Operational
predictive maintenance software retrieve multiple data sources in real time to
predict quality issues or asset failure. Adoption of these software solutions
facilitate organizations to prevent downtime and reduce maintenance costs.
Operational predictive software solutions detect failure patterns and minor
anomalies to determine the assets and operational processes that are at the
greatest risk of failure. Deployment of operation predictive maintenance
software boosts equipment uptime and enhance supply chain processes and quality.
One of the major factors for the increasing usage of these software solutions
is their ability to accurately predict asset failure, enabling enterprises to
take the asset out of production ensuing efficient supply chain.
Operational Predictive Maintenance Market: Drivers
The
operational predictive maintenance market has been experiencing massive growth
in the recent years due to rise in demand for transforming maintenance
operations and reducing asset downtime. Moreover, steadily rising dependence on
big data and emerging concepts such as the Internet of Things (IoT) coupled
with the rising focus of organizations on cutting back on operational cost is
further expected to fuel the growth of operational predictive maintenance
market during the forecast period. However, lack of training for operators and
lack of trust in predictive maintenance technology is hindering the market
growth. Increasing demand for real time steaming analytics and increasing
demand from small and medium enterprises (SMEs) is expected to create huge
opportunities for the companies operating in operational predictive maintenance
market.
Operational Predictive Maintenance Market: Segmentation
The
global operational predictive maintenance market is segmented on the basis of
components, deployment type, application, and geography. Based on the
component, the global operational predictive maintenance market is classified
into solutions and services. Further, services segment is further categorized
into system integration, training and support, and consulting. Based on
the deployment type, the global operational predictive maintenance market is
further segmented into cloud-based and on-premise.
Among
these, cloud based operational predictive maintenance solutions market is
expected to show swiftest growth enabling enterprises to reduce their
dependence on data mining specialists, data integration and IT. In terms of
application, the market is segmented automotive, energy and utilities,
healthcare, manufacturing facilities, government and defense and transportation
and logistics. Among these, manufacturing facilities are expected to hold the
major market share for operational predictive maintenance market due to high
deployment rate by manufacturers to reduce the maintenance cost consequently
increasing the profitability.
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Operational Predictive Maintenance Market: Regional Dynamics
On the
basis of geography, the global operational predictive maintenance market is
segmented into North America, Europe, Asia Pacific, Latin America, and the
Middle East and Africa. Among these, North America is expected to lead the
operational predictive maintenance market in 2016. The growing big data market
and high adoption of IoT are contributing to the growth for operational
predictive maintenance market in the North America region. Moreover, heavy
investments made by countries such as China, Japan, Korea, and India in
Asia-Pacific to enhance the efficiency of production assets is further expected
to offer sufficient growth opportunities for the operational predictive
maintenance market in this region.
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