Global Predictive Maintenance Market was valued at USD 6.04 billion in 2023 and is anticipated to project robust growth in the forecast period with a CAGR of 27.88% through 2029. The integration of advanced technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), and machine learning, is a driving force behind the growth of predictive maintenance. Industry 4.0 practices, characterized by the interconnectedness of smart devices and systems, provide a fertile ground for predictive maintenance solutions.

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Key Market Players

Accenture plc
Cisco Systems, Inc.
General Electric Company
Honeywell International Inc.
Hitachi, Ltd.
IBM Corporation
Microsoft Corporation
Robert Bosch GmbH
SAP SE
Schneider Electric SE

Machine Learning-as-a-Service Market will reach at a CAGR of 39.8% from to 2030

The market size of the machine learning-as-a-service (MLaaS) was USD 2.2 billion in 2021. It is estimated to reach USD 32.0 billion by 2030, registering a CAGR of 39.8% from 2022-2030

Below information is analyzed in depth in the report-

Global Machine Learning-as-a-Service Market Revenue, 2018-2023, 2024-2033, (US$ Millions)
Global Machine Learning-as-a-Service Market Sales Volume, 2018-2023, 2024-2033, (Units)
Share of the top five Machine Learning-as-a-Service companies in 2023 (%)
Market Growth Mapping

Qualitative and quantitative methodologies were utilized in the process of market growth mapping. The report offers an extensive examination of market dynamics, including a thorough assessment of the primary factors that drive market expansion, challenges encountered by industry participants, and forthcoming trends that indicate recent development. Prospects for investment and expansion are discerned via a comprehensive SWOT analysis, which evaluates the market’s strengths, weakness, opportunities, and threats. The PESTEL analysis, which investigates the technological, environmental, political, economic, and social factors that influence the industry, provides additional depth of analysis. Furthermore, the report incorporates an analysis of PORTER'S 5 forces, which provides valuable perspectives on the sector's profitability and competitive intensity. Moreover, the report covers regulatory landscape, COVID-19 impact analysis, customer sentiment and behavior, trade analysis, supply-demand analysis, and the influence of government policies and other macroeconomic factors.



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Machine Learning-as-a-Service Market Segmentation:

This study offers a thorough segmentation of the Machine Learning-as-a-Service market based on an in-depth examination of the product portfolios and customers of key regional and global market players. By means of a comprehensive examination, we offer detailed perspectives on market segmentation, assisting stakeholders in comprehending the diverse aspects and variables that impact the Machine Learning-as-a-Service market.

By Application Outlook (Sales/Revenue, USD Billion, 2017-2030)
Marketing and Advertisement
Predictive Maintenance
Automated Network Management
Fraud Detection and Risk Analytics
Other Applications
NLP
Sentiment Analysis
Computer Vision
By Organization Size Outlook (Sales/Revenue, USD Billion, 2017-2030)
Small and Medium Enterprises
Large Enterprises
By End-Users Outlook (Sales/Revenue, USD Billion, 2017-2030)
IT and Telecom
Automotive
Healthcare
Aerospace and Defense
Retail
Government
BFSI
Other End Users
Education
Media and Entertainment
Agriculture
Trading Market Place




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Machine Learning-as-a-Service Market Regional Analysis:

This report delivers an exhaustive regional analysis of the Machine Learning-as-a-Service market and dives into country-level evaluation for top economies. This study examines the operational activities of both domestic and international competitors in particular markets, while also evaluating the influence of market participant strategies and governmental backing on the expansion of the market. In order to provide stakeholders with a comprehensive perspective for well-informed strategy formulation, the study bridges the understanding of how regional dynamics and larger trends contribute to market growth.

North America (Revenue: USD Million; 2018-2033)

US
Canada
Mexico
Europe (Revenue: USD Million; 2018-2033)

Germany
France
K.
Italy
Spain
Russia
The Netherland
Poland
Belgium
Nordic Countries
Rest of Europe
Asia Pacific (Revenue: USD Million; 2018-2033)

China
Japan
South Korea
ASEAN
Australia & New Zealand
India
Rest of Asia
South America (Revenue: USD Million; 2018-2033)

Brazil
Argentina
Peru
Colombia
Rest of South America
Middle East & Africa (Revenue: USD Million; 2018-2033)

Turkey
Israel
Saudi Arabia
Egypt
UAE
Rest of the Middle East & Africa


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Artificial Intelligence (AI) in Manufacturing Market Demand, Opportunities and Forecast By 2029

The finest Artificial Intelligence (AI) in Manufacturing market report describes CAGR value fluctuation during the forecast period of 2021-2028 for the market. It is the most suitable, rational, and admirable market research report provided with a devotion and comprehension of business needs. The market report also comprises drivers and restraints for the market that are obtained with the help of SWOT analysis and also show all the recent developments, product launches, joint ventures, mergers, and acquisitions by the several key players and brands with their systemic company profiles that are driving the market. Artificial Intelligence (AI) in Manufacturing is the most capable market research report which has been prepared in the way anticipated.


The artificial intelligence (AI) in manufacturing market is expected to witness market growth at a rate of 17.20% in the forecast period of 2022 to 2029 and is expected to reach USD 5,325.1 million by 2029. Data Bridge Market Research report on artificial intelligence (AI) in manufacturing market provides analysis and insights regarding the various factors expected to be prevalent throughout the forecast period while providing their impacts on the market's growth. The rise in the application of AI for intelligent business process is escalating the growth of artificial intelligence (AI) in manufacturing market.

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Market Overview:

Artificial intelligence (AI) is known to be one of the most developed technologies in the field of computer science. It is related to the human intelligence through similar characteristics including better decision making, language understanding, and so forth.

Global Artificial Intelligence (AI) in Manufacturing Market Scope and Market Size

The artificial intelligence (AI) in manufacturing market is segmented on the basis of offering, technology, applications and industry. The growth among segments helps you analyze niche pockets of growth and strategies to approach the market and determine your core application areas and the difference in your target markets.



· On the basis of offering, the artificial intelligence (AI) in manufacturing market has been segmented into hardware, software and services.

· On the basis of technology, the artificial intelligence (AI) in manufacturing market has been segmented into machine learning, natural language processing, context-aware computing and computer vision.

· On the basis of application, the artificial intelligence (AI) in manufacturing market has been segmented into predictive maintenance and machinery inspection, material movement, production planning, field services, quality control, cybersecurity, industrial robots and reclaimation.

· On the basis of industry, the artificial intelligence (AI) in manufacturing market has been segmented into automobile, energy and power, pharmaceuticals, heavy metals and machine manufacturing, semiconductors and electronics, food & beverages and others.

Some of the major players operating in the artificial intelligence (AI) in manufacturing market are NVIDIA Corporation, IBM, Alphabet Inc., Microsoft Corporation, Intel Corporation, Siemens, General Electric Company, General Vision, inc., Progress Software Corporation, Micron Technology, Inc., Mitsubishi Electric Corporation, Sight Machine, Cisco Systems Inc., SAP SE, Rockwell Automation, Inc., AIBrain Inc., Vicarious, Oracle, Amazon Web Services, Inc., SparkCognition., Rethink Robotics, UBTECH Robotics, Inc., Aquant, Bright Machines, Inc., and Flutura among others.



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Global Connected Lighting Platform Market has valued at USD 16.63 billion in 2023 and is anticipated to project robust growth in the forecast period with a CAGR of 14.38% through 2029. The rapid evolution of Internet of Things (IoT) technologies is a significant driver for connected lighting platforms. The integration of sensors, connectivity modules, and smart controls into lighting infrastructure enables real-time data collection, analysis, and communication. This connectivity allows for advanced functionalities, including remote monitoring, predictive maintenance, and the ability to customize lighting settings based on user preferences and environmental conditions.

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Key Market Players

Eaton Corporation
Cree, Inc.
Philips Lighting
Honeywell International Inc.
Samsung Electronics
IKEA
Schneider Electric
Echelon Corporation
Lutron Electronics Co. Inc
Leviton Manufacturing Co.

Predictive Maintenance Market will reach at a CAGR of 28.8% from to 2027

The global predictive maintenance market size is expected to grow from USD 5,443.1 million in 2020 to USD 31,965.5 million by 2027, at a CAGR of 28.8% from 2021 to 2027.

Below information is analyzed in depth in the report-

Global Predictive Maintenance Market Revenue, 2018-2023, 2024-2033, (US$ Millions)
Global Predictive Maintenance Market Sales Volume, 2018-2023, 2024-2033, (Units)
Share of the top five Predictive Maintenance companies in 2023 (%)
Market Growth Mapping

Qualitative and quantitative methodologies were utilized in the process of market growth mapping. The report offers an extensive examination of market dynamics, including a thorough assessment of the primary factors that drive market expansion, challenges encountered by industry participants, and forthcoming trends that indicate recent development. Prospects for investment and expansion are discerned via a comprehensive SWOT analysis, which evaluates the market’s strengths, weakness, opportunities, and threats. The PESTEL analysis, which investigates the technological, environmental, political, economic, and social factors that influence the industry, provides additional depth of analysis. Furthermore, the report incorporates an analysis of PORTER'S 5 forces, which provides valuable perspectives on the sector's profitability and competitive intensity. Moreover, the report covers regulatory landscape, COVID-19 impact analysis, customer sentiment and behavior, trade analysis, supply-demand analysis, and the influence of government policies and other macroeconomic factors.



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Predictive Maintenance Market Segmentation:

This study offers a thorough segmentation of the Predictive Maintenance market based on an in-depth examination of the product portfolios and customers of key regional and global market players. By means of a comprehensive examination, we offer detailed perspectives on market segmentation, assisting stakeholders in comprehending the diverse aspects and variables that impact the Predictive Maintenance market.

By Component Outlook (Revenue, 2017-2027, USD Billion)
Solution
Service
By Deployment Outlook (Revenue, 2017-2027, USD Billion)
Cloud
On-premise
By Technique Outlook (Revenue, 2017-2027, USD Billion)
Vibration Monitoring
Electrical Testing
Oil Analysis
Ultrasonic Leak Detectors
Shock Pulse
Infrared
Others
By Stakeholder Outlook (Revenue, 2017-2027, USD Billion)
MRO
OEM/ODM
Technology Integrators
By Industry Outlook (Revenue, 2017-2027, USD Billion)
Manufacturing
Energy & utilities
Aerospace & Defense
Transportation & Logistics
Government
Healthcare
Other




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Predictive Maintenance Market Regional Analysis:

This report delivers an exhaustive regional analysis of the Predictive Maintenance market and dives into country-level evaluation for top economies. This study examines the operational activities of both domestic and international competitors in particular markets, while also evaluating the influence of market participant strategies and governmental backing on the expansion of the market. In order to provide stakeholders with a comprehensive perspective for well-informed strategy formulation, the study bridges the understanding of how regional dynamics and larger trends contribute to market growth.

North America (Revenue: USD Million; 2018-2033)

US
Canada
Mexico
Europe (Revenue: USD Million; 2018-2033)

Germany
France
K.
Italy
Spain
Russia
The Netherland
Poland
Belgium
Nordic Countries
Rest of Europe
Asia Pacific (Revenue: USD Million; 2018-2033)

China
Japan
South Korea
ASEAN
Australia & New Zealand
India
Rest of Asia
South America (Revenue: USD Million; 2018-2033)

Brazil
Argentina
Peru
Colombia
Rest of South America
Middle East & Africa (Revenue: USD Million; 2018-2033)

Turkey
Israel
Saudi Arabia
Egypt
UAE
Rest of the Middle East & Africa


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Marine Lubricants Market Dynamics: Charting Course for Success
The Importance of Selecting the Right Marine Lubricants
Lubricant Basics for Ships
When it comes to maintaining ships, one of the most important components is selecting the proper lubricants. Lubricants are crucial for reducing friction between parts in an engine or transmission and protecting components from wear. They also aid in heat transfer and removing contaminants. For vessels that operate in harsh marine conditions, it's essential to use lubricants formulated to withstand corrosion from saltwater, extreme temperatures, and other environmental stressors.

Marine Engine Oil Requirements
Marine engine oils need to meet stringent specifications to protect engines safely and reliably. Most ship engines run on heavy fuel oil which contains sulfur and can damage conventional engine oils. Marine engine oils are designed with additives that neutralize acids and resist breakdown. They also have effective detergent and dispersant packages to prevent the buildup of sludge and deposits. Properties like high thermal and oxidation stability allow marine engine oils to maintain performance even under prolonged high temperature operating conditions. Choosing an oil that meets the correct rating for an engine's application is vital.

Gear, Grease and Hydraulic Fluid Considerations
Gears, bearings and hydraulic systems on ships require specialized lubricants as well. Marine gear oils need robust load-carrying properties and anti-wear additives to prevent metal-to-metal contact in heavily loaded gearboxes. They also incorporate corrosion and oxidation inhibitors. Marine greases are formulated with thickening agents that won't liquefy or be flushed away under water and can tolerate wide temperature variations. Hydraulic fluids demand high viscosity index and resistance to degradation since hydraulic systems are exposed to high pressures. Water-resistant types are needed where systems risk seawater contamination.

Quality is Key on the Open Seas
On ships far from repair facilities, reliability is paramount. Low-quality lubricants that fail prematurely could lead to costly repairs or breakdowns. It's important to rely on reputable brands that have proven marine formulations. Their oils, greases and fluids undergo stringent testing to validate performance under real-world marine conditions. Quality control is also critical since even minor product variances could impact lubrication. Using products from specialized marine lubricants suppliers helps ensure consistent quality is maintained, batch to batch. This provides peace of mind for operations on the open seas.

Lubricant Selection Guide
Selecting the appropriate lubricant involves considering factors like the vessel type, engine/equipment manufacturer guidance, operating environment and maintenance/service intervals. Most machinery OEMs approve select oils/lubricants to ensure compatibility. Marine owners and operators consult product data sheets and distributor expertise to choose products for various applications. Multi-grade engine oils suited for high/low temperature operations are common. Greases range from spray types for occasional reapplication to premium service grades for severe marine conditions. Hydraulic fluids span watersoluble/resistant selections. Proper training aids selecting the right lubricant the first time to maximize uptime.

Monitoring and Maintenance Best Practices
To keep lubricants performing as intended requires following monitoring and maintenance best practices. Routine oil analysis via used sample testing checks for unwanted wear metals, fuels, water or viscosity loss and flags any issues requiring attention. Drain intervals are set according to OEM guidance, taking workload and operating environment into account. Filters/strainers are changed on schedule to remove contaminants. Grease points are lubricated regularly using a grease gun. Inventory management ensures adequate lubricant volumes and no stock outs occur. Record keeping of analysis reports, tasks and lubricants used provides a performance history. Adhering to these practices helps fleet managers make data-based decisions for predictive maintenance.

Partnering with Qualified Distributors
Most ship owners and operators rely on marine lubricants distributors to supply, handle and advise on products. Experienced distributors maintain an extensive portfolio of quality lubricants from top brands as well as expertise across different applications. They provide technical support selecting the right lubricant, setup delivery/refill programs and ensure vessels have necessary inventories while in port or underway. Distributors can store lubricants in their warehouses for easy future access versus a ship needing multiple bulk deliveries. Many participate in used oil/waste disposal as well. Partnering with a qualified marine distributor streamlines lubricant management, so crew can instead focus on vessel operations.

In Summary
Considering the critical role lubricants play in ship machinery and the harsh marine operating environment, it's imperative vessels use high-performance products suited for applications. Relying on reputable marine lubricants brands with proven formulations and selecting the proper lubricant in consultation with distributors helps maximize engine/equipment protection, reduce wear and provide peace of mind. Adhering to recommended maintenance practices moreover helps fleet managers make informed decisions to keep vessels running smoothly. Overall, using the right lubrication strategies tailored for marine duty is a cornerstone of safe, reliable and efficient ship op

Egypt IoT in Manufacturing market is expected to grow at a steady CAGR in the forecast period, 2022-2026. The growing adoption of industry 4.0 to obtain enhanced production capacity, increase the overall efficiency of the system and deliver insights to make real-time decisions is expected to spur the market growth. Manufacturers are integrating advanced technologies including artificial intelligence, cloud computing, and analytics, machine learning along with the internet of things to improve the throughput of their operations.

The use of embedded software, technologically advanced sensors and robotics collect the information and data to make smart decisions in the manufacturing units. The surge in the need for the centralized monitoring and predictive maintenance of assets and the increasing demand for industrial automation is expected to influence the growth of the IoT in manufacturing market in the next five years.

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The major players operating in the Egypt IoT in Manufacturing market are Cisco, Valeo Spime Sense Lab, Telecom Egypt, IBM, Accenture, SAP, Nokia, Ericsson, Honeywell, Fujitsu, Microsoft, Etisalat, Oracle, Huawei, and others. Major companies are developing advanced technologies and launching new services to stay competitive in the market. Other competitive strategies include mergers & acquisitions and new service developments.

The Global Fiber Optic Sensor Market is experiencing robust growth, driven by an array of factors that collectively underscore the increasing importance and demand for advanced sensing solutions across industries. Fiber optic sensors, renowned for their precision, sensitivity, and resistance to electromagnetic interference, are being increasingly adopted in various applications.

Among the key market drivers, the need for real-time data is paramount. Industries across the spectrum, from manufacturing to healthcare, are turning to fiber optic sensors to enable real-time monitoring and control, ensuring optimal efficiency and safety. The growth of the Internet of Things (IoT) further fuels the market, as fiber optic sensors integrate seamlessly with IoT networks, allowing for predictive maintenance and data-driven decision-making.

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Key Market Players

Corning Incorporated
Amphenol Corporation
TE Connectivity Ltd.
Keysight Technologies, Inc.
LUNA Innovations Incorporated
Ocean Optics, Inc.
EXFO Inc.
FISO Technologies Inc.
Fiber Bragg Grating Sensors (FBGS)
Shanghai Senstech Co.,Ltd.

Global Asset Management System Market was valued at USD 10.55 billion in 2023 and is anticipated to project robust growth in the forecast period with a CAGR of 8.49% through 2029. The integration of predictive maintenance capabilities within asset management systems allows organizations to proactively address potential issues before they result in asset failures.

Predictive analytics, enabled by technologies like artificial intelligence and machine learning, helps businesses schedule maintenance activities based on data-driven predictions, minimizing disruptions and extending the lifespan of assets.

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Key Market Players

Zebra Technologies Corp.
Stanley Black and Decker, Inc.
Sato Holdings Corp.
Impinj, Inc.
Honeywell International Inc.
Datalogic S.p.A
Trimble Inc.
TomTom International BV
Topcon Corp.
Cognex Corp.

Global Machine to Machine Connections Market has valued at USD 40.58 billion in 2023 and is anticipated to project robust growth in the forecast period with a CAGR of 6.27% through 2029. The fourth industrial revolution, often referred to as Industry 4.0, emphasizes the integration of digital technologies into industrial processes. Industrial IoT (IIoT) is a key component of this transformation, and M2M connections play a vital role in facilitating communication and data exchange among connected industrial devices. The pursuit of operational efficiency, predictive maintenance, and real-time monitoring in manufacturing and other industries is driving the adoption of M2M in the industrial sector.

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Key Market Players

Deutsche Telekom AG
Vodafone Group PLC
AT&T Inc.
Telit Communications
NTT Data
U-blox Holding AG
Telenor Group
Verizon Communications Inc.
Texas Instruments Incorporated
Intel Corporation

Machine Learning-as-a-Service Market Size to Reach US$ 32.0 billion by 2030

The market size of the machine learning-as-a-service (MLaaS) was USD 2.2 billion in 2021. It is estimated to reach USD 32.0 billion by 2030, registering a CAGR of 39.8% from 2022-2030.

Below information is analyzed in depth in the report-

Global Machine Learning-as-a-Service Market Revenue, 2018-2023, 2024-2033, (US$ Millions)
Global Machine Learning-as-a-Service Market Sales Volume, 2018-2023, 2024-2033, (Units)
Share of the top five Machine Learning-as-a-Service companies in 2023 (%)
Market Growth Mapping

Qualitative and quantitative methodologies were utilized in the process of market growth mapping. The report offers an extensive examination of market dynamics, including a thorough assessment of the primary factors that drive market expansion, challenges encountered by industry participants, and forthcoming trends that indicate recent development. Prospects for investment and expansion are discerned via a comprehensive SWOT analysis, which evaluates the market’s strengths, weakness, opportunities, and threats. The PESTEL analysis, which investigates the technological, environmental, political, economic, and social factors that influence the industry, provides additional depth of analysis. Furthermore, the report incorporates an analysis of PORTER'S 5 forces, which provides valuable perspectives on the sector's profitability and competitive intensity. Moreover, the report covers regulatory landscape, COVID-19 impact analysis, customer sentiment and behavior, trade analysis, supply-demand analysis, and the influence of government policies and other macroeconomic factors.



Request Sample Copy of this Report: https://www.marketstatsville.com/request-sample/machine-learning-as-a-service?utm_source=Free&utm_medium=VIPIN



Machine Learning-as-a-Service Market Segmentation:

This study offers a thorough segmentation of the Machine Learning-as-a-Service market based on an in-depth examination of the product portfolios and customers of key regional and global market players. By means of a comprehensive examination, we offer detailed perspectives on market segmentation, assisting stakeholders in comprehending the diverse aspects and variables that impact the Machine Learning-as-a-Service market.

By Application Outlook (Sales/Revenue, USD Billion, 2017-2030)
Marketing and Advertisement
Predictive Maintenance
Automated Network Management
Fraud Detection and Risk Analytics
Other Applications
NLP
Sentiment Analysis
Computer Vision
By Organization Size Outlook (Sales/Revenue, USD Billion, 2017-2030)
Small and Medium Enterprises
Large Enterprises
By End-Users Outlook (Sales/Revenue, USD Billion, 2017-2030)
IT and Telecom
Automotive
Healthcare
Aerospace and Defense
Retail
Government
BFSI
Other End Users
Education
Media and Entertainment
Agriculture
Trading Market Place




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Machine Learning-as-a-Service Market Regional Analysis:

This report delivers an exhaustive regional analysis of the Machine Learning-as-a-Service market and dives into country-level evaluation for top economies. This study examines the operational activities of both domestic and international competitors in particular markets, while also evaluating the influence of market participant strategies and governmental backing on the expansion of the market. In order to provide stakeholders with a comprehensive perspective for well-informed strategy formulation, the study bridges the understanding of how regional dynamics and larger trends contribute to market growth.

North America (Revenue: USD Million; 2018-2033)

US
Canada
Mexico
Europe (Revenue: USD Million; 2018-2033)

Germany
France
K.
Italy
Spain
Russia
The Netherland
Poland
Belgium
Nordic Countries
Rest of Europe
Asia Pacific (Revenue: USD Million; 2018-2033)

China
Japan
South Korea
ASEAN
Australia & New Zealand
India
Rest of Asia
South America (Revenue: USD Million; 2018-2033)

Brazil
Argentina
Peru
Colombia
Rest of South America
Middle East & Africa (Revenue: USD Million; 2018-2033)

Turkey
Israel
Saudi Arabia
Egypt
UAE
Rest of the Middle East & Africa


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Global industrial services market is growing at a brisk CAGR in value terms owing to growing need for operational quality, increasing equipment complication, product developments and increasing demand for maintenance as a service. APAC region is predicted to hold the largest market share over the next five years due to the growing industrial automation and related services in countries like India, China, and Japan. Moreover, the growing trend of cloud connectivity in Asia-Pacific countries would contribute to need for industrial internet of things (IIoT) and predictive maintenance services which will further drive the industrial services market in the region.

Global industrial services market is segmented by type, by application, by industry and by region. By industry, it is further segmented into chemicals, aerospace & defence, automotive, pharmaceuticals, metals & mining, and others. Based on industry, in 2021, oil & gas industry held the largest market share and is expected to maintain its dominance during the next five years as well due to growing demand for minimizing the unanticipated downtime and to increase the usage of industrial services.

Some of the leading players in the global industrial services market include General Electric, Metso Corporation, Siemens AG, Wood Group Mustang, Honeywell International Inc., ABB, Emerson Electric, Rockwell Automation, Samson AG, Schneider Electric, among others.

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