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Predictive Maintenance Market Size, Share & Trends Analysis Report By Component, By Solution, By Service, By Deployment, By Enterprise Size, By Monitoring Technique, By End-use, By Region, And Segment Forecasts, 2023 - 2030
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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.

Predictive Maintenance Market Report Highlights:

Table of Contents

Chapter 1. Methodology and Scope

Chapter 2. Executive Summary

Chapter 3. Predictive Maintenance Market Variables, Trends & Scope

Chapter 4. Predictive Maintenance Market Component Outlook

Chapter 5. Predictive Maintenance Market Solution Outlook

Chapter 6. Predictive Maintenance Market Service Outlook

Chapter 7. Predictive Maintenance Market On-premise Outlook

Chapter 8. Predictive Maintenance Market Enterprise Size Outlook

Chapter 9. Predictive Maintenance Market Monitoring Technique Outlook

Chapter 10. Predictive Maintenance Market End Use Outlook

Chapter 11. Predictive Maintenance Market: Regional Outlook

Chapter 12. Competitive Landscape

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