Predictive Maintenance Platform

• Completes an end-to-end predictive maintenance once supplied with right inputs (can also be used merely for descriptive purposes, i.e. to collect, organise, and visualise industrial IoT data, without any predictive model)
• Ability to auto-scale with demand

Input(s):

• Sensor readouts
• Failure data
• Service records

Main feature(s):

• Flow-based programming UI
• Customisable charts & dashboard
• Callable RESTful API
• Ability to define endpoints for IoT, edge device and gateway
• Cloud based; multi-tenant Web application

Output(s):

• Remaining Useful Life in time unit
• Probability of Failure in percentage
• Alerts, self-updating visuals
• Machine Learning Model results

• Platform requires minimum configuration during set-up
• Docker-based; also an enabler for local cloud implementation
• Input data in JSON format

Cyber physical system operator; Manufacturing Execution System; (MES) vendors; Operation and Maintenance teams; End-user (maintenance engineer).

Licensing