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.).​

quaility-control

process quality

predictive system

(NOK vs. OK Production )

System that integrates different sources of process information to generate predictive models that allow to identify when the facilities are going to produce elements with quality defects before this occurs.

The objective is to make a small so that the machine continues its process within the quality standards.

Métricas y mejoras

Metrics and enhancements

The system processes the information in real time and generates an analytical model that allows, depending on the process to be optimized, to act directly on the production equipment to minimize costs, to report on energy expenditure and inefficient processes or to reorganize the production planning. All this while guaranteeing the production requirements and minimizing the associated energy consumption.

Energy efficiency

with Machine Learning

Machine learning system developed to optimize and minimize energy consumption associated with distributed processes or production facilities.

The integrated system monitors multiple data sources such as process information, consumption, demand forecasts and external data such as energy prices.

Métricas y mejoras

Metrics and enhancements​

The system integrates the process data by accessing the different information sources of the factory (Sensorics, Databases, PLCs, Maintenance and Excel reports, CMMS systems, MES, ERP, SCADA, etc.).

Optimizacion-Energetica

PRODUCTION

PLANNING SYSTEM

Tailor-made system for automatic production planning and maximization of resources.

Customized for each specific production process taking into account the different parts of the process (orders, raw materials, stocks, production and human resources, work orders, deliveries, etc.).

Métricas y mejoras

Metrics and enhancements​

The system can greatly reduce incidents related to process quality. It can reduce up to 35% the generation of NOK products with any quality defect, or the optimization of inefficient processes that produce a higher cost of raw materials, energy consumption or process times.

FORECASTING THE DEMAND FOR SUPPLY IN THE SHORT AND LONG TERM

OPTIMIZATION AND INCREASE IN PRODUCTION AVAILABILITY

REAL-TIME ROUTING REORGANIZATION

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.