What keeps you from implementing predictive maintenance?
Interest in predictive maintenance analytics is on the upswing, according to ABI Research. The market intelligence company estimates that the maintenance analytics market will reach $24.7 billion in 2019, driven largely by adoption of predictive analytics and machine-to-machine (M2M) connectivity.
Many different asset-intensive industries recognize the potential benefits of a predictive maintenance strategy—heightened asset availability and reliability, reduced materials and supply inventories, enhanced ability to meet production and budget targets and lessened unplanned downtime. But for some organizations, the need for additional on-premises IT resources to provide such capabilities stands as a barrier to adoption.
To help organizations incorporate predictive analytics into their maintenance practices, IBM offers a cloud-based solution that provides asset performance insight for personnel who are responsible for operating and maintaining critical assets. The IBM solution, which allows the combination of asset maintenance and performance data from disparate sources—whether structured or unstructured—analyzes such data and executes predictive models, based on real-time events, to help anticipate asset failure.
Using predictive models, personnel who are responsible for operating and maintaining critical assets can monitor asset health in real time while enjoying a cloud-based user experience. Additionally, dashboards can provide a high-level summary of the health of all assets at all sites, along with detailed reports showing all data available about asset condition. In doing so, they allow maintenance personnel to forecast degradation and failure, proactively addressing specific problems and optimizing maintenance schedules by using enterprise asset management products such as IBM Maximo Asset Management.
If predictive modeling is not currently part of your maintenance practices, learn more about IBM Predictive Maintenance on Cloud capabilities. Using a cloud-based offering, organizations can accelerate the implementation process, realizing the benefits of predictive analytics without incurring additional IT infrastructure costs.