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.

Machine tools are recognized as goods-generating equipment that constitute the realm of manufacturing facilities, providing the means of production for the generation of consumer products. This work explores the possibility of implementing sustainability concepts, employing criteria from a circular economy in the design and manufacturing of new equipment, using existing structural elements as the basis for the development of these machines. Stamping presses for automotive body panels were considered as the focus of this study. A quantitative evaluation of the possibilities for reusing existing components was developed using an algebraic tool, through the creation of algorithms that facilitate the comparative analysis of production costs and delivery lead times. Additionally, a case study was conducted to assess the capability of these algorithms to provide results, presented as comparative indicators that should be taken into consideration and may assist in the decision-making process regarding the implementation or not of the possibilities presented by the study. The simulation performed proved to be proficient, providing data that can guide decision making regarding the reuse of the chosen structural elements, based on their soundness verified through inspections conducted by the machine designers.