Create awesome websites!
Creation of a knowledge portal, the basic function of which is the possibility of optimal storage, updating, supplementation, maintenance, targeted distribution and above all protection of information and knowledge for use in corporate R&D departments, but also for external stakeholders to support their interest in the company's production. Testing of the operation of the Internet knowledge portal (IPTI) of the technical base base (BATEZ), with processing of the results into an application version. Technical support.
Specification of the information and knowledge required for the technical development of the defined field within the corporate R&D concept. Creation of a technical information base (BATEZ), taking into account the needs that are continuously being developed. This involves filling the database according to clearly defines rules, respecting subsequent electronic processing.
Installation and start-up, testing the basic functions of the portal (User panel, IPZ Administration, IPU Helpdesk, Document) and start of operation.
The most important part of the solution of stage E2 was setting up different types of dials. These record the list of used quantities and their units. It also contains an important import of data in MS Excel file into the IPZ database.
Comparison of the parametres achieved by machining the same material (and the same abrasive thickness). The parameters of roughness and quality of the machined surface and compared depending on different feed rates.
Users write down their requests of problems directly in the system. The IPZ helpdesk is connected to the central VUSTE-APIS helpdesk and communication between the customers and the solver is therefore fast and efficient.
The basic task of the knowledge web portal will be to store, accutalize, update, maintain, distribute and protect information and knowledge for the use of beneficiary's and partners' R&D during the Project.
Development of a dialog knowledge system and data populating. User use of ZIP by providing knowledge, technical information and lab test information for design and manufacture of the press head. Providing maintanance of the productive operation of the web application (ZIP) including user support and changes.
It will allows solvers to store and access the results of laboratory analysis of abrasives and their cutting properties.
provide information on the appropriate abrasive for the required technology based on the expert system principle. The web-based knowledge portal will process data from the operation of the recycling line and use newly developed algorithms (models, networks and simulation) to control the line technology based on the Industry 4.0 principle.
To select basic technological parameters and tools for machining difficult to machine materials in order to increase adaptibility and efficiency interdisciplinary research.
The most important part of the E3 stage solution is the definition of the data structure of the repository (BigData) based on the result continuously obtained from the solution (measurements, lab tests).
Installation and operation of project management tools - use of the portal, for monitoring project performance and for communication between researchers.
Under technological control, collection of data from individual sensors, continuous evaluation and replenishment of the database. Solution of tools for basic data control: repositories (data forms, overviews and reports).
of a cloud portal for active interaction of all project participants.
for data transfer to the cloud, design of the storage structure and representation of sensed variables.
for remote transmission and processing of sensor data from robotic platforms.
for user reuse of the cloud portal and launching a productive operation.
Unique applicable system for streamlining the management of a printing company providing top managers with an effective tool for decision support based on immediate and accurate information in real and predictive mode about the status and parameters of managed business processes.
The design and implementation of the database, including the means used, will respect the use of big data processing methods (BigData). The cloud will be used for this purpose.
of internet technical knowledge portal for efficient ecological harvesting of dendromass.
An online technical knowledge portal for the testing of funtional samples of a skid steer and high volume trailer with selected accessories.
Unique and applicable system for managing complex projects. It will allow remote access and communication between all the project subjects.
The design and implementation of the database, including the resources used, will respect the use of big data processing methods (BigData). The cloud will be used for this purpose.
Design of a Proactive Model of Operational Reliability (PMOR) of a printer production system using Fronte as an example for continuous monitoring of machine components. Data representation of PMOR and design of verified model components. Launching a knowledge portal for PMOR implementation and Project Management.
Obtaining comparative datasets (emission-free states) to evaluate monitoring of critical PMOR components for use in machine learning. Design and validate the use of AI tools to evaluate operational monitoring within the PMOR model. Design and validation of PMOR core functions.
Testing of PMOR data interface functions to collect, transmit, record, and process monitoring data. Testing and validation of PMOR functionality in implementation on a subscriber queue.
The project is solved in cooperation with the University of Technology České Budějovice,
with the Institute of Business Strategy of the VŠTE, through the Department of Management:
The dataset, or a supporting database on real industrial enterprises, has been created at the Department of Management of VŠTE for several years and contains more than 700 entities with data on the state of their value processes and reactions to the external economic environment. The database has been transferred to the cloud, key (economic) data are being added and the assessment of entrepreneurial competence is being progressively processed.
The preprocessing will determine the structural dependencies of the state data representing the individual components (categories) of the enterprise value chain. A suitable machine learning method will be used and validated to find the relationships between the state and (corresponding) key data over the Dataset (KNN). The results will be compared with the data input of the user - the queried enterprise against its query targets - the key data.
