Predictive Maintenance Market to Explode at 35.1% CAGR Over 2024-2029 - Adoption of Industry 4.0 and Digital Transformation Initiatives Driving Demand


Dublin, May 09, 2024 (GLOBE NEWSWIRE) -- The "Global Predictive Maintenance Market by Component (Hardware, Solution (Deployment Mode), & Services), Technology, Technique (Vibration Analysis, Infrared Thermography, Motor Circuit Analysis), Organization Size, Vertical, & Region - Forecast to 2029" report has been added to ResearchAndMarkets.com's offering.

The global predictive maintenance market is valued at USD 10.6 billion in 2024 and is estimated to reach USD 47.8 billion in 2029, registering a CAGR of 35.1% during the forecast period. The continuous advancements in big data, Machine-to-Machine (M2M) communication, and cloud technology have opened up new possibilities for analyzing information derived from industrial assets. IoT devices generate vast amounts of data from diverse sources like sensors, cameras, and interconnected devices. However, this data alone lacks value until it is transformed into actionable, context-rich information. Big data analytics and data visualization techniques empower users to uncover fresh insights through batch processing and offline analysis.



While real-time data analysis and decision-making are often manual, automating these processes is preferred for scalability. AI technology plays a crucial role in analyzing the extensive data volumes generated by various components of the IoT ecosystem and converting them into meaningful insights. Enterprises are integrating AI into their established analytical frameworks to automate data interpretation and gain real-time insights from IoT-generated data. AI equips enterprises with frameworks and tools to analyze real-time data and discover multiple use cases for IoT applications.

By component, the solution segment is projected to hold the largest market size during the forecast period

Predictive maintenance solutions have emerged as indispensable components for numerous successful and large enterprises, given the challenges they face in monitoring asset conditions using traditional maintenance methods. Moreover, these solutions offer real-time asset monitoring, a significant advancement over rule-based maintenance approaches, allowing organizations to adopt proactive maintenance strategies that reduce costs, minimize downtime, and optimize operational maintenance processes.

The solutions market is categorized into standalone and integrated offerings, with integrated solutions experiencing substantial demand due to their comprehensive functionality and widespread adoption across diverse sectors and regions. Integrated software, offering both single and multi-functional capabilities, has gained popularity over standalone software, which lacks customization capabilities but remains prevalent in small and mid-sized enterprises due to its affordability.

By Technology, Artificial Intelligence is registered to grow at the highest CAGR during the forecast period

AI technology plays a significant role in predictive maintenance by leveraging advanced algorithms and machine learning models to analyze data and predict potential equipment failures before they occur. This technology enables organizations to move from reactive maintenance to proactive and even predictive maintenance strategies, ultimately improving asset reliability, reducing downtime, and optimizing maintenance costs. Examples of AI technology in predictive maintenance include the use of predictive modeling techniques such as regression analysis, decision trees, and neural networks to forecast equipment failures based on historical data patterns.

AI-powered anomaly detection algorithms can also identify abnormal behavior in real-time sensor data, allowing for timely intervention and preventive maintenance actions. Additionally, AI-driven condition monitoring systems utilizing IoT sensors can continuously monitor equipment health and performance metrics, providing early warnings of potential issues and enabling predictive maintenance scheduling. These AI technologies empower organizations to transform their maintenance practices, enhance operational efficiency, and drive better business outcomes.

Asia Pacific is projected to witness the highest CAGR during the forecast period

Asia Pacific has witnessed advanced and dynamic adoption of new technologies and is expected to record the highest CAGR during the forecast period. The commercialization of IoT technology and the need for further advancements to leverage the technology to the best are expected to drive the adoption of predictive maintenance solutions in the region. The region includes major economies, such as China and Japan, which are expected to register high growth in the predictive maintenance market. Verticals, such as energy and utilities, transportation and logistics, and healthcare and life sciences, are expected to adopt predictive maintenance solutions and services at the highest rate in the region.

Companies operating in Asia Pacific would benefit from the flexible economic conditions, industrialization- and globalization-motivated policies of the governments, as well as from the growing digitalization, which is expected to have a huge impact on the business community. Other countries in the region, such as South Korea, Singapore, Hong Kong, and Malaysia, are exploring ways to integrate predictive maintenance solutions and services. The countries considered for the analysis of the Asian predictive maintenance market are China, Japan, India, Bangladesh, and the rest of Asia Pacific.

Research Coverage

The market study covers predictive maintenance across segments. It aims at estimating the market size and the growth potential across different segments, such as component (hardware, solution [by deployment mode] & services), technology, technique, organization size, vertical and region. It includes an in-depth competitive analysis of the key players in the market, along with their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.

Major vendors offering predictive maintenance hardware, solution and services across the globe are IBM (US), ABB (Switzerland), Schneider Electric (France), AWS (US), Google (US), Microsoft (US), Hitachi (Japan), SAP (Germany), SAS Institute (US), Software AG (Germany), TIBCO Software (US), Altair (US), Oracle (US), Splunk (US), C3.ai (US), Emerson (US), GE (US), Honeywell (US), Siemens (Germany), PTC (US), Dingo (Australia), Uptake (US), Samotics (Netherlands), WaveScan (Singapore), Quadrical Ai (Canada), UpKeep (US), Limble (US), SenseGrow (US), Presage Insights (India), Falcon Labs (India).

Key Attributes

Report AttributeDetails
No. of Pages377
Forecast Period2024 - 2029
Estimated Market Value (USD) in 2024$10.6 Billion
Forecasted Market Value (USD) by 2029$47.8 Billion
Compound Annual Growth Rate35.1%
Regions CoveredGlobal

Premium Insights

  • Adoption of Industry 4.0 and Digital Transformation Initiatives Across Industries to Drive Market
  • Services to Grow at Highest CAGR During Forecast Period
  • Solutions and Energy & Utilities to Account for Largest Shares of North American Market in 2024
  • North America to Account for Largest Share in 2024

Market Dynamics

  • Drivers
    • Increasing Use of Emerging Technologies to Gain Valuable Insights
    • Advent of ML and AI
    • Rising Internet Proliferation and Growing Use of Connected and Integrated Technologies
  • Restraints
    • Lack of Skilled Workforce
    • Data Security Concerns
  • Opportunities
    • Real-Time Condition Monitoring to Assist in Taking Prompt Actions
    • Growing Need to Reduce Maintenance Cost, Equipment Failure, and Downtime
  • Challenges
    • Frequent Maintenance and Upgradation Requirements
    • Ownership and Privacy of Collected Data

Case Study Analysis

  • Riyadh Airport Modernized Maintenance by Implementing Maximo and IBM Cognos Analytics
  • VPI Enhanced Efficiency of Its Combined Cycle Gas Turbine Plant with IBM Maximo Application Suite
  • Western Digital Boosted Manufacturing Excellence with SAS Asset Performance Analytics
  • Vantage Power Accelerated Predictive Maintenance for Connected Vehicles with VPVision
  • SAM4 Health Prevented Costly Downtime with Predictive Maintenance Alerts

Companies Featured

  • Becton, Dickinson and Company
  • ICU Medical, Inc.
  • B. Braun Melsungen AG
  • JMS Co. Ltd.
  • Baxter International, Inc.
  • West Pharmaceutical Services, Inc.
  • Corning Incorporated
  • Terumo Corporation
  • Cardinal Health, Inc.
  • Equashield LLC
  • Simplivia Healthcare Ltd.
  • Yukon Medical
  • Codan Medizinische Gerate GmbH
  • Vygon SA
  • Practivet, Inc.
  • Elcam Medical
  • Caragen Ltd.
  • Corvida Medical
  • Victus, Inc.
  • Epic Medical
  • Eraser Medical
  • Needleless Corporation
  • Amsino International, Inc.
  • Insung Medical Co. Ltd.
  • Advcare Medical, Inc.

For more information about this report visit https://www.researchandmarkets.com/r/nz2yxb

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Global Predictive Maintenance Market

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