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REACH - complex IoT solution for manufacturing

Real-Time Event based Analytics and Collaboration Hub

 

REACH  is a central data integration, storage and processing system, the technology platform of the smart factory. REACH is collecting and processing huge amounts of data from different sources in order to increase operational efficiency, find savings on energy consumption,  event prognosis (the range of opportunities is endless). Data sources can be sensors, PLC-s, human input or different IT systems e.g. MES/SCADA/ERP.

We combined the knowledge of our best BI experts and engineers with the aim of creatig a robust IOT platform that is capable of real-time, event based operations using the latest available, open source big data technologies. Our customers are the owners of a transparent solution, easy to integrate and scale for their use cases.

 

Main features

  • Device integration layer: sensors, IoT data sources, ERP, SCADA, other structured or non-structured data sources
  • Stream and batch message processing
  • Analytics: algorithms, complex analytics and reports e.g. real time OEE for the production line
  • Scalable big data processing environment
  • Own platform with the minimum necessary TCO
  • Information monitoring on any device
  • Instructions on different user interfaces: andon system, machines, tablet, mobile

Use Cases (Samples)

OEE (Overall Equipment Effectiveness) real-time calculation and visualization for production lines and offices, manager offices.
The OEE is a metric metrics that reports the overall utilization of facilities, is calculated with the formula Availability*Quality*Performance, where Availability= percentage of scheduled time that the operation is available to operate, Performance= the speed at which the production line runs as a percentage of its designed speed), Quality= units produced as a percentage of the units planned.

Energy utilization savings up to 100M HUF/year as a result of real-time analysis of hundreds of sensors
Collecting and analysing used material and external environment parameters in an integrated near real-time monitoring system to optimize energy consumption can lead to 4% of savings, that can be further increased with machine learning algorithms based on the existing statistics.

Predicitve maintenance or scheduled repair based on the real time analysis of production patterns and estimated working time , reduce the number of faulty pieces, avoid non-planned stoppage, environmental damage or prevent workplace accidents. Predictive maintenance is driven by two goals: both right-time intervention to decrease the number of repairs and cost optimization  by optimizing the usage of the equipment.

We developed Mortoff 's competences constiously to answer most of the questions of the Industry 4.0 vision. Our team is built from IT and digital architects, solution engineers, database developers, big data engineers, data scientists, visualization experts, testers and production engineers.

Our products and services

  • REACH complex IoT solution for manufacturing, our central data integration, storage and processing system
  • Software applications working in high quality assurance/safety-related environment (3D/4D image processing, analysis, data processing, workflow support)
  • Development and testing of embedded software (C/C++/Embedded, real-time)
  • Electronic planning and validation (PCB, microcontroller/FPGA, communication)
  • Mechanical planning and validation (CAD-CAM)
  • SENSEoT own device for predictive maintenance
  • Indoor tracking solutions
  • Engineering support for production, project management
  • Complex data analytics and visualization
  • I4.0 strategy consulting
  • Digitalization of industry processes
  • Engineering support in manufacturing
Professional consulting

10+ years of professional experience


5+ successful projects


5+ satisfied clients

Richárd Tunkel, information Technology Director

We experience that only by the understandable and right-time visualization of the existing complex data the process efficiency increases by 5%. This is the first simple but spectacular step. By continuous data analytics activities and with the help of machine learning algorithms the efficiency increase is significant leading to return in competitve advantage of the company.

References

End-to-end solutions

from Mortoff

Our service portfolio, built on the cooperation of our service lines, is able to effectively cover even the most complex client requirements:

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