The global operational predictive maintenance market is growing at a significant CAGR during the forecast period. Operational predictive maintenance is a service that is primarily used to predict asset failure and to predict quality issues in equipment by collecting data from multiple sources in real time. Operational predictive management software detects peculiarity and evaluates failure patterns to determine the assets, equipment and operational process that are at huge failure risk. The primary aspects that are required to perform predictive maintenance include real time data collection, time to failure prediction, resource optimization and scheduled maintenance.

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One of the major factors that is driving the growth of the global operational predictive maintenance market is its ability to precisely predict possible asset failure and to ensure the optimization of supply chain by assisting organizations in removing the prone asset out of production line. Additionally, demand for reducing asset downtime and modification maintenance operations is growing constantly which in turn is rising the demand for these software solutions. Moreover, with the emergence of IoT, continuous adoption of big data is anticipated to propel the market in near future.

Further, the demand from organization for reducing the operational cost is increasing the demand for operational predictive maintenance software. Cutting operational cost assists organizations in increasing their profit owing to which they are constantly adopting operational predictive maintenance software. Heavy investments by Asia-Pacific countries such as India, China, Japan and South Korea to optimize the operation process and enhance the efficiency of production is expected to boost the market of operational predictive maintenance software in the region.Improving economic reforms and an increase in the focus of government towards economic stability are some factors that are considerably propelling the market growth in the region.

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The key players that are dominating the global operational predictive maintenance market include IBM Corp., SAS Institute Inc., Software AG, General Electric Co., Robert Bosch GmbH, Rockwell Automation, Inc., PTC, Inc., and Schneider Electric SE.These players adopt various strategies such as mergers & acquisitions, products, and services offering expansion, geographical expansion, and partnership & collaboration to stay competitive in the market.

Global Operational Predictive Maintenance Market - Segment

By Deployment Model

• On-premises
• Cloud-based

By Application

• Government
• Manufacturing
• Energy & Utilities
• Transportation and Logistics
• Others (Healthcare, Aerospace and defense)

Global Operational Predictive Maintenance Market –Region

North America

• US
• Canada
Europe

• Germany
• UK
• France
• Spain
• Italy
• 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.
• Hitachi Ltd.
• Huawei Technologies Co., Ltd.
• IBM Corp.
• Intel Corp.
• Microsoft Corp.
• PTC Inc.
• Robert Bosch GmbH
• Rockwell Automation, Inc.
• SAP SE
• SAS Institute Inc.
• Schneider Electric SE
• Senseye Ltd
• Siemens AG
• Software AG
• Splunk Inc.

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