Machinery Health Moves Toward an Integrated Future

The process industries rely on high-performing equipment to meet ever-increasing goals in support of their organizations. Unaddressed equipment issues can lead to costly repairs or replacements and create safety issues.

As experienced maintenance personnel retire in droves, creating a skilled worker shortage, few plants can continue to rely on manual maintenance checks to ensure equipment runs at its best. To close the gap, plants will continue the move to automated asset management, which will optimize maintenance planning and reduce costs through early diagnosis and analytics-based decision support for developing issues.

However, asset management technologies implemented without a plan have the potential to generate problems that complicate maintenance in new ways. To avoid these problems, organizations striving for the best performance must carefully plan system implementation based on a foundation of integration—among technologies and key stakeholders, and with business enterprise systems.

The rise of data

Rapid decreases in the cost of sensing technologies have made it fast and easy to instrument nearly everything in the plant. Maintenance teams are quickly shifting critical, and even balance-of-plant equipment, from the list of assets needing routine in-person monitoring to a more automated monitoring strategy (Figure 1).

Teaching technologies to communicate

Today’s asset management is about more than identifying a spike in vibration or temperature on a piece of equipment. Plant personnel also must focus on asset interaction and how those interactions affect production. For example, what if a vibration increase only occurs when another piece of equipment upstream is in a certain state? Or, what if a temperature spike only happens on Thursdays at 4:00 p.m.?

To investigate these multivariate issues, personnel must be aware of all relevant variables, and even the most skilled technicians cannot be in two places at once. Instead of waiting for a new generation of technicians to come up to speed and manually cover every asset, tomorrow’s maintenance teams will rely on integration among all the devices monitoring plant assets, so their results can be viewed, compared, and trended in one place.

When different devices operate using different protocols, guidelines, and software packages, operators and technicians are left running between pieces of equipment or switching between many different systems, some in different areas of the plant. This style of work slows responses and significantly limits return on investment (ROI) for asset management technologies. The solution lies in integrating data from a wide variety of devices using a shared technology architecture. Doing so requires open technology standards for asset monitoring. Many of these standards are currently in their infancy, but even these early open technologies are already significantly impacting the way organizations design automated monitoring systems.

To speed ROI, plants are turning to machinery health software packages that can collect data from many types of devices, perform local analysis, and export critical values (lead photo). These software packages analyze aggregated data from multiple monitoring technologies to make an early diagnosis of developing issues and to help users identify root causes and isolate problems before they become severe. Information is presented intuitively in a single location, so users do not need to search through mountains of data, potentially in a variety of disparate systems.

As more plants embrace the integrated data foundation, industry will share machinery health data exported via OPC UA in data repositories, such as data lakes, where it can be combined with metadata, process data, historian data, and more. Such systems can quickly turn raw data into the highly contextualized information plant personnel need to improve performance, efficiency and safety.