Author: Dr. Jovana Milenkovic – Head of Project Management Dpt., ATLANTIS Engineering

In Di-Hydro, one of the main objectives is to harness digital resources, such as AI and predictive algorithms, to support hydropower plants monitor their infrastructure health conditions, as well as schedule necessary maintenance which at times include the closure of the plant. To maximise efficiency, ATLANTIS Engineering can provide the expertise to devise digital solutions for hydropower plants specific needs.

For more than fifteen years now, ATLANTIS Engineering has been progressively investing in research, aiming at the exploitation of new technological capabilities and for product development. This SME has a long-standing experience in offering services and bespoke products to the manufacturing industry. The company invests particular attention on the decision support for the management and optimisation of production activities and assets’ life-cycle, as well as on the streamlining of various asset lifecycle management related processes, including predictive/condition-based monitoring.

ATLANTIS supports its clients to understand and prioritise smart manufacturing routes, embracing CPS and Industry 4.0 principles, along with obtaining a holistic view of their plant performance.  Furthermore, the company has successfully supported and organised a great number of Technical Departments of manufacturing companies, service companies, hospitals, hotels and ports through the implementation of its in-house developed Computerised Maintenance Management System (CMMS) and the state-of-the-art cognitive maintenance implementations for the Industry of the Future.

ATLANTIS digital expertise in Di-Hydro

Throughout the significant number of EU and National projects, ATLANTIS Engineering has accumulated the state-of-the-art knowledge in cutting edge technologies, such are predictive models for maintenance and production process performance, as well as autonomous quality, decision support systems, KPI-based performance assessment and zero-defect manufacturing. Our know-how in failure prediction, fault detection and fault prevention, Failure Mode, Effects and Criticality Analysis, system integration, as well as decision-making, offers a spectrum of monitoring strategies and tools for Di-Hydro pilot health monitoring. Specifically, as part of the work dedicated to diagnostic and prognostic of AI-based models, the ATLANTIS company will develop predictive models to recognise patterns to assess the current state of assets, while achieving fault detection, identification, prediction and remaining useful lifetime (RUL) estimations for components and machinery health of hydro-power plants. In this way, the maintenance and operation managers will be proactively supported in decision making with their everyday tasks.