Operational predictive maintenance is a service that detects the onset of system degradation; thereby, enabling usual stressors to be eliminated or controlled past any significant deterioration in the physical state of the component. Adoption of operational predictive maintenance software facilitates organizations to reduce maintenance cost and prevent downtime. It further assists the organizations in optimizing supply chain and operation management of products.
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Increasing adoption of cloud-based technologies across various industry verticals such as government and manufacturing has augmented the demand for operational predictive maintenance solution and services. Increasing focus on reducing the cost associated with the maintenance of machines, products, and other assets is fueling the growth in the market across the globe. Moreover, the technological advancement in maintenance solutions such as the deployment of big data and IoT is anticipated to offer a growth opportunity to the market in the near future.
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Global Operational Predictive Maintenance Market Segmentation
By Deployment Model
On-premises
Cloud-based
By Application
Government
Manufacturing
Energy & Utilities
Transportation and Logistics
Others (Healthcare, Aerospace and defense)
Regional Analysis
North America
United States
Canada
Europe
UK
Germany
Italy
Spain
France
Rest of Europe
Asia-Pacific
China
Japan
India
Rest of Asia-Pacific
Rest of the World
Company Profiles
ABB Asea Brown Boveri Ltd.
Accenture PLC
Advanced Technology Services, Inc.
Altizon Systems Pvt. Ltd.
Augury Inc.
Bentley Systems, Inc.
Cisco Systems, Inc.
Eaton Corp.
Embitel Technologies India Pvt. Ltd.
General Electric Co.
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