Industry 4.0 in the context of passenger railway companies

A Indústria 4.0 tem sido um tema de pesquisa crescente e tem chamado a atenção de países desenvolvidos e emergentes que buscam uma posição de destaque neste novo cenário industrial. O setor ferroviário é um segmento relevante para o transporte de pessoas e mercadorias. No entanto, a literatura que une o tema Indústria 4.0 e ferrovias ainda precisa ser explorada. Na prática, há mais estudos partindo de uma determinada tecnologia em evidência. Assim, este trabalho levanta uma questão importante: como os conceitos da Indústria 4.0 podem ser aplicados às empresas ferroviárias de passageiros holisticamente? Utilizamos uma abordagem exploratória e qualitativa para analisar este importante setor, considerando a escassez de estudos com a visão abrangente pretendida. Entrevistamos especialistas de oito operadoras de transporte e de quatro fornecedores de tecnologia do segmento ferroviário brasileiro. Os resultados foram agrupados em um modelo de oportunidades e indicam que as empresas estão se movendo em direção a um centro de inteligência operacional para implementar oferta de trens robusta e eficiente, manutenção prescritiva, gerenciamento robusto da cadeia de suprimentos, melhor experiência dos passageiros e desempenho dos trabalhadores. Desenvolvemos e testamos um modelo de maturidade da Indústria 4.0 para operadoras ferroviárias de passageiros com base em nossas descobertas empíricas e nos principais indicadores de desempenho das empresas brasileiras. Recebemos retorno positivo de que o modelo retrata as preocupações diárias dos profissionais que trabalham para rodar o negócio e que os estágios de maturidade propostos representam um caminho para alavancar as métricas associadas aos objetivos produtivos definidos com ajuda dos indicadores de desempenho do setor. A contribuição prática da pesquisa é auxiliar as empresas ferroviárias de passageiros a planejar a jornada da Indústria 4.0 em seu segmento, tanto na concepção de novas linhas de trens quanto na busca por sistemas em operação mais sustentáveis. O estudo traz uma contribuição acadêmica significativa, pois os modelos com essa visão holística da Quarta Revolução Industrial no transporte ferroviário de passageiros são inéditos.Industry 4.0 has been a growing research topic and has drawn the attention of developed and emerging countries that seek a prominent position in this new industrial scenario. The railway sector is a relevant segment for transporting people and goods. However, the literature joining the theme of Industry 4.0 and railways still needs to be explored. In practice, there are more studies from a determined technology in evidence. Thus, this dissertation raises an important question: How can the Industry 4.0 concepts be applied to passenger railway companies holistically? We used an exploratory and qualitative approach to analyze this important sector, considering the scarcity of studies with the intended embracing vision. We interviewed experts from eight transport operators and four technology providers in the Brazilian railway segment. The results were grouped into an opportunities model, indicating that companies are moving towards an operational intelligence center to implement robust and efficient train offers, prescriptive maintenance, strong supply chain management, and improved passenger experience and worker performance. We developed and tested an Industry 4.0 maturity model for passenger railway companies based on our empirical findings and the Brazilian companies' main Key Performance Indicators (KPIs). We received positive feedback that the model portrays the daily concerns of professionals who work to run the business and that the proposed maturity stages represent a way to leverage the metrics associated with the productive objectives defined with the help of the sector's KPIs. The practical contribution of the research is to help passenger railway companies plan the Industry 4.0 journey in their segment, both in designing new train lines and looking for more sustainable systems in operation. The study delivers a significant academic contribution as the frameworks with this holistic view of the Fourth Industrial Revolution in the passenger railway are unprecedented

Trends in Smart City Development

This report examines the meanings and practices associated with the term 'smart cities.' Smart city initiatives involve three components: information and communication technologies (ICTs) that generate and aggregate data; analytical tools which convert that data into usable information; and organizational structures that encourage collaboration, innovation, and the application of that information to solve public problems

A review on artificial intelligence in high-speed rail

High-speed rail (HSR) has brought a number of social and economic benefits, such as shorter trip times for journeys of between one and five hours; safety, security, comfort and on-time commuting for passengers; energy saving and environmental protection; job creation; and encouraging sustainable use of renewable energy and land. The recent development in HSR has seen the pervasive applications of artificial intelligence (AI). This paper first briefly reviews the related disciplines in HSR where AI may play an important role, such as civil engineering, mechanical engineering, electrical engineering and signalling and control. Then, an overview of current AI techniques is presented in the context of smart planning, intelligent control and intelligent maintenance of HSR systems. Finally, a framework of future HSR systems where AI is expected to play a key role is provided

Energy Management Systems for Smart Electric Railway Networks: A Methodological Review

Energy shortage is one of the major concerns in today’s world. As a consumer of electrical energy, the electric railway system (ERS), due to trains, stations, and commercial users, intakes an enormous amount of electricity. Increasing greenhouse gases (GHG) and CO2 emissions, in addition, have drawn the regard of world leaders as among the most dangerous threats at present; based on research in this field, the transportation sector contributes significantly to this pollution. Railway Energy Management Systems (REMS) are a modern green solution that not only tackle these problems but also, by implementing REMS, electricity can be sold to the grid market. Researchers have been trying to reduce the daily operational costs of smart railway stations, mitigating power quality issues, considering the traction uncertainties and stochastic behavior of Renewable Energy Resources (RERs) and Energy Storage Systems (ESSs), which has a significant impact on total operational cost. In this context, the first main objective of this article is to take a comprehensive review of the literature on REMS and examine closely all the works that have been carried out in this area, and also the REMS architecture and configurations are clarified as well. The secondary objective of this article is to analyze both traditional and modern methods utilized in REMS and conduct a thorough comparison of them. In order to provide a comprehensive analysis in this field, over 120 publications have been compiled, listed, and categorized. The study highlights the potential of leveraging RERs for cost reduction and sustainability. Evaluating factors including speed, simplicity, efficiency, accuracy, and ability to handle stochastic behavior and constraints, the strengths and limitations of each optimization method are elucidated

Coordinated Energy Management of the Electric Railway Traction System: Croatian Railways Case Study

A railway energy management system based on hierarchical coordination of electric traction substation energy flows and on-route trains energy consumption is presented in the paper. The railway system is divided into energy-efficient individual trains energy consumption management as a lower level, and the energy-cost-efficient electric traction substation energy flows management as a higher level. The levels are coordinated through parametric hierarchical model predictive control with the main goal of additionally decreasing the operational costs of the overall system. Through interactions with the power grid at the higher level, the system can provide ancillary services and respond to various grid requests. At the same time, lower level trains driving profiles are adjusted to attain the minimum cost of system operation with timetables and on-route constraints respected. The developed algorithm is verified against a detailed real case study scenario with the presented results showing significant cost and energy consumption reduction