Solution

Predictive maintenance is done by periodic or continuous monitoring of machine health through data from critical machine parts and total machine run hours. Data is then fed into a machine learning and prediction engine, which gives statistical data on maintenance tasks that will be needed in the future via SMS and key dashboards.

Places

This technology is used in early fault detection and diagnosis in manufacturing industries, public sector infrastructure and utilities, telecommunication and oil and gas sectors. Enormous amounts of data are collected and analysed, giving the operations team the opportunity to respond to failures before they occur. Replacement parts can be organized according to alarm predictions, and new work orders can be set in existing maintenance platforms for the future tracking and analysis.

Need

Predictive maintenance is extremely valuable in improving overall maintenance and reliability of operations. This technology benefits the manufacturers by minimizing the number of unexpected failures, increasing longevity of the machine, and reducing operational costs by performing maintenance only when absolutely necessary.

Impact

With the help of predictive maintenance technology, optimal operation time can be defined, which leads to low maintenance frequency. It also allows maintenance to be performed only when required, helping facilities cut cost, save time and maximize resources. Predictive maintenance has been shown to reduce maintenance costs by 25%-35%, decrease the number of breakdowns by 70%-75%, and reduce downtime by 35%-45%.