Platform for Industry 4.0
LOTYLDA is a platform for collecting and analyses a data from production processes (machines, operators, process), managing maintenance (reacting, planing, prediction) and support logistic.
Uses a deep learning for computer vision and signal analysis (vibrodiagnostic, PLC). It's ideal tool for quality control or predictive maintenance.
LOTYLDA is being developed by the Czech based company OptiSolutions.
Integration, analysis and visualization of TBs data
all data (machines, ERP, DB, EOLT, XLS) in one place
Data mining (LOTYLDA BI)
searching for nontrivial dependencies in data
Object recognition by Neural Networks (LOTYLDA DL)
product classification, quality control
Module for maintenance and terminal (LOTYLDA PMM)
reactive, planned and predictive maintenance
non-production states, material logistics
available from PC, tablet, mobile
ability to run on multiple servers
uses the GPU
It is an Artificial Intelligence tool for advanced quality control or machine diagnostics. It uses machine vision and deep neural networks. Ideal for image, video, sound, or vibration recognition.
Neural networks are taught similarly to humans according to examples (patterns). Their advantage is the generalization capability, that they apply the learned knowledge to differing conditions from those under which they were taught
It is an online platform for collecting, storing and analyzing large data. It is available via web browser (HTML5). It provides the tools for ETL creation, data storage, reporting, analysis and prediction modules.
Able to create a statistics application
All descriptive statistics are ready
Statistics use a parallel query
Data-mining with an implementation of GUHA method.
Production and Maintenance
LOTYLDA PMM is an application manages and monitors human resources and machines and maintenance within the production area
management and monitoring of operators, identification of operators, production lines and non-production processes
production plans and stoppage analysis
EOLT management, indicators measured by individual products
identification of possible defects for NOK analysis
maintenance monitoring and planning
machinery and its defects vs troubleshooting
predictive maintenance based on sensors data