Partner Details

 

Transition Technologies S.A.


Polish company operating globally with 25 years of experience. We are a stable provider of IT solutions for industry.

 

 

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Overview

1) Polish company operating globally: * Company`s branches abroad (USA, Germany). * More than 500 projects abroad (USA, Asia, Western Europe). 2) Stable provider of IT solutions for industry: * Strong position in a difficult and competitive market. * Specialization in selected market segments (energy, gas, industry, healthcare). * Experts in the field of IT industry. 3) The leader among the investors in R&D in the IT market: * A separate, big R&D department. * Solutions protected by patents worldwide.

Partner Type: System Integrator

Active Locations: Africa, Asia-Pacific, Europe, Latin America, Middle East, North America

Industries: Engineering Services, Hospital & Medical, Mining, Metallurgy & Material, Oil & Gas, Power Generation, Pulp and Paper, Water & Wastewater

Partner Tier: Registered

Locations

Headquarters

Pawia 55
Warsaw, 01-030 Poland
Phone: 0048 661 904 350

Accreditation

 

 

Products & Services

 

EDS - Enterprise Data Server

EDS is a system whose main task is to collect live process data from the control system and view this data for analysts and executives. The system presents information in the form of process diagrams, trends and reports in the convenient and intuitive user interface of EDS Terminal application. Collected data can be interactively displayed and analyzed in real-time at desktop computers and also using mobile devices from any location in the world.

 

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SILO - Stochastical Immunological Layer Optimizer

SILO (Stochastical Immunological Layer Optimizer) is an Advanced Control class software solution which is aimed to perform automatic, on-line optimization of industrial processes - combustion in power boilers in particular. It is one of these systems which draw their inspiration from the nature. The SILO’s inspiration is an immune system of living creatures, which gives it some unique features such as on-line learning of the process and effective adaptation to new, unknown operating conditions. The main advantage of the SILO algorithm is efficient coordination of two algorithms - learning and optimization. From one hand, the system monitors the process parameters constantly to collect the knowledge. From the other hand, it calculates setpoints or corrections to setpoints of such decision variables like: O2 demand, secondary air dampers, OFA (Over Fire Air) dampers, coal feeders etc. to meet optimization goals related to superheated and reheated steam temperatures (SH and RH steam temperatures), superheated and reheated sprays flow, NOx and CO emission, etc. Implementation results show that SILO is able to significantly improve such parameters like flue gases temperature, CO, NOx emission and LOI (Loss on Ignition). These results had a positive impact on process efficiency and the environment.

 

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