A5048380249- Digital Transformation in Industry
- Optimization and Mathematical Programming
- Energy Efficiency and Management
- Software System Performance and Reliability
- Flexible and Reconfigurable Manufacturing Systems
- Multi-Criteria Decision Making
- Advanced Multi-Objective Optimization Algorithms
- Service-Oriented Architecture and Web Services
- Efficiency Analysis Using DEA
- Water resources management and optimization
- Big Data and Business Intelligence
- Green IT and Sustainability
- Data Management and Algorithms
- Advanced Graph Theory Research
- Semantic Web and Ontologies
- Manufacturing Process and Optimization
- Product Development and Customization
- Machine Fault Diagnosis Techniques
- Business Process Modeling and Analysis
- Scheduling and Optimization Algorithms
- Water Quality Monitoring Technologies
- Cloud Computing and Resource Management
- Advanced Database Systems and Queries
- Fault Detection and Control Systems
- Distributed and Parallel Computing Systems
University of Piraeus
2022-2024
Athens University of Economics and Business
2013-2020
Danaos (Greece)
2018
Digital Twins (DTs) are a core enabler of Industry 4.0 in manufacturing. Cognitive (CDTs), as an evolution, utilize services and tools towards enabling human-like cognitive capabilities DTs. This paper proposes conceptual framework for implementing CDTs to support resilience production, i.e., enable manufacturing systems identify handle anomalies disruptive events production processes decisions alleviate their consequences. Through analyzing five real-life cases different industries,...
One of the key challenges in maritime industry refers to minimizing time a vessel cannot be utilized, which has multiple effects. The latter is addressed through maintenance approaches that however many cases are not efficient terms cost and downtime. Predictive provides optimized scheduling offering extended lifespan, coupled with reduced costs. As several industries, including domain, an increasing amount data made available deployment exploitation sources, such as on board sensors provide...
The new data-driven industrial revolution highlights the need for big data technologies to unlock potential in various application domains. In this context, emerging innovative solutions exploit several underlying infrastructure and cluster management systems. However, these systems have not been designed implemented a "big context", they rather emphasize address computational needs aspects of applications services be deployed. paper we present architecture complete stack (namely...
In this paper we describe a scenario from the Shipping industry, that employs analytics, stream processing, monitoring, alerting and vessel route optimization over big data. This includes business process modelling, infrastructure management monitoring along with dimensioning deployment of focused services requiring different stakeholders roles for their parameterization enactment. Apart analysing domain requirements user roles, show how BigDataStack, i.e., high-performance data-centric...
Shipbrokers play a key role in maritime industry by acting as intermediates between shipping companies and the market. They undertake various chartering, buying or selling operations. In this paper, we propose mathematical programming approach for evaluation selection of shipbrokers. Specifically, score each ship broker is composite measure that derived aggregating set performance criteria, e.g., reputation, etc. The developed models enable aggregation weighting criteria. We employ three...
Liquified Petroleum Gas (LPG) is an oil refinery product that must adhere to quality specifications with respect certain impurities. Refineries apply LPG purification process consists of a flow network several units (PUs). Current methods focus on optimising the performance each PU separately; there exists no known approach for identifying whole optimum. In this paper, we present as whole. We utilise operational scenarios model non-linear transformations PU. These enable us devise Mixed...
In this paper, we present the Optiship decision support system (DSS) developed for evaluation of alternative decisions in context ship's Life Cycle Assessment (LCA). particular, DSS is devoted to assessment operation and end-of-life LCA phases. For problems occurring these phases, provides user with KPIs that correspond three main dimensions-criteria, i.e., Economic, Environmental Social. The some involve uncertainty as they refer future. designed account by employing mathematical methods...