- Microsoft Solutions
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Unexpected equipment failures create costly downtime, delayed production, emergency repairs, and frustrated teams. Predictive maintenance uses equipment data, sensors, and AI-powered analytics to identify changes in performance before a failure occurs. AT-NET helps manufacturers and operational businesses improve maintenance planning, strengthen visibility, and make better decisions about critical assets.
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“AT-NET really knows how to cater to their customers. Their Security Services and IT/wiring consulting has really helped us increase productivity, and focus on our business. Great customer service. Will and Chris are the best.”
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Monitor equipment conditions and identify performance changes that may indicate developing mechanical or operational problems.
Use asset condition, risk, and performance data to schedule maintenance before a failure disrupts operations.
Address potential issues earlier and reduce the need for emergency repairs, rushed decisions, and production interruptions.
Bring equipment information, maintenance history, and operational data together for clearer reporting and decision-making.
Monitor vibration, temperature, usage, and other operational indicators to identify changes in asset performance.
Use historical and real-time data to recognize patterns that may indicate developing equipment problems.
Use condition and risk information to schedule maintenance around operational needs instead of relying only on fixed intervals.
Bring asset condition, maintenance status, downtime, and performance metrics together in clear dashboards.
Integrate equipment and maintenance data with business systems while maintaining cybersecurity, access controls, and governance.
Detect Problems Earlier: Identify changes in equipment performance before they lead to failure.
Reduce Unplanned Downtime: Address potential issues before they interrupt production or service delivery.
Improve Maintenance Planning: Prioritize work using condition, risk, and operational impact.
Extend Asset Life: Make better maintenance decisions that support long-term equipment reliability.
Predictive maintenance uses equipment data, condition monitoring, and analytics to identify signs of developing problems before a failure occurs.
Preventive maintenance is usually completed on a fixed schedule. Predictive maintenance uses actual equipment condition and performance data to help determine when maintenance may be needed.
Predictive maintenance can support motors, pumps, fans, compressors, conveyors, production equipment, HVAC systems, and other critical assets, depending on available sensors and data.
Common data may include vibration, temperature, pressure, runtime, energy use, maintenance history, alarms, and other operational information.
In many cases, yes. Data may be connected from sensors, control systems, maintenance platforms, and business applications. The available integration options depend on your current equipment and technology environment.
The investment depends on the number of assets, available sensors, system integrations, reporting requirements, and operational complexity. Organizations that combine predictive maintenance initiatives with ongoing managed IT and cybersecurity services typically invest between $175 and $225 per user per month, while equipment monitoring and implementation costs are scoped separately based on the assets and systems involved.
Meet with our team to review your critical assets, current maintenance processes, operational data, and technology environment. We will help identify practical opportunities to reduce downtime, improve maintenance planning, and strengthen visibility across your operations.
