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Predictive Maintenance Market Research Report Covers, Future Trends, Past, Present Data and Deep Analysis 2022-2028

Predictive Maintenance Market Research Report Covers, Future Trends, Past, Present Data and Deep Analysis 2022-2028


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Ankush M

13 days ago | 3 min read
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According to the latest market study on "Predictive Maintenance Market Forecast to 2028 – COVID-19 Impact and Global Analysis – by Component, Deployment Type, Technique and Industry," the market is expected to grow from US$ 5,316.99 million in 2021 to US$ 26,588.00 million by 2028; it is anticipated to grow at a CAGR of 27.4% from 2022 to 2028.

Industry 4.0 is revolutionizing the way companies make, improve, and sell their products. Aerospace, defense, transportation, and many other industries are implementing the latest technologies, including the Internet of Things (IoT), cloud computing and analytics, artificial intelligence (AI), and machine learning (ML), to improve processes and overall operations. Companies in the oil & gas industry are significantly adopting technologies, such as IoT and advanced analytics to enhance operational efficiencies, cut costs, and optimize manual processes. Oil and gas companies experience several unplanned incidences, such as pipe leakage and energy grid failure, which cost millions to them.

Predictive maintenance enables these companies to rely on Industrial Internet of Things (IIoT)-enabled technologies, such as sensor data, and use predictive analytics for real-time equipment inspections, which helps reduce maintenance costs and unplanned equipment downtime. These factors are collectively driving the growth of predictive maintenance market size globally.

The Asia Pacific predictive maintenance market is segmented into Australia, China, India, Japan, and South Korea. The increased uptake of advanced technologies in Asia Pacific across various industrial applications is expected to drive the predictive maintenance market growth over the coming years. Every industry vertical need improved asset management, boosting the demand for predictive maintenance solutions. Solution providers equipped with machine learning (ML) and artificial intelligence (AI) can achieve meaningful insights from the vast amount of customer-related data generated by IoT and other connected devices. Additionally, Chinese firms have been one of the keenest adopters of technology in APAC as they seek to gain a competitive edge through digitalization and innovation. Similar trends are being witnessed across other nations in the region, such as India and Singapore. Such factors are likely to drive APAC’s predictive maintenance market size during the forecast period.

The ecosystem of the global predictive maintenance market comprises the following stakeholders: Hardware suppliers, software providers, predictive maintenance service providers, and end users. Hardware suppliers provide IoT-enabled sensors and other equipment enabling data collection for predictive maintenance. Software providers offer solutions, which are often customized as per customer requirements. Solutions collect, disseminate, and analyze data gathered from different equipment requiring predictive maintenance. Service providers of predictive maintenance are some of the major customers of hardware and software providers. Various offerings of service providers comprise acoustic analysis, vibration analysis, and infrared analysis alerts. End users can also avail hardware and software directly from suppliers without engaging any service provider.

The predictive maintenance market is analyzed on the basis of component, deployment type, technique, and industry. Based on component, the market is segmented into solutions and services. Based on deployment type, the market is bifurcated into cloud and on-premise. Based on technique, the market is segmented into vibration monitoring, electrical testing, oil analysis, ultrasonic leak detectors, shock pulse, infrared, and others. Based on industry, the predictive maintenance market is segmented into manufacturing, energy & utilities, aerospace & defense, transportation & logistics, oil & gas, and others.

General Electric Co., Hitachi Ltd., IBM Corporation, Microsoft Corporation, PTC, Inc., SAS Institute Inc., Schneider Electric SE, Software AG, Syncron AB, and TOSL Engineering Ltd. are key predictive maintenance market players profiled during this study. In addition, several other important predictive maintenance market players were studied and analyzed during this market study to get a holistic view of the global predictive maintenance market and its ecosystem.

The COVID-19 pandemic negatively impacted major countries, such as India, China, Australia, and Japan, leading to decreased productivity. Several economies in Asia Pacific experienced a sharp decline in their GDP in 2020 due to the sudden closedown of the majority of economic activities across the region. Severe travel restrictions were put into effect across several regions. The COVID-19 outbreak, thus, initially disrupted the growth rate of the predictive maintenance market even though the outbreak had driven many companies to use advanced analytics and artificial intelligence (AI).

Early stages of the pandemic saw a slowdown in companies adopting new solutions and services. However, during the later stages, many market players were increasingly turning to analytics, collaboration applications, security solutions, and AI to outline sustainable ways to continue business operations amid the pandemic threat. Industrial manufacturing production gained pace from mid-2021, which is further foreseen to positively influence the uptake of analytics solutions, including predictive maintenance. Hence, the COVID-19 pandemic positively impacted the predictive maintenance market growth.



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