Connected Machines (in the field)

Globally connected machines with the purpose of analyzing data for predictive maintenance and enhanced service programs

Background

Globally connected machines with the purpose of analyzing data for predictive maintenance and enhanced service programs for the end customer.
Enabling full-duplex data communication for both collecting and updating the data flows deployed in the gateways.
Equipped with a rugged 3G/4G gateway and Wifi capabilities.

Prerequisites

When having a global base of customers, data communication requires a setup that uses as little bandwidth as possible for updates and data flow configuration changes, taking into account high bandwidth costs and large number of connected machines. Furthermore, the system needs support for several protocols running through the entire fleet of machines, including legacy protocols

Scope

Collect and compute data from machines in the field

Read proprietary protocols from machines operating system
Reformat proprietary data to MQTT for further communication

Reduce bandwidth

Filter data and remove unnecessary tags.
Filter recurrent data before sending and repopulation of data at cloud arrival

Deadband handling (loss of connectivity)

Save expected data if/when the machine loses connectivity.

Anomaly Detection

Simple Anomaly Detection for analyzing known error codes

Notifications

Notification when connectivity is broken
Notification to service system when anomalies are detected

Solution

Crosser Node deployed in the machine gateway:

Using RS323 interface for machine data.
Customized modules for error-code handling and proprietary protocols
Anomaly detection based on error-code data
Email notifications via email delivery service to service personal
SMS notifications if connectivity is broken (RnD)

Crosser Cloud:

Customer organization set up with roles