Predictive Maintenance

Global Manufacturer wants to take the lead in real-time remote condition monitoring and predictive maintenance within the process industry.

Free Trial

Background

Global Manufacturer wants to take the lead in real-time remote condition monitoring and predictive maintenance within the process industry. Using anomaly detection algorithms and machine models for predicting and optimizing machine runtime windows.

Prerequisites

Machines are already connected through customers local ethernet. All computing and communication can be initiated and deployed within local gateways or virtual machines. The end-user base i very fragmented in terms of security and architecture. Issues with data access rights, where the machine builder may want more data than the machine owner is prepared to provide. Also fragmented base of protocols and OT-systems running the machines globally.

Scope

Real-time analytics and Machine Models

Running Machine models at the edge for millisecond analysis and anomaly detection
Take action on real-time insights and notify engineers/control board
Horizontal integration to other Machine Execution Systems (MES)

Fragmented Stack of Protocols

Support for proprietary, legacy and future protocols
Reformat legacy protocols to adapt to Cloud provider requirements of IOT data communication

Remote updates and Version control

Ease of use when overview, updating and maintaining global software deployments

Tag Management

Simplified Tag Management due to a huge amount and very fragmented set of tags.

Notifications and Messaging

Integration of real-time messaging to service engineers and OT-systems

Solution

Crosser Node deployed in the machine gateway:

Development of custom modules for proprietary protocols
Connector modules for Amazon Web Services
Deploy Machine Models for Runtime Window Monitoring

Crosser Cloud

Customer organization set up with roles
Resources library setup