Expectations for EAM systems have heightened over the past decade, particularly during the past few years. As maintenance management processes become more sophisticated, connectivity and interoperability are increasing visibility into the condition of critical equipment and systems. At the same time, sensors are becoming more powerful and less expensive, and prediction capabilities are much more accurate and user friendly.
Adding to the mix is the accelerated need for capabilities like remote monitoring and management brought on by the COVID-19. The pandemic has accelerated the timeline, and many remote management and other digital transformation initiatives have been accelerated by as much as two-to-five years.
EAM Systems in Transition
Much has changed over the past few years in the EAM market. The transition from single-site CMMS and traditional EAM systems with a focus on work planning and scheduling has evolved. While many EAM systems have traditionally been reactive, there is an industry-wide movement to offer real-time insight into needed tasks, leading to accelerated adoption of automated and intelligent EAM business processes and systems.
At the same time, various maintenance philosophies continue to exist and evolve. These range from run-to-failure to corrective maintenance, preventive maintenance (based on such factors as time, miles/kilometers, engine hours, and other parameters), and predictive (increasingly including some form of predictive maintenance and/or predictive analytics), and in some cases prescriptive maintenance. Together, this broad array of information can shed light not only on what has occurred, but also in what is occurring, and increasingly – what is likely to occur, and when it might occur.
Maintenance and operations teams continue to encounter new challenges. As a result, today’s EAM solutions are more capable and offer robust work management capabilities like job, PM, and safety plans, inventory management, predictive maintenance, and enhanced integration and interoperability capabilities. For end users, not only must these systems be available 24/7, they must operate and manage in challenging, and often harsh environments.
All of this is occurring while plants are ramping-up their digital transformation efforts to leverage analytics, AI, ML, Industrial IoT, and enterprise-wide connectivity to better monitor and manage critical assets. Industrial IoT in particular can be an important conduit from which maintenance and operations teams consider how best to incorporate such capabilities as autonomous or semi-autonomous operations in plants and other industrial facilities.
Many Industrial Organizations Are Evaluating Their Digital Transformation Journeys
As organizations continue to seek new and novel ways to improve operational efficiency and asset performance, discussions about the progress of their digital transformation efforts to increase efficiency, productivity, and worker safety are top of mind. And, for an increasing number of firms, their EAM digital transformation journeys are well underway.
To meet these expectations, end users are demanding better ways to connect and communicate, both directly and remotely. This is being accomplished by connecting sensor data distributed via Industrial IoT, from which sensors, networks, and industrial edge devices are linked. This interoperability and data collaboration with other systems, most notably ERP suites, allow advanced EAM solutions adopting more advanced features. Examples of the evolution of asset management capabilities can be seen in the following illustration.
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Keywords: Enterprise Asset Management, EAM, Digital Transformation, IoT, Industrial IoT, Edge Computing, Asset Performance Management, APM, Maintenance, CMMS, ERP, ARC Advisory Group.