils, which have higher quality and can be commercialized with a potential profit over 3 million dollars/year.

Due to the increasing demand for water supply of urban areas, treatment and supply plants are becoming important to ensure availability and quality of this essential resource for human health. Enabling technologies of Industry 4.0 have the potential to improve performances of treatment plants. In this paper, after reviewing contributions in scientific literature on I4.0 technologies in dam operations, a study carried out on a Brazilian dam is presented and discussed. The main purpose of the study is to evaluate the economic, environmental, and social advantages achieved through the adoption of Artificial Intelligence (AI) in dam operations. Unlike automation that just respond to commands, AI uses a large amount of data training to make computers able to take the best decision. The current study involved a company that managed six reservoirs for treatment systems supplying water to almost ten million people at the metropolitan area of São Paulo City. Results of the study show that AI adoption could lead to economic gain in figures around US$ 51,000.00 per year, as well as less trips between sites and less overtime extra costs on the main operations. Increasing gates maneuvers agility result in significant environmental gains with savings of about 4.32 billion L of water per year, enough to supply 73,000 people. Also, decreasing operational vehicle utilization results in less emissions. Finally, the AI implementation improved the safety of dam operations, resulting in social benefits such as the flood risk mitigation in cities and the health and safety of operators.

Large textile industries are deploying Industry 4.0 Technologies (I4.0T) aiming to develop a micro-level circular economy (CECP), considering cleaner production practices as a strategic tool. However, due to the environmental impact generated by the textile industry, it has not yet achieved Strong Sustainability (SS), denoting an important path to be pursued by managers and shareholders in view of meeting the 2030 agenda. With this, the objective of this study is to evaluate whether the adoption of I4.0T promotes CECP-driving SS actions in large textile industries located in Brazil. A survey was the research method adopted, and for data analysis, structural equation modeling was used to test the hypotheses and Pearson correlation between variables. It was concluded that the adoption of I4.0T promotes CECP. However, they neglect SS actions. Facilitators for CECP practices were big data, augmented reality, and autonomous robots. In terms of SS, I4.0T has a low impact on increasing resource consumption efficiency, reusing waste as input in other processes, and increasing access to commodities. This research contributes to the linking I4.0T, CECP, and SS theory. Moreover, with the dissemination of knowledge to managers about the I4.0T that generates the CECP, it is possible to develop sustainable strategies in operations. However, to move in this direction, it is essential that there is a collective effort of the government, companies, and society, starting by raising awareness about the importance of SS in the textile sector.

The concept of strong sustainability establishes ecosystem conservation as the basis for socioeconomic development. Despite the increase in the number of studies on this subject, the qualitative approach used in studies on strong sustainability makes the introduction of this theme difficult in the industrial context. The absence of a model of sustainability evaluation in manufacturing based on the concept of strong sustainability was the gap identified by this research. The objective of this study was to develop a model that embeds strong sustainability within the sustainability assessment of manufacturing companies. The research used survey methodology to obtain the opinion of experts on the relevance of sustainability metrics. Information collected from experts was used to calculate the weights of indicators and of the participation of each dimension in strong sustainability. The results indicated that strong sustainability consists of 48% of environmental, 29% of social, and 23% of economic factors. The model has been applied in a study of multiple cases in factories in the automotive sector, two in Brazil and two in Italy. The results revealed that the four companies were rated regular in the strong sustainability scale. However, the sustainability performances of the companies showed different patterns over five years. Furthermore, analysis of the individual performance of the dimensions showed that the economic growth of the two Brazilian factories was superior to the socio-environmental development. The result of the Italian units emphasized different priorities. A firm reached the best result in environmental performance and the other one on the social dimension.

Product-Service System (PSS) is a sustainable strategy that shifts the focus of the business from selling physical products to providing service by using the product. The innovation proposed in the PSS, focused on sustainable production and consumption, is consistent with the sustainable development goals of the United Nations 2030 Agenda. The scientific literature on PSS in machining showed studies that address the economic factor of PSS contract, machine maintenance and logistics and operational process improvement. Then, there is a lack of studies on the assessment of the PSS in machining under a sustainability factors perspective. Thus, the objective of this paper was to evaluate the economic, environmental, and social advantages of PSS cutting tools in machining. Consistent with this aim, the research focused on a case study in a diesel engine parts machining company. From an economic point of view, the results indicated a reduction in operating costs of US$ 1,206,080 per year, which allowed a nine-month return on investment. From an ecological perspective, the recovery of 602 kg of carbide per year mitigated the environmental impact of tungsten and cobalt exploration. These results are even more expressive because it deals with scarce metals. Furthermore, technological advances reduced the risk of injury to operators. This research increased knowledge on PSS in machining by presenting an original study that led the analysis under a sustainability perspective. Moreover, this study contributes to managers by showing the business model’s advantages that reduce operating costs and socio-environmental impacts, enhancing sustainable development.