Subject Areas
Causality is a journal created with the aim of providing support to the author in the difficult task of publishing scientific contributions within the field of engineering. In this sense, a set of thematic topics have been defined within the central areas of knowledge or specific lines of research on which Causality is focused. The following thematic axes define the priority topics that the journal attempts to address in its publications, and help to guide both the authors, who wish to submit their papers, and the readers, who are looking for specialized information.
Industrial automation.
Use of systems and technologies, such as robots, control software and advanced machinery, to perform production tasks and industrial operations with minimal human intervention. Its main objective is to improve efficiency, accuracy and consistency in manufacturing processes and improve product quality. In an automated environment, machines and systems control processes such as assembly, material handling, quality inspection and packaging. These systems are often integrated with information technologies, enabling real-time monitoring and automated, data-driven decision making. Industrial automation covers different levels, from the automation of specific tasks to the implementation of complex systems that control the entire production in a plant. In modern industry, it makes it possible to respond quickly to changes in demand, improve workplace safety and increase competitiveness in the global marketplace.
Artificial Intelligence (AI) and Autonomous Systems.
Simulation of human intelligence processes by machines, especially computer systems, including capabilities such as machine learning, reasoning, perception and pattern recognition to make decisions based on that information.
Autonomous systems are those that can operate and make decisions independently, without the need for constant human intervention. These systems use AI algorithms, sensors, and control technology to interact with and adapt to their environment in real time. While AI provides the intelligence necessary for autonomous systems to make decisions and learn from their environment, autonomous systems apply that intelligence to perform tasks independently in the real world.
New trends and technologies in the industry.
The transformation in the way companies produce, manage and distribute products and services. These innovations are driving Industry 4.0. A new phase of the industrial revolution that integrates advanced technologies to improve the efficiency, flexibility and sustainability of industrial processes.
These trends and technologies are redefining the industrial landscape, enabling companies to be more competitive, adapt quickly to market changes and operate more sustainably.
Engineering Education 4.0.
An educational approach that integrates the latest technologies and methodologies to prepare future engineers for the Industry 4.0 era. This concept goes beyond traditional teaching, focusing on the development of skills and competencies needed to work in a highly digitized and interconnected industrial environment.
Education 4.0 incorporates advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), robotics, augmented reality (AR), virtual reality (VR), and additive manufacturing (3D printing) into the industrial engineering curriculum. Students learn to use these tools to design, simulate, optimize, and manage processes.
Control and automation systems.
These are mechanisms that regulate the behavior of other systems, processes or machines to achieve a specific objective. In an industrial environment, a control system monitors process variables (such as temperature, pressure, speed, etc.) and adjusts operating parameters to maintain the values of the variables within a defined range.
Automation refers to the use of technologies to perform industrial tasks and processes with little or no human intervention. The main objective of automation is to improve efficiency, accuracy, safety and consistency in production.
Sustainable systems for engineering.
The application of principles and technologies that minimize environmental impact, conserve natural resources, and promote economically and socially responsible practices throughout the life cycle of a product or project that addresses global challenges such as climate change, resource scarcity, and pollution.
The development and integration of renewable energy in engineering systems is key to reducing dependence on fossil fuels and reducing greenhouse gas emissions. These include solar energy, wind energy, biomass and biogas, and water management. Specifically, the development of sustainable systems for water management is essential in engineering, especially in regions with water scarcity, so studies are carried out on the collection and reuse of rainwater, wastewater treatment and efficient irrigation systems. Moreover, the use of sustainable materials is fundamental to reduce the environmental impact of engineering projects, including recycled or recyclable materials and low environmental impact materials.
Operations research.
This discipline uses mathematical and statistical methods and algorithms to make optimal decisions and solve complex problems in the management and operation of systems. Its main objective is to find efficient and effective solutions to optimization problems involving limited resources and multiple constraints.
The goal is to use mathematical models to represent real-world problems. These models may include linear, nonlinear, integer or stochastic equations that describe the relationships between problem variables. Then, a relevant objective is focused on the optimization of some objective function, which could maximize benefits, minimize costs, reduce time, or improve efficiency. Techniques such as linear programming, nonlinear programming, dynamic programming, and genetic algorithms are used to find optimal solutions. Operations Research supports organizations in making informed decisions based on data and models. This can involve analyzing trade-offs between different options, assessing risks, and forecasting future outcomes.
Mechatronic systems.
They represent the convergence of traditional engineering with advanced digital technologies, enabling the creation of intelligent and adaptive systems that improve efficiency, safety and sustainability in a wide range of applications that open up new possibilities for innovation and efficiency in all sectors.
These integrated systems combine the physical and digital worlds through computational networks, sensors, actuators and advanced algorithms. They also enable dynamic, real-time interaction between physical components (such as machinery, vehicles or devices) and cyber-physical systems (such as software, networks and controllers), creating an intelligent and adaptive infrastructure.
A mechatronic system can be implemented within Industry 4.0, where smart factories integrate machines, control systems, and data networks to optimize production, improve efficiency, and customize products. Finally, with the growing adoption of artificial intelligence, the Internet of Things (IoT), and cloud computing, mechatronic systems are becoming increasingly intelligent, autonomous, and connected, opening up new possibilities for innovation and efficiency across industries.
Security Engineering.
Engineering discipline that focuses on the identification, evaluation, mitigation and control of risks associated with systems, products, processes and environments. Its main objective is to protect people, the environment, and assets from potential damage that may arise due to failures, accidents, or unforeseen events.
A rigorous focus on safety not only reduces the likelihood of accidents and disasters, but can also improve operational efficiency, reduce costs, and protect an organization's reputation. Applications include: Petrochemical Industry, Aeronautics and Space, Nuclear Power, Construction, Information Technology, etc. Therefore, this multidisciplinary field covers a wide range of areas, all focused on accident prevention and the protection of people, assets and the environment. Through the use of advanced tools, rigorous analysis and a proactive approach, safety engineering plays a crucial role in creating safer and more reliable systems and processes.
Strategy and entrepreneurship.
Fundamental concepts in business development and growth, especially in competitive and changing environments. Strategy refers to the plan or set of actions designed to achieve an organization's long-term objectives, while entrepreneurship focuses on the creation, development and management of new businesses in response to market opportunities.
Entrepreneurship often involves creation and innovation is key to maintaining a competitive advantage. Strategy should support innovation by allocating resources and creating a culture that fosters creativity.
That is, strategy provides the direction and framework for making decisions in entrepreneurship, while entrepreneurship drives the implementation of new ideas and the creation of value in the marketplace. Both are essential to the long-term success of any business.
