Predictive Maintenance Market to Hit USD 111.34 Billion by 2030, at a CAGR of 26.2% - Report by Market Research Future (MRFR)

Industry 4.0 Creates Vast Demand for AI-based Predictive Maintenance (PdM)Solutions


New York, US, June 16, 2022 (GLOBE NEWSWIRE) -- According to a comprehensive research report by Market Research Future (MRFR), “Predictive Maintenance Industry Analysis by Component (Hardware, Solution, Services), Testing Type, Deployment Mode, Technique (Traditional Technique, Advanced Technique (IoT/Big Data Technique, Machine Learning Technique) - Forecast 2030” valuation is poised to reach USD 111.34 Billion by 2030, registering a 26.2% CAGR throughout the forecast period (2021–2030). 

Predictive Maintenance Market Overview

Predictive Maintenance (PdM) platform has been gaining significant market prominence over recent years. PdM solutions are integrated with new or existing machinery infrastructure to determine machine health and identify signs of impending deterioration. PdM integration guarantees ROI and enables organizations to meet & exceed sustainability goals, enabling remote machine monitoring globally. 

Predictive Maintenance Market Report Scope:

Report Metric Details
  Market Size USD 111.34 Billion (2030)
  CAGR 26.2% (2021-2030)
  Base Year 2020
  Forecast Period 2021-2030
  Historical Data 2019
  Forecast Units Value (USD Billion)
  Report Coverage Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
  Segments Covered Component, Testing Type, Deployment and Region
  Geographies Covered North America, Europe, Asia-Pacific, and Rest of the World (RoW)
  Key Vendors Uptake Technologies, Oracle Corporation (US), Axiomtek Co. Ltd (Taiwan), Microsoft Corporation (US), IBM Corporation (US), XMPro (US), RapidMiner (US), SAP SE (Germany), Hitachi, Ltd (Japan), Comtrade (Ireland), Software AG (Germany), and C3 IoT (US)
  Key Market Opportunities Advances in technology across industries, expansion of IoT connectivity, and rapid adoption of advanced technologies, particularly machine learning
  Key Market Drivers The increasing adoption of real-time streaming analytics technology

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Proactive maintenance approaches of PdM provide tools to reduce unplanned downtime of equipment critical for production and minimize the time & money spent on repairs and maintenance. Moreover, PdM solutions ensure assets are in optimal working condition and available at all times. Integration of PdM in machinery extends the life expectancy of assets and reduces high maintenance costs that can be costly to businesses.

The predictive maintenance (PdM) market is garnering substantial traction. The rising adoption of PdM solutions in various rapidly growing sectors, such as manufacturing, energy & utilities, and healthcare, boosts the PdM market size. Also, burgeoning industries like automotive and, aerospace & defense are increasingly integrating PdM platforms into their systems, which supports the predictive maintenance market growth further.

Predictive maintenance strategies have emerged as one of the most effective solutions for asset-heavy organizations, offering reduced costs and a greater ROI. Industries leverage the analytical capabilities of PdM to thrive in continually rising volumes, types and complexities of data. Utilities are increasingly implementing PdM solutions to target market strategic framework, impacting the predictive maintenance market growth positively.

Besides, the growing implementations of the Internet of Things (IoT) across end-user verticals worldwide drive the market growth, allowing different assets & systems to connect, synchronize, share, analyze, and act on the data. With substantial R&D investments in the development of PdM solutions, the predictive maintenance market is projected to garner vast gains during the next few years.

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Predictive Maintenance Market Segments

The report is segmented into components, testing types, deployments, techniques, verticals, and regions. The component segment is sub-segmented into hardware, solutions, and services (consulting, support & maintenance, system integration, others). Of these, the hardware segment accounts for the largest market share. The segment is further expected to register the highest CAGR during the assessment period.

The testing type segment is sub-segmented into vibration monitoring, electrical insulation, infrared thermography, temperature monitoring, ultrasonic leak detector, oil analysis, and others. Among these, the vibration monitoring segment accounts for the largest market share. The segment is further expected to register the highest CAGR during the assessment period.

The deployment segment is sub-segmented into on-cloud and on-premise. Among these, the on-premise segment accounts for the largest market share. The segment is further expected to register the highest CAGR during the assessment period.

The technique segment is sub-segmented into traditional and advanced techniques (the IoT/Big Data technique and machine learning-based technique). Of these, the traditional techniques segment accounts for the largest market share. The segment is further expected to register the highest CAGR during the assessment period.

The vertical segment is sub-segmented into manufacturing, healthcare, energy & utility, automotive, aerospace & defense, transportation, and others. Among these, the manufacturing segment accounts for the largest market share. The segment is further expected to register the highest CAGR during the assessment period.

By regions, the predictive maintenance market is sub-segmented into North America, Europe, APAC, and the rest of the world. Of these, North America accounts for the largest market share. The region is further expected to register the highest CAGR during the assessment period.

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Predictive Maintenance Market Regional Analysis 

Globally, North America holds the largest predictive maintenance market share. The presence of leading solution providers investing heavily in R&D to enhance the capabilities and operational efficiency of their solutions drives the market growth. Besides, the growing adoption of advanced technologies in manufacturing industries across the region to halve unplanned downtime and maintenance costs boost the market size. Moreover, the increasing demand for energy & utilities, alongside government initiatives & utility-scale policy, increases the region's market shares.

Predictive Maintenance Market Competitive Analysis

Dominant Key Players in Predictive Maintenance Market Covered are:

  •  Uptake Technologies
  •  Oracle Corporation (US)
  •  Axiomtek Co. Ltd (Taiwan)
  •  Microsoft Corporation (US)
  •  IBM Corporation (US)
  •  XMPro (US)
  •  RapidMiner (US)
  •  SAP SE (Germany)
  •  Hitachi
  •  Ltd (Japan)
  •  Comtrade (Ireland)
  •  Software AG (Germany)
  •  C3 IoT (US)

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Highly competitive, the PdM market appears to be fragmented due to the presence of several well-established industry players. These players initiate strategic approaches such as mergers & acquisitions, collaboration, expansion, and technology launches to gain a larger competitive advantage.

For instance, on June 09, 2022, Siemens Digital Industries announced the acquisition of a Southampton-based machine data firm, Senseye, to expand its innovative predictive maintenance and asset intelligence portfolio. The acquisition would bolster Siemens' digital technology and service offering to the industry. Senseye is now assigned organisationally to Siemens Digital Industries and part of the Customer Services Business Unit.

Senseye is a global industrial analytics software company providing outcome-oriented predictive maintenance solutions for manufacturing and industrial companies. Its predictive maintenance solution enables a substantial reduction in unplanned machine downtimes and increased productivity of maintenance staff. In corporate, Senseye solutions support improved sustainability through increased asset lifetime and waste reduction.

On June 01, 2022, Arrow Electronics/ Altron Arrow (South Africa) announced an alliance with Senseye to deliver AI-based predictive maintenance solutions for industrial sectors. The agreement covering Europe and the EMEA allows companies to bring to market AI & machine learning-powered system monitoring and predictive maintenance solutions for industrial organizations.

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