Predictive Maintenance Market to Reach $66.46 Billion by 2031, Attributed to Increase Demand to Reduce Maintenance Costs

WESTFORD, MASSACHUSETTS, UNITED STATES, August 8, 2024 /EINPresswire.com/ -- Predictive Maintenance Market size was valued at USD 5.77 Billion in 2022 and is poised to grow from USD 7.57 Billion in 2023 to USD 66.46 Billion by 2031, at a CAGR of 31.2% during the forecast period (2024-2031).

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The predictive maintenance industry is expanding due to several causes, including demand to reduce maintenance costs and minimize equipment breakdowns, availability of ML and AI, and rise in trend of adopting novel technologies to acquire usable data. Predictive maintenance is a relatively new industry within the intersection of technology and industrial maintenance. They use big data analytics, which uses machine learning and the Internet of Things to anticipate when specific machinery or equipment is predicted to break. Predictive maintenance lowers operating downtime and expenses by forecasting the need for maintenance based on historical trends and current data.

Revolutionize AI Through Siemens Strategic Expansion

The following are the key Predictive Maintenance Trends that will shape the growth of the market in the next 5 years

In January 2024, the company decided to extend its strategic as-a-service partnership with Siemens. The goal of this tactic is to facilitate the deployment of generative AI for businesses of all sizes across all industries. Long-term partnerships that allow specialists in engineering, manufacturing, logistics, finance, insurance, or insurance to create cutting-edge generative AI solutions or improve current ones are highly valued by them.

The company's strategic commitment to the creation of generative AI solutions for all business sizes and industries is highlighted in its extended relationship with Siemens. This initiative exemplifies their shared objective of being the benchmark for harnessing artificial intelligence's transformative potential in a variety of global businesses.

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Empowering Airline Industry with AI: Qatar Airways Partners with Google Cloud
In June 2023, Google Cloud and Qatar Airways signed a partnership deal to provide data and artificial intelligence (AI) solutions to the airline industry. The key areas of concentration for this symbiosis are anticipated to be cargo, passenger satisfaction, and predictive maintenance since these are the areas where it may be possible to increase the efficiency of customer-oriented activities within the airline business.

Advanced analytics offer insights into traveler preferences and behaviors, resulting in experiences and services that are tailored to the individual needs of each customer and raise customer satisfaction. In predictive maintenance, AI algorithms can be used to evaluate aircraft data and forecast equipment problems before they arise. This can guarantee fleet dependability, save downtime, and raise safety standards. By focusing on these vital areas, the alliance aims to raise operational efficiencies, set new standards for innovation in the airline industry, and enhance passengers' overall travel experiences on Qatar Airways.

Latest Updates in Predictive Maintenance: Key Market Developments

• August 2019: Cisco Systems, Inc. acquired Cloudcherry, a customer experience management startup that specialized in predictive analytics, to enhance its cognitive contact center solutions through predictive maintenance and analytics.

• January 2019: In wind power generation solutions, Hitachi Ltd. stated that it will expand the range of its wind power generator maintenance services and continue to develop its core products. This is one of Hitachi's efforts to strengthen its renewable energy business, which also includes neighborhood-based and cooperative energy projects that use solar energy, storage batteries, and other components.

• June 2018: IBM Corporation acquired Oniqua Holdings Pvt Ltd., one of the leading providers of software for maintenance, repair, and operations optimization, to expand its asset optimization practice and help clients minimize and optimize maintenance, repair, and operations (MRO) inventories.

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Predictive Maintenance: A Closer Look

Predictive maintenance is becoming more and more popular, which suggests that proactive asset management is becoming the new normal. Companies are increasingly utilizing machine learning, IoT sensors, and advanced analytics to predict equipment failures before they occur. They can reduce downtime, improve maintenance schedules, and ultimately reduce operational costs as a result. In addition to altering traditional maintenance practices, this trend is driving industrial asset management toward increased efficiency and data-driven decision-making.

Related Report:
Internet Of Things (IoT) Market

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