A promising direction for the development of society, especially in the conditions of the industry 4.0 paradigm, a of is the Smart City. The purpose of the Smart City is to optimize resources, monitor security, and maximize the level of services for the population. For the successful development of the concept of the Smart City, the integration of various systems and technologies is required. One part of the Smart City concept in particular to consider is the Smart Port. This article examines the existing digital solutions for the automation of Smart Ports, the direction of technology development, the existing problems and prospects for the digitalization of port terminals and transport logistics operators.
Global economy and era of digitalization poses great pressure on development of different enterprises. Businesses have to be complied with newest technologies and focus on efficiency of their management system. Seaports are complicated business systems, which are becoming global hubs for different stakeholders to exchange data within complex infrastructure. Digitalization of such complex systems requires a coherent approach, aiming to summon managerial and digitalization goals. The key concept to create a digital-based system of business processes is the concept of IT-services, which are characterized to be a support of business functions. The goals of this research paper is to adapt standard of Enterprise Architecture and create a coherent system of business processes for container terminals and suggest a set of IT-services, which could be further transformed into a complex Applications Architecture of seaport. This Applications Architecture can be further built up with modern digital technologies and information systems of different types.
Throughout the last century, global demand for electricity increased, resulting in a growing number of power plants and related infrastructure. Along with this, the demand for modernization and automation of electric networks has risen. Different industrial trends, such as digitalization and integration emerged in various industries, including energy production, result in the creation of the Smart Grid concept. Smart Grid is a term for an intelligent network that extends the distribution and transport system of electricity to optimize ongoing operations and opening new markets for alternative energy. The Smart Grid has different properties, such as increased use of digital and monitoring technologies, demand management, integration of smart metering devices and consumer devices, providing consumers with real time information and management capabilities. Smart Grid is a complex concept, which has to be analyzed for the point of implementation complexity. The key components of this implementation complexity have the technology and the organizational cores. Technological complexity includes component production, technical implementation of networks, reliability and security, and privacy. At the same time, organizational complexity is associated with the interests of a huge number of different stakeholders and their goals. All these points complicate the implementation of technology and the creation of a unified potential implementation framework. This research papers addresses the Smart Grid technology in order to create its comprehensive understanding and develop this implementation framework based on worldwide standard of Enterprise Architecture.
This paper presents a time-sequential probabilistic simulation model for the detailed design of maintenance strategies for turbine critical items. The term item shall refer to any part, component, device, subsystem, or functional unit of a wind turbine that can be individually described and considered. The model enables wind farm operators and turbine manufactures to find the most cost-effective maintenance strategy for each turbine critical item. Cost optimizations are realized through a better adaptation of the maintenance strategy to the item-specific failure modes, degradation processes, failure detection capabilities and the given operational configuration of the wind farm. Based on a time-sequential Monte Carlo simulation technique, the maintenance activities at turbine level are simulated over the windfarm’s operational lifetime, considering correlations between the stochastic variables. The results of the Monte Carlo simulation are evaluated using statistical means, thereby, determining the optimal maintenance strategy and associated parameters. The developed model is implemented as a Python application and equally applicable for onshore and offshore windfarms.
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