Eliminating Downtime with Smarter Asset Reliability Management

Unplanned outages, equipment running inefficiently, and downtime for repairs can cause billions of dollars a year of added costs in manufacturing and other asset- intensive industries. Asset reliability management is the process of ensuring that critical equipment, machinery, and infrastructure is working as intended and is available when needed.

Over the past decade, many enterprises have focused on developing data-driven strategies to predict and prevent failures. From the C-Suite to the plant floor, organizations have invested heavily in digital transformation. However, industry research found that many teams still spend more than 80 percent of their efforts on gathering and organizing data—as opposed to analyzing and applying insights to improve asset reliability.

This level of effort is unsustainable and stands in the way of realizing the potential of your reliability and predictive maintenance investments. But new end-to-end solutions including automated sensing tools, asset reliability software, and AI-driven insights make it easier to bridge the data gap and eliminate surprises.

Barriers to Digital Transformation

Why is data capture and analysis for asset reliability so much work?

There are several compounding factors. First, older equipment isn’t connected to IoT systems and the cost of sensorization and networking these assets is high, meaning many teams still rely on manual condition monitoring rather than automating data collection.

At the same time, many industries are facing labor shortages, aging workforces, and high turnover; they need their maintenance team focused on more skilled and engaging work rather than data capture. And finally, many areas in industrial facilities are unsafe for people while operational, reducing the frequency they can be inspected.

The result? Data capture is often slow, inconsistent, or incomplete. Yet asset reliability management depends on accurate, real-time data at scale. Without it, predictive maintenance strategies fall short, leaving organizations vulnerable to unexpected failures and costly downtime.

Automating Through the Data Gap

Getting through this data gap requires a new way to think about automation. Frequently, the focus is processing data efficiently—using AI to generate insights for asset reliability management, for example. But this doesn’t solve the underlying bottleneck. So how do you effectively automate data collection without breaking the bank or overtaxing your vital teams?

Today, agile mobile robots enable asset reliability solutions with dynamic sensing—automating industrial inspection rounds and gathering asset data when and where it’s needed. This approach helps alleviate the underlying challenges of data capture.

  • Real-Time Data on Legacy Equipment: Robots ensure repeatable and standardized data capture—performing the same inspections consistently on your schedule—making it easier to predict issues without extensive IoT installations.
  • Augmented Workforce: Employees would rather focus on high-value tasks. Using robots for industrial inspections frees employees up to perform analysis, conduct repairs, and solve problems.
  • Safe Conditions: Existing infrastructure may contain dangerous environments—active work cells, areas with high voltage, deafening noise, and other occupational hazards. Robots are able to enter these hard-to-reach and unsafe areas of the facility without waiting for off-hours or routine shutdowns.
  • Contextualized, Customized Data: Robotic data capture makes it easy to understand your data in the context of your entire facility and operations, with the flexibility to add new sensing types and adapt to changes on site.

With the Spot® robot, we built an asset reliability solution that takes the guesswork out of predictive maintenance. First, Spot has the advanced mobility and autonomy to reliably navigate your facility. Second, Spot is equipped with sensors for visual, thermal, and acoustic inspections to capture the relevant asset data. Orbit, our software for fleet management and site awareness, offers a central hub to review data and manage inspections, as well as easy integration to your existing EAM software tools. And finally, our expert support and service teams make implementing and scaling with Spot simple.

Unblocking Asset Reliability KPIs

With over 1,500 robots deployed, our customers are unblocking their data pipeline and converting insights into action. Customers are inspecting thousands of assets every day, moving the needle on their asset reliability KPI metrics, and unlocking inspection ROI.

With Spot and dynamic sensing, you can improve reliability metrics such as:

  • Mean time before failures: Detect issues before they escalate and reduce the risk of failures
  • Mean time between repairs: Monitor known issues and manage risk until planned downtime
  • Overall asset lifespan: Repair rather than replace equipment with data-driven predictive and proactive maintenance, extending asset lifespans and reducing the total cost of ownership.

What can you accomplish with better data? Watch our on-demand webinar and start empowering your asset reliability management program with better data today.