Middle East and Africa Predictive Maintenance Market Forecast to 2027 - COVID-19 Impact and Regional Analysis by Component (Solution 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, and Others)
The MEA predictive maintenance market is expected to grow from US$ 284.11 million in 2022 to US$ 1,106.06 million by 2028. It is estimated to grow at a CAGR of 25.4% from 2022 to 2028.
Automation through Incorporation of AI and ML
The proliferation of IoT and AI technologies is anticipated to play a significant role in the ease of conducting predictive maintenance in the coming years. Throughout the machine's lifecycle, IoT sensors collect any relevant data and store it on the cloud. AI can make specific recommendations on what actions need be taken to maintain the health of the company assets. On many devices or machines, these recommendations are often warnings of actions that a technician should take. This can be from a simple request to perform a software update or lubricating a few wheels to complex repairs. AI and ML advancements can significantly change the working of these predictive maintenance tasks. In the future, there will be an exponential rise in automation as improvement in processes and efficiency will be the major focus of the companies. Industries across the region are already incorporating advanced machineries, with IoT enabled sensors, to aid them in continuous monitoring of machine health. Additionally, drone-based monitoring of equipment is growing rapidly in the conventional and renewable energy sectors. Drones, fitted with thermal imaging equipment, are assisting industries in remotely monitoring the health of power lines and other equipment. Major service providers of predictive maintenance are increasingly adopting this technology, despite incidents of drone crashes and property loss. With advancements of drone technology and capabilities, it can be touted as the future of remote predictive maintenance. Such trends are expected to boost the demand for predictive maintenance solutions and services across the region in the coming years.
The major leading countries, such as Saudi Arabia, Kuwait, and Qatar, dominate the demand for the predictive maintenance market. These countries are significantly contributing to the growth by producing oil & gas that emerges the need for consistent maintenance and helping the market to grow. The key factors responsible for the market's growth are supportive government policies for oil and gas production, which are expected to drive the market over the coming years. The oil & gas industry witnessed a major demand for predictive maintenance from 2020, with major absorption from the Middle East region. In November 2019, The Abu Dhabi National Oil Company (ADNOC) selected Honeywell's asset monitoring and predictive analytics solution to drive improved asset and machinery management across ADNOC's upstream and downstream operations. The predictive analytics solution leveraged AI technologies such as machine learning and digital twins to generate significant yearly savings through reduced unplanned maintenance, increased reliability, uptime, and safety. In the MEA region, asset performance management (APM) had a major role to play in achieving the maintenance objective by using a set of cyber-physical systems, including the industrial Internet of Things (IIoT), cloud computing, big data analytics, predictive analytics leveraging artificial intelligence and machine learning, mobility and augmented and virtual reality. In August 2022, as per the Dubai Electricity and Water Authority (DEWA), periodic preventive maintenance of the power transmission networks has contributed to achieve 100% reliability and availability of the power transmission system in Dubai. This has reduced the average maintenance costs by approximately US$0.54 million, making it the ‘Best in Class’ among global utilities. Thus, such growing demand for predictive maintenance in MEA is anticipated to drive the market growth over the forecast period.
MEA Predictive Maintenance Market Revenue and Forecast to 2028 (US$ Million)
MEA Predictive Maintenance Market Segmentation
The MEA predictive maintenance market is segmented based on component, deployment type, technique, industry, and country.
Based on component, the MEA predictive maintenance market is bifurcated into solutions and services. The solutions segment held a larger market share in 2022.
Based on deployment type, the MEA predictive maintenance market is bifurcated into cloud and on-premise. The cloud segment held a larger market share in 2022.
Based on technique, the MEA predictive maintenance market is segmented into vibration monitoring, electrical testing, oil analysis, ultrasonic leak detectors, shock pulse, infrared, and others. The vibration monitoring segment held the largest market share in 2022.
Based on industry, the MEA predictive maintenance market is segmented into manufacturing, energy & utilities, aerospace & defense, transportation & logistics, oil & gas, and others. The oil & gas segment held the largest market share in 2022.
Based on country, the MEA predictive maintenance market has been categorized into the UAE, Saudi Arabia, South Africa, and rest of MEA. Our regional analysis states that Saudi Arabia dominated the market share in 2022.
General Electric Company; Hitachi, Ltd.; IBM Corporation; Microsoft Corporation; PTC Inc.; SAS Institute, Inc.; Schneider Electric SE; Software AG; and Syncron AB are the leading companies operating in the MEA predictive maintenance market.
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