Machinery Health Moves Toward an Integrated Future

An interconnected workforce

Collaboration is key to plant health. Whether maintenance personnel are standing next to each other at an asset or relaying important workflow steps from a corporate headquarters miles away, success is directly related to the ease with which they can share data, advice, and awareness. As staffing shortages escalate and plants are forced to accomplish more with fewer people, industry will continue to build comprehensive collaboration platforms to extend the reach of expert personnel without the delay, cost, and hassle of travel.

To empower smaller workforces, organizations will leverage persona-based machinery health software to help mobile workers more easily identify problems. With persona-based platforms, users receive only the data relevant to their roles, so they do not miss critical issues buried under alerts and alarms more relevant to other personnel. Critical asset health information is clearly highlighted on intuitive graphical dashboards, showing machinery health status at a glance.

Improving the view from above

Key performance analytics start at the plant level—where the processes, equipment, and systems reside and interact. But even plant-level analytics are driven by corporate initiatives. As these plant-level initiatives show ROI, many organizations will begin to expand their reach, performing analytics across plants on similar assets to gain visibility of higher-level trends. These macro-level analytics require seamless integration to business systems, many of which reside in the cloud.

In the past, getting plant data to enterprise systems required infrastructure—hardware, software, and a reliable backbone of network equipment—all of which needed a skilled information technology (IT) staff to manage. But today, many of the tools plants rely on to aggregate and contextualize machinery health data are either cloud ready or entirely cloud based.

Machinery health platforms will play a key role in the transition to cloud platforms, acting as translation packages to help make device data cloud ready. As industry continues to embrace the cloud for macro-level analytics, it will rely heavily on machinery health applications. These platforms will collect crucial data from sensors and export it via application programming interfaces and open protocols, such as OPC UA, to data repositories where it can be accessed by cloud systems.