Predictive Maintenance Market is anticipated to generate a revenue of USD 15487 million by 2026, exhibiting a CAGR of 25.9% during forecast period., owing to the growing demand for predictive maintenance by plant owners, operators, and equipment manufacturers to minimize the ownership and maintenance cost.

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Key Drivers

Increasing application of predictive maintenance in the manufacturing, aerospace, energy, defense, and transportation industry is one of the major factors fueling the global predictive maintenance market. Growing application of predictive maintenance services for more effective and improving the up time of equipment by detecting potential issues is projected to offer enormous opportunities to the market. Besides, with the growing data volume across organizations, the need of real-time streaming analytics to process and analyze data has increased, thereby driving the market size.

Moreover, the rising deployment of predictive maintenance in tomography, X-ray, and mammography to strengthen decision-making capabilities and operational efficiencies are projected to expand the market growth. The growing use of machine-to-machine (M2M) communication and cloud technology to examine the information derived from industrial assets and the increasing adoption of artificial intelligence (AI) technology to transform data produced by various components of the internet of things (IoT) ecosystem into meaningful insights, will further augment the market growth. Besides this, strong investments in predictive maintenance to increase the life of aging industrial machinery and growing demand for predictive maintenance to trace distant working and asset management will offer enormous opportunities to the market. Besides this, the growing adoption of real-time streaming analytics technology across different organizations to process and analyze data records have strengthened the market growth. Factors including the need to expand the lifespan of ageing industrial machinery, reduce maintenance costs, extend asset uptime, have increased the investment in predictive maintenance which will propel the market growth. However, inadequate availability of skilled workforce with knowledge about operating the predictive maintenance solution is a major challenge faced by the organizations, which might hamper the predictive analytics market size.

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End-User Segment Analysis
Manufacturing segment is forecast to lead the predictive maintenance market over the upcoming years, owing to the advent of fourth industrial revolution. The emerging need for maintenance of manufacturing equipment including machinery, elevators, industrial robots, and pumps to minimize the downtime and increasing adoption of automation in manufacturing sector will boost the market growth.

Energy and utilities industry is anticipated to expand at a faster CAGR in the predictive analytics market over the forecast period, due to the accelerating penetration of power consumption analytics. The growing need to improve equipment up-time by analyzing issues prior to their occurrence will bolster the market growth.

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Regional – Segment Analysis:

Asia Pacific is estimated to hold the largest share during the forecast period. The growth can be attributed to the growing investment by public and private sectors to upgrade asset maintenance solutions and easy availability of cheap labor in the region. Furthermore, growing concerns pertaining the overall downtime and operational costs in manufacturing plants has encouraged the plant owners to deploy these solutions, bolstering the regional growth.

North America will hold a larger share over the forecast period because of the early adoption of advance predictive maintenance solutions. Besides this, the existence of a large number of leading solution and service providers and intensified investments made on emerging technologies such as artificial intelligence, IoT, and machine learning are predicted to strengthen the regional growth.

Top Market Players

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.

Key Developments:

• • In 2021 – Spanish technology company Ingeteam declared the innovation of a latest tool that incorporates all its predictive maintenance products and services under a single brand. Ingepredict is attributed to increase the production and extending the service life of assets at industrial and renewable energy generation plants, with main motive to facilitate poor maintenance, early detection of faults, or any other deviation that could lead to unplanned downtime.
  • In 2021, Schneider Electric innovated EcoStruxure™ TriconexTM Safety View, the industry’s first dual safety- and cybersecurity-certified bypass and alarm management software application to facilitate operators witness the bypass status that influences the level of risk reduction in place, and alarms needed to operate the plant safely when risks are high.
  • In 2021, SAS Institute introduced its SAS Viya platform to strengthen the foundation for data and analytic success by integrating new data management solutions into its powerful, cloud native SASViya platform.

Segments covered in the Report:

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

Global Predictive Maintenance Market by Application

• Monitoring
• Decision Making

Global Predictive Maintenance Market by End Use

• Automotive
• Transportation
• Aerospace and Defence
• Others

Global Predictive Maintenance Market by Region

• North America Predictive Maintenance Market (Option 1: As a part of the free 25% customization)
• • By Application
  • By End Use
  • US Market All-Up
  • Canada Market All-Up

• Europe Predictive Maintenance Market (Option 2: As a part of the free 25% customization)
  • By Application
  • By End Use
  • UK Market All-Up
  • Germany Market All-Up
  • France Market All-Up
  • Spain Market All-Up
  • Rest of Europe Market All-Up

• Asia-Pacific Predictive Maintenance Market (Option 3: As a part of the free 25% customization)
  • By Application
  • By End Use
  • China Market All-Up
  • India Market All-Up
  • Japan Market All-Up
  • Rest of APAC Market All-Up

• RoW Predictive Maintenance Market (Option 4: As a part of the free 25% customization)
  • By Application
  • By End Use
  • Brazil Market All-Up
  • South Africa Market All-Up
  • Saudi Arabia Market All-Up
  • UAE Market All-Up
  • Rest of world (remaining countries of the LAMEA region) Market All-Up

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