EACH 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