Tecnologias da indústria 4.0 no transporte ferroviário de cargas: proposição de um modelo para auxílio à tomada de decisão nos territórios de identidade do Estado da Bahia

Abstract

Rail transport has changed the way goods are transported, especially in terms of quantities and long distances covered, bringing resource savings and reducing environmental pollutants for companies and countries. On the other hand, Industry 4.0 technologies have brought benefits to the rail transport sector, such as predictive maintenance based on sensors in superstructure components, synchronization between intermodal terminals, and operational cost reduction, among others. In Brazil, the rail freight mode represents only 17.7% of the transportation matrix, while the road mode accounts for 66.2%, which is similar in the state of Bahia. Thus, balancing the transportation matrix can be a direction for regional growth, considering the outflow of production and the need to optimize the resources involved. Moreover, linking technologies to rail transport in the identity territories of the state of Bahia can provide valuable information on the benefits for the state's productive sectors. Therefore, the aim of this work is to propose a prescriptive model based on Industry 4.0 enabling technologies applicable to rail freight transport implementation projects in the state of Bahia. Additionally, it addresses the integration of the rail sector with Industry 4.0 technologies, considering the identity territories of the state of Bahia. The method used was Design Science Research (DSR) to create an artifact containing steps to assist organizations in decision-making regarding railway implementation projects with Industry 4.0 technologies. A quantitative survey was also conducted with 18 experts from the railway sector, containing 17 questions related to technologies, railways, the state of Bahia, and scientific methods, which contributed to the construction of the artifact. To verify the reliability of the responses, Cronbach's Alpha Coefficient was used, which obtained a value of 0.8954, indicating high consistency. The results include a synthesis of case studies on intelligent sensor technologies and remote monitoring, as well as multi-criteria methods based on the experts' responses, and an artifact entitled “Sensing System - Management Phase” with three robust stages to assist managers in decision-making for railway implementation projects with technologies. It is expected that the research will contribute to new projects for the construction and expansion of the railway network in Bahia and Brazil, as well as provide valuable insights for studies on the digital transformation of the sector.