Predictive Maintenance Market To Reach $60.13 Billion By 2030

Predictive Maintenance Market Growth & Trends

The global predictive maintenance market size is projected to reach USD 60.13 billion by 2030, registering a CAGR of 29.5% from 2023 to 2030, according to a new study by Grand View Research, Inc. The advancement in technologies such as AI and ML has been a major factor in driving the growth of the predictive maintenance market over the forecast period. AI and ML technologies enable analysing historical data, identifying patterns, and offering accurate machine failure and maintenance predictions. AI technology will continue to improve over time as it receives more data, thereby helping improve the accuracy and reliability of predictive maintenance solutions, which would help companies reduce machinery breakdown and halt production, which helps improve operational efficiency and productivity.

The application of predictive maintenance solutions in industries such as healthcare, energy, transportation, and others has been another major factor driving the market's growth, as many companies started recognizing the potential benefits of installing predictive maintenance solutions. Companies are opting for digital transformation to ensure operational excellence; this trend will further accelerate the adoption of the predictive eminence solution, which is integrated with technologies such as IoT, AI, and ML. However, this limitation includes concerns regarding data price, complex interaction processes, and skill gaps, among others.

The predictive maintenance solution providers have been constantly improving the functionalities of the offering, which has been gaining traction in the market. Integrated platforms, such as a combination of predictive maintenance systems and smart technologies such as asset management, enterprise resource planning, and condition monitoring, are witnessing increased consumer adoption rates. The availability of such solutions would enable businesses to facilitate data-driven decision-making, improve efficiency; productivity, and optimize resources, among others.

The advancement in cloud computing technologies has positively impacted the predictive mainline market, as cloud-based solutions offer scalability and flexibility in managing infrastructure and processing a large amount of data generated by the sensors integrated into the machinery. The delivery of cloud-based predictive maintenance solutions has made them more accessible to a wider range of audiences, especially SMEs, owing to eliminating the cost of IT infrastructure requirements. Another major trend in the predictive maintenance market is the integration of technologies such as AR and VR, which enable technicians to visualize the health data of the equipment and repair & maintenance procedures to be followed. AR and VR tools further help improve the efficiency and effectiveness of the repair works by reducing the chances of error.

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Predictive Maintenance Market Report Highlights

• The service segment is projected to witness the highest CAGR of 31.0% from 2023 to 2030. The growth of the service segment can be attributed to service providers using numerical evaluation to create predictive models that predict equipment breakdowns and servicing needs.

• The integrated segment is projected to witness the highest CAGR of 29.5% from 2023 to 2030. The growth of the integrated segment can be attributed to ERP and CRM integrated solutions enabling improved efficiency and productivity.

• The training & consulting segment is projected to witness the highest CAGR of 31.5% from 2023 to 2030. The growth of the training & consulting segment can be attributed to a customized predictive maintenance strategy to enable catering to a wide range of businesses considering factors such as the machinery being used, maintenance information, and workflow, among others.

• The cloud segment is projected to witness the highest CAGR of 37.9% from 2023 to 2030. The growth of the cloud segment can be attributed to the ability to analyse large volumes and data and offer accurate information on the expected machinery failure maintenance/repair schedule, among others.

• Small and medium enterprises are projected to witness the highest CAGR of 31.6% from 2023 to 2030. The small and medium enterprises' growth can be attributed to the lower cost of cloud-based predictive maintenance solutions, enabling small and medium enterprises to avoid upfront investment into IT infrastructure.

• The oil analysis segment is projected to witness the highest CAGR of 31.5% from 2023 to 2030. The growth of the oil analysis segment can be attributed to information provided by the predictive penitence solution, including oil change, contamination, and changes in other chemical properties, among others.

• The aerospace & defense segment is projected to witness the highest CAGR of 30.6% from 2023 to 2030. The growth of the aerospace & defense segment can be attributed to AI and ML integrated predictive maintenance solution ability to proactively monitor the health of the asset, predict potential failure, and schedule repair & maintenance, among others.

• The Asia Pacific region is projected to witness the highest CAGR of 31.8% from 2023 to 2030. The growth of the Asia Pacific region can be attributed to increasing purchasing power, improving digital infrastructure, availability of cheaper predictive mainline solutions owing to the easy availability of raw materials, and advancement in 5G technology, among others.

• The companies in the predictive maintenance market have been coming up with strategic initiatives such as partnerships and mergers, among others, aimed at gaining traction in the market. For instance, in February 2023, Boon Logic, a provider of AI-based solution detectors, partnered with Software AG as a Premier member of the latter company’s PartnerConnect partner program to provide AI-enabled high-speed prediction service conditions for all complex assets. Through this partnership, the firms aimed to provide valuable insights related to the health and status of equipment to avoid failures.

Predictive Maintenance Market Segmentation

Grand View Research has segmented the global predictive maintenance market on the basis of component, solution, service, deployment, enterprise size, monitoring technique, end use and region:

Predictive Maintenance Component Outlook (Revenue, USD Billion; 2018 - 2030)

• Solution

• Service

Predictive Maintenance Solution Outlook (Revenue, USD Billion; 2018 - 2030)

• Integrated

• Standalone

Predictive Maintenance Service Outlook (Revenue, USD Billion; 2018 - 2030)

• Integration and Deployment

• Support & Maintenance

• Training & Consulting

Predictive Maintenance Deployment Model Outlook (Revenue, USD Billion; 2018 - 2030)

• Cloud

• On-premise

Predictive Maintenance Enterprise Size Outlook (Revenue, USD Billion; 2018 - 2030)

• Small & Medium Enterprises

• Large Enterprises

Predictive Maintenance Monitoring Technique Outlook (Revenue, USD Billion; 2018 - 2030)

• Torque Monitoring

• Vibration Monitoring

• Oil Analysis

• Thermography

• Corrosion Monitoring

• Others

Predictive Maintenance End Use Outlook (Revenue, USD Billion; 2018 - 2030)

• Aerospace & Defense

• Automotive & Transportation

• Energy & Utilities

• Healthcare

• IT & Telecommunications

• Manufacturing

• Oil & Gas

• Others

Predictive Maintenance Regional Outlook (Revenue, USD Billion; 2018 - 2030)

• North America

  • U.S.

  • Canada

• Europe

  • U.K.

  • Germany

  • France

  • Italy

  • Spain

• Asia Pacific

  • China

  • India

  • Japan

  • Australia

  • South Korea

• Latin America

  • Brazil

  • Mexico

  • Argentina

• Middle East & Africa

  • UAE

  • Saudi Arabia

  • South Africa

List of key players of Predictive Maintenance Market

• Accenture plc

• Cisco Systems, Inc.

• General Electric

• Honeywell International Inc.

• Hitachi, Ltd.

• IBM Corporation

• Microsoft

• PTC

• Robert Bosch GmbH

• Rockwell Automation

• SAP SE

• SAS Institute

• Schneider Electric SE

• Siemens

• Software AG