Predictive Maintenance Market is anticipated to grow at a CAGR of 25.9% during forecast period and estimated to reach USD 15487 million by 2026.

Introduction of Predictive Maintenance Market Report

The maintenance strategy has been classified as corrective maintenance, preventive maintenance, and predictive maintenance. The corrective approach considered with the problem associated with minor faults whereas the predictive maintenance includes the predetermined check for the equipment’s as per scheduled timings. However, the predictive maintenance depends on the technological suggestion to schedule a maintenance task before the major breakdown issues.

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The global market for the predictive maintenance needs, growing significantly owing to the restrict the major damage caused by the breakdown issues. The market driven factors for the global predictive maintenance includes reduction in the operational cost and enhance sustainable production capabilities. In addition, predictive maintenance strategy owes to the reduce the loss of severe damage to machinery as well as the major breakdown issues leading to heavy loss of operating income to the company. In addition, rising demand for the automation implementation requires deep integration of latest technological approach acts as one of the most important demand bolstering factors for the predictive maintenance market around the globe. The implementation of the predictive maintenance requires heavy investment and skilled people which acts as a restraining factor for the preventive maintenance market.

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Various notable players operating in the market, includes IBM Corporation, Microsoft Corporation, SAP SE, General Electric, Schneider Electric, Hitachi, Ltd., PTC Inc., Software AG, SAS Institute Inc., Engineering Consultants Group, Inc., Expert Microsystems, Inc., SparkCognition, C3.ai, Inc., Uptake Technologies Inc., Fiix Inc., Operational Excellence (Opex) Group Ltd, TIBCO Software Inc., Asystom, and Sigma Industrial Precision etc.

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The Global Predictive Maintenance Market has been segmented on the basis of Application, End Use and key geographies. Based on application the market comprises of Monitoring and Decision Making. The research report “Global Predictive Maintenance Market” provides in-depth analysis of global predictive maintenance market based on application, end use and major geographies for the forecast period from 2019 to 2026. The report also highlights the major market drivers propelling the growth as well as challenges faced by market participants. The research report provides market size and forecast for the global predictive maintenance market. In addition, the report also analyses the competitive landscape, major players and their strategies in 2018. The competitive landscape section of the report captures and highlights the recent developments in the market.

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Key questions answered in this research report:
1- At what pace is predictive maintenance market growing? What will be growth trend in future?
2- What are the key drivers and restraints in the current market? What will be the impact of drivers and restraints in the future?
3- What are the regional revenue and forecast breakdowns? Which are the major regional revenue pockets for growth in the global predictive maintenance market?
4- What are the various application areas and how they are poised to grow?

Market Segmentation
• By Application Revenue Forecast till 2026
• Monitoring
• Decision Making
• By End Use Revenue Forecast till 2026
• Automotive
• Transportation
• Aerospace and Defence
• Others

By Geography
• North America
As a part of customization
o By Application
o By End Use
o US
o Canada
o Mexico

• Europe
As a part of customization
o By Application
o By End Use
o UK
o Germany
o Spain
o Rest of Europe

• Asia-Pacific
As a part of customization
o By Application
o By End Use
o China
o Australia
o India
o Rest of APAC

• ROW
As a part of customization
o By Application
o By End Use
o Brazil
o South Africa
o GCC countries
o Rest of world (remaining countries of the LAMEA region)

Leading market players
• IBM Corporation
• Microsoft Corporation
• SAP SE
• General Electric
• Schneider Electric
• Hitachi, Ltd.
• PTC Inc.
• Warwick Analytics
• RapidMiner
• eMaint Enterprises, LLC