Turning asset data into maintenance action
15 July 2026 
Manufacturers have invested heavily in condition monitoring, wireless sensors and predictive maintenance technologies, yet many still struggle to turn asset data into meaningful action. At the recent Maintec Exhibition, PWE’s Aaron Blutstein spoke to Michael DeMaria, Director of Product Management, Condition Monitoring and Alignment at Fluke Corporation, about why the next challenge for industry is not collecting more information but turning machine intelligence into maintenance action.
For much of the past decade, manufacturers have been encouraged to collect more data. From Industry 4.0 initiatives and predictive maintenance programmes to the rapid growth of wireless
monitoring, the emphasis has been on creating greater visibility into asset performance. Today, many organisations have access to more machine condition data than ever before.
According to Michael DeMaria, Director of Product Management at Fluke Corporation, the problem is no longer obtaining information. “Industry 4.0 was about gathering data,” he said during Maintec. “Plant and maintenance managers are done gathering data.”
The challenge now is deciding what to do with it. That shift in thinking underpins Fluke Corporation’s strategy as the company continues to bring together technologies acquired over recent years, including Prüftechnik’s alignment and condition monitoring capabilities, the diagnostic expertise developed by Azima, and eMaint, its computerised maintenance management system (CMMS).
Taken together, those technologies reflect what DeMaria sees as the next stage of industrial reliability: connecting machine data, diagnostic insight and maintenance action more effectively than has traditionally been possible.
The issue is becoming increasingly pressing as maintenance teams face a combination of growing data volumes and shrinking resources.
Across industry, experienced personnel are retiring while many organisations struggle to recruit and train replacements. At the same time, monitoring technologies are generating ever larger quantities of information.
Manufacturers therefore face a difficult balancing act. They have more visibility into asset condition than ever before, but often fewer people available to interpret the information and
act upon it.
This is one reason why DeMaria believes discussions around artificial intelligence need to become more grounded in practical outcomes. Customers are tired of hearing the hype,” he said. “If it’s not solving a problem on the plant floor, they’re tired of it.”
For Fluke, the value of AI lies less in the technology itself and more in its ability to simplify complex tasks. The company is developing capabilities designed to help users generate work orders, create standard operating procedures, identify maintenance gaps and access technical information more quickly.
The objective is not to replace maintenance expertise, but to make it easier to use and share. One example DeMaria highlighted is the ability to present information differently depending on the user’s level of experience. A reliability specialist and a newly recruited technician may need access to the same knowledge, but not necessarily in the same format.
Beyond data collection
However, AI represents only part of a wider reliability strategy. A recurring theme throughout the discussion was the need to connect activities that have traditionally operated in isolation.
Condition monitoring systems identify developing faults. Diagnostic tools help explain what those faults mean. Maintenance systems are responsible for ensuring the appropriate actions are taken.
The challenge, according to DeMaria, is bringing those elements together.
This is where eMaint plays an important role within Fluke Corporation’s portfolio. While monitoring technologies can identify emerging issues, maintenance management systems help ensure that corrective actions are planned, executed and recorded. Bringing those functions together helps reduce the gap between recognising a problem and resolving it. The need for that connection has become more apparent as wireless monitoring technologies have matured.
Historically, vibration data might have been collected quarterly or monthly. Wireless sensors have transformed that process, allowing organisations to monitor assets far more frequently and at much greater scale. Yet DeMaria argues that more data does not automatically lead to better decisions.
Fluke was relatively late in bringing its own wireless sensor offering to market, a decision he says was deliberate. The company believed many early systems were effective at collecting information and generating alarms but often provided little guidance on what should happen next. “If you have a machine that’s red, how do you turn it green?” he said. For maintenance teams already stretched for time and resources, that distinction matters. Another source of data is only valuable if it helps solve a problem.
The wireless sensor market also illustrates a broader challenge facing manufacturers. DeMaria noted that there are now dozens of competing technologies available, leaving many organisations uncertain about where to begin. In some cases, companies run multiple pilot projects simultaneously while trying to determine which approach delivers the greatest value
Despite years of discussion around predictive maintenance, many organisations are still at the start of that journey. One of the most common questions DeMaria encounters is simply: where do we start?
The answer depends less on the technology itself and more on the problems a company is trying to solve. Some organisations need better visibility into asset condition. Others need help
analysing data, access to specialist expertise or a clearer way of demonstrating business value. That business dimension is becoming increasingly important. Reliability professionals today often find themselves operating between the plant floor and the boardroom. Beyond identifying equipment issues, they are increasingly expected to demonstrate how reliability initiatives contribute to uptime, productivity, risk reduction and overall operational performance.
For Fluke, that means turning technical information into something that supports decisionmaking at multiple levels of the organisation. The company’s confidence in this area is supported by decades of machine condition data accumulated through the former Azima business. Those records include fault signatures, machine behaviour patterns and corrective actions gathered across 100 trillion test points of asset data, over many years. Today, that information forms part of the foundation for the company’s diagnostic and analytical capabilities.
Looking ahead, DeMaria expects data volumes to continue growing as monitoring technologies become more widespread and more sophisticated. The challenge, however, is unlikely to be a
shortage of information. Instead, the question will be how organisations make use of it. The growth of sensors, software and AI means manufacturers now have unprecedented visibility into the
condition of their assets. Yet visibility alone does not improve reliability. As DeMaria suggests, the real value lies in helping organisations understand what action to take next. In an
industry awash with data, that may prove to be the harder challenge.
For further information please visit: https://www.fluke.com/en-gb