Best Practices for Maintaining and Supporting Automated Systems

Executive Summary

As industrial automation grows more advanced and interconnected, maintaining system uptime and reliability becomes mission-critical. Proactive support strategies not only reduce downtime and repair costs but also extend asset life and ensure compliance. This white paper outlines best practices for maintaining and supporting automated systems, including predictive maintenance, digital diagnostics, and remote support technologies.

The Shift from Reactive to Predictive Maintenance

Traditional reactive maintenance—fixing equipment after it fails—results in costly downtime, emergency repairs, and potential safety risks. Progressive manufacturers are shifting toward:

Preventive Maintenance: Scheduled servicing based on usage intervals
Predictive Maintenance: Real-time analytics to anticipate failures before they occur
Prescriptive Maintenance: AI-driven recommendations for corrective action based on root-cause analysis

Key Maintenance Best Practices

Standardize Maintenance Protocols: Develop uniform procedures for inspections, lubrication, calibration, and part replacements across similar equipment types.
Implement Real-Time Monitoring: Deploy IoT sensors to track key metrics—i.e. vibration, motor current, temperature, lubrication pressure—and trigger alerts on threshold deviations.
Digitalize Maintenance Records: Use CMMS or edge-enabled platforms to log service history, spare part usage, and downtime causes to enable trend analysis and compliance.
Establish Remote Diagnostics Capability: Utilize edge and cloud systems to access equipment health data, software logs, and video feeds for remote troubleshooting and support.
Train for Hybrid Skillsets: Upskill technicians in both mechanical and software diagnostics, including PLC fault tracing, sensor calibration, and HMI logic validation.

Support Models to Consider

In-House Maintenance Teams: For high-volume facilities with consistent needs
OEM Service Agreements: For specialized equipment requiring certified expertise
Hybrid Models: Combine internal teams with remote vendor support to balance coverage and cost
Predictive Maintenance-as-a-Service (PMaaS): Outsource analytics and scheduling to a data-driven provider

The Role of Artisan Edge in Automation Support

Artisan Edge enhances support strategies by:

Capturing machine-level sensor data to feed into predictive models
Triggering alerts and maintenance workflows through CMMS or ERP integration
Enabling remote visibility for off-site diagnostics and performance reviews
Providing APIs for closed-loop reporting and compliance documentation

Case Snapshot: Food Packaging Line Optimization

A food manufacturer used Artisan Edge to monitor condition-based indicators on its robotic palletizing system:

42% reduction in unplanned maintenance events
12% increase in asset life due to early intervention
Full traceability of work orders and parts for quality audits

Conclusion

Maintaining automated systems requires more than traditional servicing—it demands real-time visibility, cross-functional training, and digital infrastructure. By adopting these best practices and leveraging platforms like Artisan Edge, manufacturers can ensure reliability, reduce cost, and operate with confidence in a high-performance automation environment.

To modernize your maintenance and support capabilities, contact us at sales@artisantec.io or visit www.artisantec.io.