logo tyris AI

MAINTENANCE AND

PREDICTIVE QUALITY

TYRIS AI IS LEADER IN PREDICTIVE MAINTENANCE SYSTEMS WITH MACHINE LEARNING TECHNOLOGY.

The system creates predictive models to identify future breakdowns/failures in critical machine components before they occur, through automatic learning of production parameters. The main objective of the system is to increase machine availability, increase production and reduce uncontrolled downtime.

Métricas y mejoras

Metrics and Improvements

The system integrates the process data through access to the different information sources of the factory (Sensors, Databases, Automatons/PLCs, Maintenance Parts and Excel, CMMS Systems, MES, ERP, SCADA, etc.).

55%

REDUCTION OF CRITICAL MACHINE FAULTS​

The anticipated knowledge of the breakdowns allows, knowing the type of failure, the workpiece model and the corrective to apply in planned stoppages.​

35%

INCREASED MACHINE AVAILABILITY​

The main objective is to increase the machines availability, increase production and reduce uncontrolled downtime.​

30%

INCREASE THE AVERAGE TIME BETWEEN FAULTS (MTBF)​

Predictive analytics allows you to improve corrective operations, optimizes plannings and the management of spare parts helping to increase MTBF​

45%

REDUCED MAINTENANCE COSTS​

The predictive system allows optimizing the main factors for the reduction of maintenance costs (Times, Resources, Components, etc.).​

Optimizacion-Energetica

ENERGY

OPTIMIZATION

Machine Learning Module developed to optimize and minimize energy consumption associated with machinery or production processes in industry.

The solution has a data integration layer that connects with the systems to be optimized to integrate and monitor internal process data such as manufacturing status, associated consumption or demand forecast, and external data such as the price of the electric pool.

It allows communication with sensors deployed in production facilities, automata and databases.

Métricas y mejoras

Metrics and Improvements

The system processes the information in real time and generates an analytical model that allows, depending on the process to be optimised, to act directly on the production equipment in order to minimise costs, report focuses on energy costs and inefficient processes or reorganise production planning. All this guaranteeing the production requirements and minimising the associated energy consumption.

Cadena Suministro

SUPPLY CHAIN

OPTIMIZATION

Automatic learning enables patterns to be discovered in supply chain data by applying algorithms that quickly identify the most influential factors for the success of a supply network, while constantly learning in the process.

The system enables demand forecasting with real-time warehouse alerts in anticipation of future supplies and logistical problems.

In addition to optimization and reorganization of routes based on daily production planning, it allows communication with sensors deployed in production facilities, automata and databases.

Métricas y mejoras

Metrics and Improvements

REAL-TIME ROUTING REORGANIZATION

FORECASTING THE DEMAND FOR SUPPLY IN THE SHORT AND LONG TERM

OPTIMIZATION AND INCREASE IN PRODUCTION AVAILABILITY

STOCK REDUCTION AND MAINTENANCE

EXPERTS IN INDUSTRIAL DATA ANALYSIS AND INTEGRATION

COVERING THE ENTIRE PROCESS

Industrial Data Analytics is an industrial analytics solution that includes 3 main modules: 

Data Integration + Big Data Module + Predictive Analytics.

PRODUCTION DATA
INTEGRATION

SPECIALIZED PARTNERS IN PREDICTIVE SENSORS

The system integrates and processes the different information sources of the production line on a Big Data architecture in real time (Automaton Network / Sensors / Databases / IoT Disp. / CMMS/MES/ERP Systems).

BIG DATA
CORE

INDUSTRIAL IOT PLATFORM

Executes vertical predictive analytics and process optimization based on process needs (Predictive Maintenance / Predictive Quality / Energy Efficiency / Supply Chain Optimization).

PRODUCTIVE ANALYTICS
WITH MACHINE LEARNING

PREDICTION ENGINE. MACHINE LEARNING

It also allows the execution of predictive analytics verticals on IoT Platforms or Corporate Management Systems such as: PI Osisoft, Nexus Integra or SAP HANA among others.