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AI-driven Predictive Maintenance Market

InsightAce Analytic Pvt. Ltd. announces the release of a market assessment report on the “Global AI-driven Predictive Maintenance Market- (By Solution (Integrated Solution and Standalone Solution), By Industry (Automotive & Transportation, Aerospace & Defense, Manufacturing, Healthcare Telecommunications and Others)) Trends, Industry Competition Analysis, Revenue and Forecast To 2031.”

According to the latest research by InsightAce Analytic, the Global AI-driven Predictive Maintenance Market is valued at US$ 761.04 Mn in 2023, and it is expected to reach US$ 1,868.51 Mn by 2031, with a CAGR of 11.8% during the forecast period of 2024-2031.

AI-driven predictive maintenance services may streamline the process of gaining valuable insights from data on device health and functionality. This, in turn, can enhance dependability and maintenance personnel’s capacity to oversee manufacturing operations overall. Proactive maintenance methods, which can foresee potential equipment issues and optimize maintenance schedules, are becoming more popular, as evidenced by the increasing demand for AI-driven predictive maintenance. Industries are rushing to find AI-powered predictive maintenance solutions to increase asset reliability and productivity and decrease operational expenses. The growth of industry-specific AI algorithms increased public understanding of predictive maintenance’s benefits, and other technological advancements are all driving this expansion. However, Problems with integration and worries about data protection are limiting market growth.

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List of Prominent Players in the AI-driven Predictive Maintenance Market:

• DB E.C.O. Group
• Radix Engineering and Software
• Machinestalk
• KCF Technologies, Inc.
• Infinite Uptime
• OCP Maintenance Solutions
• Emprise Corporation
• ONYX Insight
• Gastops
• PROGNOST Systems GmbH

Market Dynamics:

Drivers-

The growing demand for the AI-driven predictive maintenance market is fueled by the Internet of Things, the necessity to prolong the lifespan of aging industrial gear, and the rising need to maximize asset uptime while minimizing maintenance costs are key factors propelling the predictive maintenance market growth. AI helps locate problems before they become major breakdowns, which helps keep things running smoothly. Because of this, asset uptime is improved, guaranteeing that machinery and equipment are available for operations as required. Predictive maintenance looks at patterns in equipment performance to foretell when maintenance is needed by using data analytics and machine learning algorithms.

Challenges:

The prime challenges are insufficient technological knowledge, a need for more competent individuals, and a lack of norms and protocol because of lockdowns and isolation in emerging countries, which is predicted to slow the growth of the AI-driven predictive maintenance market. Integrating predictive maintenance systems with existing infrastructure and legacy systems is seen as a challenging and time-consuming process, resulting in delayed acceptance and deployment. Implementing AI-driven predictive maintenance necessitates skilled individuals who possess knowledge in maintenance domains in addition to data analytics and machine learning, a combination that is presently lacking. During the COVID-19 epidemic, corporations had to be especially careful with their machinery and equipment to boost production because of a lack of workers, disruptions in the worldwide supply chain, and high demand for diverse items. A worldwide uptick in interest in predictive maintenance solutions followed.

Regional Trends:

The North American AI-driven predictive maintenance market is anticipated to register a major market share in terms of revenue. It is projected to grow at a high CAGR in the near future because of the growing research and development activities of both small and major companies. Businesses in North America are thriving because their leaders are adopting integrated enterprise and business solutions, which allow for more adaptability and speed in daily operations. Besides, Europe had a substantial share of the market due to the rising demand for more cost-effective solutions and the focus on reducing machine breakdowns.

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Recent Developments:

• In January 2024, OCP Maintenance Solutions is pleased to announce a new collaboration with Nexans, an industry-leading provider of cutting-edge cabling and connection solutions. This partnership is a watershed moment in the integration of mechanical and electrical knowledge, paving the way for pioneering solutions to be co-developed and used by both parties.
• In September 2023, Gastops is delighted to announce that ChipCHECK has been chosen on Bell Textron Canada’s program to support the 85 CH146 Griffon helicopters of the Royal Canadian Air Force (RCAF). These helicopters are a multi-role military derivative of the extensively used Bell-412EP. Seven ChipCHECK devices have been acquired to enhance equipment readiness, streamline maintenance processes, and save costs.

Segmentation of AI-driven Predictive Maintenance Market-

AI-driven Predictive Maintenance Market- By Solution

• Integrated Solution
• Standalone Solution

AI-driven Predictive Maintenance Market- By Industry

• Automotive & Transportation
• Aerospace & Defense
• Manufacturing
• Healthcare
• Telecommunications
• Others

AI-driven Predictive Maintenance Market- By Region

North America-

• The US
• Canada
• Mexico

Europe-

• Germany
• The UK
• France
• Italy
• Spain
• Rest of Europe

Asia-Pacific-

• China
• Japan
• India
• South Korea
• Southeast Asia
• Rest of Asia Pacific

Latin America-

• Brazil
• Argentina
• Rest of Latin America

 Middle East & Africa-

• GCC Countries
• South Africa
• Rest of the Middle East and Africa

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Company Name: InsightAce Analytic Pvt. Ltd
Contact Person: Diana D’Souza
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Country: United States
Website: https://www.insightaceanalytic.com/