Five Maintenance Challenges Fiix Asset Health Helps Solve

For maintenance teams, helping prevent equipment failure is rarely as simple as knowing that an asset is important. The real challenge is knowing which assets are developing problems, how serious those problems are, and what action to take before a failure disrupts production.

Many manufacturers still rely on reactive repairs, preventive maintenance schedules, or standalone condition-monitoring tools. These approaches can help keep equipment running, but they can also leave teams working with incomplete information: maintenance happens because the calendar says it is time, or because an asset has already started to fail. The result can be unplanned downtime, emergency repairs, lost production, higher maintenance costs, and resources spent on work that isn’t the highest priority. What high-performance maintenance teams require is a reliable way to anticipate an asset’s true needs, so they can act accordingly and with a minimum of wasted resources.

Fiix Asset Health (opens in new tab), powered by Augury’s Industrial AI Workforce, is designed to help manufacturers move towards this predictive and prescriptive approach. By continuously monitoring critical equipment, validating those findings with human experts, and making work orders and recommendations directly in Fiix CMMS, Fiix Asset Health helps close the gap between knowing there is a problem and doing something about it.

Here are five common maintenance challenges this solution is designed to address.

1. You find out about equipment problems too late

A breakdown is often the final stage of an issue that has been developing for some time. Traditional preventive maintenance can reduce the likelihood of some failures, but fixed schedules do not necessarily reflect the actual condition of an asset. An asset may begin showing signs of degradation shortly after a scheduled inspection or continue operating normally long after maintenance has been performed.

That creates a difficult question for maintenance teams: What is happening inside the asset right now?

Fiix Asset Health uses wireless sensors to collect machine health data, including vibration. temperature, and magnetic flux. That data is analyzed using AI and machine learning models trained on billions of machine operating hours to identify early signs of developing equipment issues.

Now, instead of waiting for a failure or the next scheduled maintenance activity, teams can gain greater visibility into the condition of critical rotating equipment, identify potential problems earlier, and take corrective action.

Fiix Asset Health dashboard monitoring an asset is overheating and notifying the user

2. Your maintenance team is overwhelmed by alerts and competing priorities

Detecting an anomaly is only useful if your team knows what to do about it. In a plant with hundreds or thousands of assets, maintenance teams cannot treat every unusual reading as an emergency. They must distinguish between normal performance variation, an issue that can be monitored without immediate intervention, and a developing failure that requires action. This is where simply adding more sensors or alerts isn’t enough.

Fiix Asset Health combines AI-powered fault detection with validation from certified vibration analysts. When a developing issue is identified, not only is that diagnosis more reliable, but the solution provides actionable recommendations rather than simply telling the team that something looks abnormal.

That can help maintenance and reliability teams focus their resources where they matter most: prioritizing work based on asset health and potential risk instead of treating every alert equally.

3. Machine health insights are disconnected from maintenance execution

One of the biggest challenges with monitoring technology isn’t necessarily detecting a problem. It’s what happens after the problem is detected. If machine health data lives in one system while maintenance planning and execution happen somewhere else, teams will have to manually transfer information, create work orders, communicate recommendations, and track whether the issue was actually resolved. Every handoff creates another opportunity for information to be delayed or lost.

Fiix Asset Health is designed around a connected workflow. When an actionable issue is detected, a work order can be automatically created in Fiix CMMS with the diagnosis and recommended actions. Once the work order has been completed, the information is sent back to Augury. Maintenance teams can then prioritize, plan, and complete the required work within their existing Fiix CMMS workflows.

The goal is to turn machine health insight into maintenance action without requiring teams to build a separate process around the insight.

4. You fix the problem, but don’t know if the fix worked

Maintenance doesn’t end when a repair is completed. After corrective work, teams need confidence that the underlying issue has been resolved and that the asset has returned to normal operating conditions. Otherwise, a problem can remain hidden until the equipment fails again.

Fiix Asset Health continues monitoring equipment after repairs. The system can verify whether the issue has been resolved and whether the equipment has returned to normal conditions.

This creates a closed-loop approach:

Detect → diagnose → act → verify → continue monitoring

Rather than treating a work order as the end of the process, maintenance teams can connect the repair back to the asset’s ongoing health.

5. You want to become more predictive but don’t know how

Moving from reactive maintenance to predictive maintenance is a journey. Not every asset needs the same maintenance strategy. Condition-based monitoring can provide broad visibility across connected equipment, while predictive maintenance can be especially valuable for critical, high-value assets where an unexpected failure carries significant operational consequences.

Fiix Asset Health provides a path for organizations looking to take the next step in maintenance maturity. It combines continuous machine monitoring with AI-powered analysis and human expertise to help identify developing failures and recommend corrective action.

For organizations that are already using condition-based monitoring, this can mean moving beyond simply watching asset conditions toward predicting potential failures. For teams earlier in their reliability journey, it can provide greater visibility into machine health and a more proactive approach to maintenance.

Turning asset health into action

The value of predictive maintenance isn’t simply knowing that an asset is healthy or that it isn’t. It’s being able to understand what is happening, determine what matters, take the right action, and learn from the outcome. That’s the goal behind Fiix Asset Health.

The solution combines wireless machine sensors, AI-powered analytics, human-validated machine health analysis, and Fiix CMMS to create a connected workflow from early issue detection through maintenance execution and ongoing monitoring. For maintenance teams, that means less fixed schedules and reactive responses and more opportunity to plan maintenance around the condition of critical equipment.