Predictive Maintenance Market to hit USD 26,588Mn by 2028, Globally, by 2028 at 27.4% CAGR: The Insight Partners
The Insight Partners
Predictive Maintenance Market 2022 research report gives an analysis of revenue, forecast, company ranking, competitive landscape, growth and trends
NEW YORK, UNITED STATES, October 17, 2022 /EINPresswire.com/ -- According to our latest market study on “Predictive Maintenance Market Forecast to 2028 - COVID-19 Impact and Global Analysis By Component (Solutions and Services), Deployment Type (Cloud and On-Premise), Technique (Vibration Monitoring, Electrical Testing, Oil Analysis, Ultrasonic Leak Detectors, Shock Pulse, Infrared and Others), and Industry (Manufacturing, Energy & Utilities, Aerospace & Defense, Transportation & Logistics, Oil & Gas, and Others)” The predictive maintenance market is projected to reach US$ 26,588.00 million by 2028 from US$ 5,316.99 million in 2021. it is expected to grow at a CAGR of 27.4% during 2022–2028.
Global Smart Pest Monitoring Management System Market Growth Values, Regional and Industry Scope:
Market Size Value in - USD 5,316.99 Million in 2021
Market Size Value by - US USD 26,588.00 Million by 2028
Growth rate - CAGR of 27.4% from 2022 to 2028
Forecast Period - 2022-2028
Base Year - 2021
No. of Pages - 221
No. of Tables - 116
No. of Charts & Figures - 96
Historical data available - Yes
Segments covered - Component, Deployment Type, Technique, and Industry
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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.
Predictive Maintenance Market: Competitive Landscape and Key Developments
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.
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Impact of COVID-19 Pandemic on Predictive Maintenance Market
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).
Predictive Maintenance Market Insights
Deployment Type-Based Insights
The predictive maintenance market, by deployment type, is segmented into cloud and on-premise. Cloud is expected to remain the largest segment during the forecast period. The cloud segment is growing considerably due to several advantageous characteristics, such as scalability and cost-effectiveness, which are expected to propel the growth of the predictive maintenance market during the forecast period. The growth of this segment can also be attributed to faster data processing and direct IT control, the efficient use of resources, and the cost-effectiveness of cloud models.
The predictive maintenance market is segmented 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 classified 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 market is segmented into manufacturing, energy & utilities, aerospace & defense, transportation & logistics, oil & gas, and others.
Based on geography, the predictive maintenance market is segmented into North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and South America (SAM). 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.
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Predictive maintenance market players mainly focus on tailor-made solutions to create customer value.
•In April, 2022, Wärtsilä Corporation signed an Optimized Maintenance Agreement (OMA) covering two LNG carrier vessels technically managed and operated by the Japanese shipping group MMS Co., Ltd. The agreement is expected to deliver maximized engine uptime and long-term cost predictability while optimizing maintenance for the highest efficiency and lowest carbon footprint. Wärtsilä’s predictive maintenance solution, Expert Insight, is also included in the agreement.
•In July, 2021, Schneider Electric implemented predictive maintenance for Nestlé’s Dubai South factory. This solution is expected to aid Nestlé’s operations team monitor power management, electrical loads, and temperature settings from all of the factory’s connected assets, so they can address issues proactively, avoid unplanned downtime and mitigate safety risks.
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