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Predictive Maintenance Market by Component (Solution and Service), Technique (Vibration Monitoring, Electrical Testing, Oil Analysis, Ultrasonic Leak Detectors, Shock Pulse, Infrared, and Others), Deployment Type (Cloud and On-Premise), Stakeholder (MRO, OEM/ODM, and Technology Integrators), Industry Vertical (Manufacturing, Energy & Utilities, Aerospace & Defense, Transportation & Logistics, Government, Healthcare, and Others): Global Opportunity Analysis And Industry Forecast, 2020–2027
| A02138 | Pages: 428 | Mar 2021 | 12917 Views | | |
| Author(s) : Vishwa Gaul | Tables: 202 | Charts: 97 | Formats*: | |
COVID-19
Pandemic disrupted the entire world and affected many industries.
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Request Now !Predictive Maintenance Market Insights and Forecast -2027
The global predictive maintenance market size was valued at $4,331.56 million in 2019, and is projected to reach $31,965.49 million by 2027, growing at a CAGR of 28.8% from 2020 to 2027.
During COVID-19 pandemic, manufacturing & industrial sector was significantly affected and even the IT expenditure was declined by 3 to 4%. This in turn has also affected the predictive maintenance market. However, demand for PdM solutions from healthcare & energy and utilities sector is expected to increase during the forecast period.s
Predictive maintenance is an equipment performance and condition monitoring plan that reduces the risk of a failure under normal operating conditions. The aim is to anticipate a failure and then try to avoid it by corrective maintenance. Traditional systems rely on historical data about equipment performance and previous breakdowns or simply establish periodic maintenance schedules whether or not they are required to predict the need for maintenance. Modern predictive maintenance solutions on the other hand constantly monitor equipment behavior to collect data in real time and use advance neural network and artificial techniques to decide and raise alert when a possible equipment failure is bound to happen.
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Increase in need to boost asset uptime and minimize maintenance costs, rise in investments in predictive maintenance, owing to IoT adoption, and increase in need to extend the lifespan of ageing industrial machinery are the major factors that propel the predictive maintenance market growth. Furthermore, demand for predictive maintenance is on the rise, owing to increase in need to obtain insights from implementation of new technologies. However, market development is hampered by implementation challenges and data protection issues. Furthermore, adoption of advanced technologies such as machine learning, predictive maintenance integration with IIoT, and need for remote monitoring and asset management in the aftermath of the COVID-19 pandemic are expected to further drive the predictive maintenance market.
By deployment type, the on-premise segment dominated the overall predictive maintenance market size in 2019, and is expected to maintain its dominance during the forecast period. This is attributed to its modular sensors and easier deployments in pre-existing equipment. However, cloud-based predictive maintenance solutions are expected to exhibit highest growth rate during the forecast period, owing to direct IT control, remote accessibility, internal data delivery & handling, faster data processing using advance predictive analytics, efficient resource utilization, and cost-effectiveness.
By industry vertical, the manufacturing segment dominated the global predictive maintenance market share in 2019. Manufacturing equipment maintenance, such as machinery, pumps, elevators, and industrial robots, face a number of challenges, which is why predictive maintenance has become more common in the industry. However, the healthcare sector is expected to rise at the fastest pace in the future, owing to the fact that predictive maintenance of healthcare equipment such as X-ray, MR, tomography, and mammography is one of the most important considerations for hospitals looking to improve decision-making capabilities and improve operational efficiencies.
According to an article published in March 2021 by the news magazine Manufacturing Global, 98% of businesses report that a single hour of interruption affects their productivity, costing them more than $100,000. However, predictive maintenance solutions have the potential to minimize unplanned downtime and prolong life of machinery. Owing to this, adoption of predictive maintenance solutions have increased in recent years and is expected to grow further in the future as industries become more IoT friendly.
Impact of COVID-19 Pandemic on Predictive Maintenance Market:
Lack of employees and personnel, coupled with global supply chain disruption as well as high demand for various goods during the COVID-19 pandemic encouraged companies to take extra care of their manufacturing equipment and machinery to increase output. This resulted in a surge in demand for predictive maintenance solutions across the globe.
Many companies have started to use smart sensors, advanced artificial intelligence systems, and other Industry Internet of Things (IIoT) solutions to track health and efficiency of vital machinery used in their
manufacturing process to avoid costly production downtimes.
Predictive maintenance solutions have allowed businesses to compensate for limited availability of workers during the COVID-19 pandemic as they can handle periodic monitoring, simple machinery troubleshooting, and other tasks.
The report focuses on growth prospects, restraints, and global predictive maintenance market trends. Moreover, the study includes Porter’s five forces analysis of the industry to understand impact of various factors such as bargaining power of suppliers, competitive intensity of competitors, threat of new entrants, threat of substitutes, and bargaining power of buyers on the growth of the given market.
Segment review
The global predictive maintenance market is segmented on the basis of component, deployment, technique, stakeholder, industry vertical, and region. By component, it is bifurcated into solution and service. According to deployment, it is classified into cloud and on-premise. Further, by technique, it is divided into vibration monitoring, electrical testing, oil analysis, ultrasonic leak detectors, shock pulse, infrared, and others. By stakeholder, it is classified into MRO, OEM/ODM, and technology integrators. On the basis of industry vertical, it is classified into manufacturing, energy & utilities, aerospace & defense, transportation & logistics, government, and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The key players operating in the global predictive maintenance market analysis include IBM Corporations; Microsoft; SAP SE; General Electric; Schneider Electric; Hitachi; PTC; Software AG; SAS; Engineering Consultants Group, Inc.; Expert Microsystems, Inc.; SparkCognition; C3.Ai; Uptake Technologies Inc.; Fiix Inc.; Operational Excellence (Opex) Group Ltd, TIBCO Software Inc.; Asystom; Reliability Solutions Sp. zo.o. and Sigma Industrial Precision.
Predictive Maintenance Market
By Component
Predictive Maintenance Solution segment is projected as one of the most lucrative segments during the forecast period.
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Top impacting factors
Rise in demand for increased asset uptime and lowering maintenance costs; increase in investments in predictive maintenance in industries as a result of IoT adoption; and the need to prolong lifetime of ageing industrial machinery are the major factors that propel the market growth. Furthermore, there is a rise in need for predictive maintenance as a result of a growing need to gain insights from implementation of new technologies. However, implementation problems and data security concerns hinder the market growth. Furthermore, in the aftermath of the COVID-19 pandemic, emerging technologies such as machine learning, predictive maintenance integration with IIoT, and need for remote monitoring and asset management are expected to further boost predictive maintenance market growth.
Integration of predictive maintenance with IIoT and use of machine learning
Manufacturers are adopting machine learning based predictive maintenance. It depends on large amount of historical or test data, along with tailored machine-learning algorithms, to test different scenarios and predict the errors in the system. Then it generates the alerts accordingly. When properly designed and implemented, a machine learning algorithm will learn the typical data’s behavior and identify deviation in real-time. A machine monitoring system will comprise input about diverse temperatures, engine speed, and others. The system can then predict the time of the breakdown.
Predictive Maintenance Market
By Technique
Vibration Monitoring segment accounted for the highest market share in 2019.
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When predictive maintenance is coupled with the IIoT, it can catch equipment failures in advance. Due to emergence of ‘Industry 4.0’ in the manufacturing landscape, companies are keen to adopt IIoT to achieve better insights into their operations. Predictive maintenance relies on sensors for gathering and analyzing data from various sources, such as a CMMS and critical equipment sensors. By means of this data, the IIoT can provide innovative prediction models and analytical tools which will predict catastrophes and handle them proactively.
Huge amount of data can be transmitted due to the affordability of bandwidth and storage, to offer a complete visibility over assets in a single plant and entire production network. For instance, Lubricants & filters in hydraulic valve manufacturing require IoT gateways and sensors, the oil quality can be monitored without manual assistance and maintained a constant grade.
Predictive Maintenance Market
By Deployment Model
Cloud segment is projected as one of the most lucrative segments during the forecast period.
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Ticket allocation system, cycle time monitoring, cutting fluids monitoring, cooling systems and other industries are adopting IIoT predictive maintenance to reduce the machine downtime. Thus, the integration of predictive maintenance and IIoT is expected to offer lucrative opportunities for this predictive maintenance market during the forecast period.
Real-time condition monitoring to assist in taking prompt actions
The real-time processing of underlying data makes it possible to make forecasts that form the basis for needs-based maintenance and consequently the reduction of downtimes. Dedicated condition monitoring systems are constructed with intelligent monitoring nodes, which apply adaptive as well as static rules to real-time condition data to provide immediate & local alerts. In addition, local nodes communicate with centralized web portal to permit the staff to analyze real-time data while it is happening. In addition, the interpretation of sensor data requires a combination of real-time analysis and an in-memory database to achieve a higher access speed to the data compared to hard disk drives, which fosters the adoption of real time condition monitoring. Oil & gas companies present significant opportunity to increase efficiency and reduce operational costs through better asset tracking and real-time condition monitoring.
Predictive Maintenance Market
By Stakeholders
OEM/ODM segment is projected as one of the most lucrative segments during the forecast period.
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By adopting real-time condition monitoring of critical equipment, companies can have a strong confidence in the reliability of their equipment. It will alert immediately for emerging problems with its intelligent, on-site nodes that, even during internet outages, can alert you to immediate potential problems. Due to these significant benefits, the adoption of real-time condition monitoring is expected to offer better opportunities for predictive maintenance industry.
Growth in need for remote monitoring and asset management post pandemic
The COVID-19 pandemic has made the world adopt to remote working condition, owing to social distancing and self-isolation. Industries suffered during the pandemic from the lack of on-site workers, which decreased the productivity.
Predictive Maintenance Market
By Indsutry Vertical
IT and Telecom segment led the Predictive Maintenance Market in 2019.
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Predictive maintenance solutions allowed real time monitoring of assets, with the help of advance sensors deployed on components that can detect and predict equipment failure. These solutions allowed remote monitoring of functional status equipment, which can be beneficial for times when only limited number of employees are allowed to work on-site.
Moreover, various organizations, such as research groups, academic institutions, hospitals, and consulting firms have developed a range of statistical models, predictive analytics, and forecasting exercises with the goal to assist health systems in making COVID-19 strategic decisions. These trends post pandemic have helped predictive maintenance solutions to be popularized for healthcare equipment diagnosis, remote, and constant monitoring.
Predictive Maintenance Market
By Region
Asia-Pacific would exhibit the highest CAGR of 30.3% during 2020-2027.
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Key Benefits For Stakeholders
- This study includes the analytical depiction of the global predictive maintenance market forecast and trends to determine the imminent investment pockets.
- The report presents information related to key drivers, restraints, and Predictive Maintenance Market opportunity.
- The current market size is quantitatively analyzed from 2019 to 2027 to highlight the financial competency of the predictive maintenance industry.
- Porter’s five forces analysis illustrates the potency of buyers & suppliers in the predictive maintenance market.
Key Market Segments
By Component:
- Solution
- Service
By Technique:
- Vibration Monitoring
- Electrical Testing
- Oil Analysis
- Ultrasonic Leak Detectors
- Shock Pulse
- Infrared
- Others
By Deployment Type:
- Cloud
- On-premise
By Stakeholder:
- MRO
- OEM/ODM
- Technology Integrators
By Industry Vertical:
- Manufacturing
- Energy & utilities
- Aerospace & Defense
- Transportation & logistics
- Government
- Healthcare
- Others
By Region:
- North America
- Europe
- Asia-Pacific
- LAMEA
Key Market Players
- IBM Corporations
- Microsoft
- SAP SE
- General Electric
- Schneider Electric
- Hitachi
- PTC
- Software AG
- SAS
- Engineering Consultants Group, Inc.
- Expert Microsystems, Inc.
- SparkCognition
- C3.Ai
- Uptake Technologies Inc.
- Fiix Inc.
- Opeational Excellence (Opex) Group Ltd
- TIBCO Software Inc.
- Asystom
- Sigma Industrial Precision
- Reliability Solutions Sp. zo.o.
CHAPTER 1:INTRODUCTION
1.1.REPORT DESCRIPTION
1.2.KEY MARKET SEGMENTS
1.3.RESEARCH METHODOLOGY
1.3.1.Primary research
1.3.2.Secondary research
1.3.3.Analyst tools & models
CHAPTER 2:EXECUTIVE SUMMARY
2.1.CXO PERSPECTIVE
CHAPTER 3:MARKET LANDSCAPE
3.1.MARKET DEFINITION AND SCOPE
3.2.KEY FINDINGS
3.2.1.Top investment pockets
3.2.2.Top impacting factors
3.3.PORTER'S FIVE FORCES ANALYSIS
3.4.KEY PLAYER POSITIONING
3.5.MARKET DYNAMICS
3.5.1.Drivers
3.5.1.1.The need to improve uptime of equipment and maintenance cost reduction
3.5.1.2.Increase in investment on predictive maintenance
3.5.1.1.Rise in need to extend lifetime of aging assets
3.5.2.Restraints
3.5.2.1.Lack of skilled staff
3.5.2.2.Difficult to implement
3.5.2.3.Data privacy and security concerns
3.5.3.Opportunity
3.5.3.1.Integration of predictive maintenance with IIoT and use of machine learning
3.5.3.2.Real-time condition monitoring to assist in taking prompt actions
3.5.3.3.Growth in need for remote monitoring and asset management post pandemic
3.6.VALUE CHAIN ANALYSIS
3.7.ROBOTICS ADOPTION IN MANUFACTURING
3.8.AI IMPLEMENTATION ANALYSIS ACROSS INDUSTRY VERTICALS
3.9.QUALITATIVE INSIGHTS (DETECTION AND DIAGNOSIS)
3.9.1.Case Studies
3.9.1.1.Muller industries adopted Augury’s Auguscope device for predictive maintenance
3.9.1.2.Euromicron subsidiary Telent gained IoT master agreement from Deutsche Bahn
3.9.1.3.VAALCO to adopt PIMS from INTECSEA for subsea repair campaign
3.9.1.4.Israel Electric Corporation adopted Schneider Electric enables predictive maintenance to enhance reliability
3.10.MODELS AND APPROACHES
3.10.1.Statistical Pattern Classification:
3.10.1.1.Bayesian Network
3.10.1.2.Neural networks
3.10.1.3.Linear Classification
3.10.1.4.Hybrid Models
3.10.2.Pattern Classification: Phases and Components
3.10.2.1.Training Phase
3.10.2.2.Testing Phase
3.10.3.Sub problems Pattern Classification
3.10.3.1.Feature Extraction
3.10.3.2.Over fitting
3.10.3.3.Model Selection
3.10.3.4.Prior Knowledge
3.10.3.5.Missing Features
3.10.3.6.Mereology
3.10.3.7.Segmentation
3.10.3.8.Context
3.10.3.9.Invariance’s Evidence
3.10.3.10.Pooling Costs and Risks
3.10.3.11.Computational Complexity
3.11.COVID-19 IMPACT ANALYSIS ON PREDICTIVE MAINTENANCE MARKET
3.11.1.Impact on market size
3.11.2.Consumer trends, preferences, and budget impact
3.11.3.Regulatory framework
3.11.4.Economic impact
3.11.5.Key player strategies to tackle negative impact
3.11.6.Opportunity window (due to COVID outbreak)
CHAPTER 4:PREDICTIVE MAINTENANCE MARKET, BY COMPONENT
4.1.OVERVIEW
4.2.SOLUTION
4.2.1.Key market trends, growth factors, and opportunities
4.2.2.Market size and forecast, by region
4.2.3.Market analysis, by country
4.3.SERVICE
4.3.1.Key market trends, growth factors, and opportunities
4.3.2.Market size and forecast, by region
4.3.3.Market analysis, by country
4.3.4.Professional Service
4.3.4.1.Market size and forecast
4.3.4.2.Support and Maintenance
4.3.4.3.Deployment and Integration
4.3.4.4.Training and Education
4.3.5.Managed Service
CHAPTER 5:PREDICTIVE MAINTENANCE MARKET, BY TECHNIQUE
5.1.OVERVIEW
5.2.VIBRATION MONITORING
5.2.1.Key market trends, growth factors, and opportunities
5.2.2.Market size and forecast, by region
5.2.3.Market analysis, by country
5.3.ELECTRICAL TESTING
5.3.1.Key market trends, growth factors, and opportunities
5.3.2.Market size and forecast, by region
5.3.3.Market analysis, by country
5.4.OIL ANALYSIS
5.4.1.Key market trends, growth factors, and opportunities
5.4.2.Market size and forecast, by region
5.4.3.Market analysis, by country
5.5.ULTRASONIC LEAK DETECTORS
5.5.1.Key market trends, growth factors, and opportunities
5.5.2.Market size and forecast, by region
5.5.3.Market analysis, by country
5.6.SHOCK PULSE
5.6.1.Key market trends, growth factors, and opportunities
5.6.2.Market size and forecast, by region
5.6.3.Market analysis, by country
5.7.INFRARED
5.7.1.Key market trends, growth factors, and opportunities
5.7.2.Market size and forecast, by region
5.7.3.Market analysis, by country
5.8.OTHERS
5.8.1.Key market trends, growth factors, and opportunities
5.8.2.Market size and forecast, by region
5.8.3.Market analysis, by country
CHAPTER 6:PREDICTIVE MAINTENANCE MARKET, BY DEPLOYMENT TYPE
6.1.OVERVIEW
6.2.CLOUD
6.2.1.Key market trends, growth factors, and opportunities
6.2.2.Market size and forecast, by region
6.2.3.Market analysis, by country
6.3.ON-PREMISE
6.3.1.Key market trends, growth factors, and opportunities
6.3.2.Market size and forecast, by region
6.3.3.Market analysis, by country
CHAPTER 7:PREDICTIVE MAINTENANCE MARKET, BY STAKEHOLDER
7.1.OVERVIEW
7.2.MRO
7.2.1.Key market trends, growth factors, and opportunities
7.2.2.Market size and forecast, by region
7.2.3.Market analysis, by country
7.3.OEM/ODM
7.3.1.Key market trends, growth factors, and opportunities
7.3.2.Market size and forecast, by region
7.3.3.Market analysis, by country
7.4.TECHNOLOGY INTEGRATORS
7.4.1.Key market trends, growth factors, and opportunities
7.4.2.Market size and forecast, by region
7.4.3.Market analysis, by country
7.4.4.Pure play
7.4.5.End-to-end
CHAPTER 8:PREDICTIVE MAINTENANCE MARKET, BY INDUSTRY VERTICAL
8.1.OVERVIEW
8.2.MANUFACTURING
8.2.1.Key market trends, growth factors, and opportunities
8.2.2.Market size and forecast, by region
8.2.3.Market analysis, by country
8.3.ENERGY & UTILITIES
8.3.1.Key market trends, growth factors, and opportunities
8.3.2.Market size and forecast, by region
8.3.3.Market analysis, by country
8.4.AEROSPACE & DEFENSE
8.4.1.Key market trends, growth factors, and opportunities
8.4.2.Market size and forecast, by region
8.4.3.Market analysis, by country
8.5.TRANSPORTATION & LOGISTICS
8.5.1.Key market trends, growth factors, and opportunities
8.5.2.Market size and forecast, by region
8.5.3.Market analysis, by country
8.6.GOVERNMENT
8.6.1.Key market trends, growth factors, and opportunities
8.6.2.Market size and forecast, by region
8.6.3.Market analysis, by country
8.7.HEALTHCARE
8.7.1.Key market trends, growth factors, and opportunities
8.7.2.Market size and forecast, by region
8.7.3.Market analysis, by country
8.8.OTHERS
8.8.1.Key market trends, growth factors, and opportunities
8.8.2.Market size and forecast, by region
8.8.3.Market analysis, by country
CHAPTER 9:PREDICTIVE MAINTENANCE MARKET, BY REGION
9.1.OVERVIEW
9.2.NORTH AMERICA
9.2.1.Key market trends, growth factors, and opportunities
9.2.2.Market size and forecast, by component
9.2.3.Market size and forecast, by technique
9.2.4.Market size and forecast, by deployment type
9.2.5.Market size and forecast, by stakeholders
9.2.6.Market size and forecast, by industry vertical
9.2.7.Market analysis, by country
9.2.7.1.U.S.
9.2.7.1.1.Market size and forecast, by component
9.2.7.1.2.Market size and forecast, by technique
9.2.7.1.3.Market size and forecast, by deployment type
9.2.7.1.4.Market size and forecast, by stakeholders
9.2.7.1.5.Market size and forecast, by industry vertical
9.2.7.2.Canada
9.2.7.2.1.Market size and forecast, by component
9.2.7.2.2.Market size and forecast, by technique
9.2.7.2.3.Market size and forecast, by deployment type
9.2.7.2.4.Market size and forecast, by stakeholders
9.2.7.2.5.Market size and forecast, by industry vertical
9.3.EUROPE
9.3.1.Key market trends, growth factors, and opportunities
9.3.2.Market size and forecast, by component
9.3.3.Market size and forecast, by technique
9.3.4.Market size and forecast, by deployment type
9.3.5.Market size and forecast, by stakeholders
9.3.6.Market size and forecast, by industry vertical
9.3.7.Market analysis, by country
9.3.7.1.Germany
9.3.7.1.1.Market size and forecast, by component
9.3.7.1.2.Market size and forecast, by technique
9.3.7.1.3.Market size and forecast, by deployment type
9.3.7.1.4.Market size and forecast, by stakeholders
9.3.7.1.5.Market size and forecast, by industry vertical
9.3.7.2.France
9.3.7.2.1.Market size and forecast, by component
9.3.7.2.2.Market size and forecast, by technique
9.3.7.2.3.Market size and forecast, by deployment type
9.3.7.2.4.Market size and forecast, by stakeholders
9.3.7.2.5.Market size and forecast, by industry vertical
9.3.7.3.UK
9.3.7.3.1.Market size and forecast, by component
9.3.7.3.2.Market size and forecast, by technique
9.3.7.3.3.Market size and forecast, by deployment type
9.3.7.3.4.Market size and forecast, by stakeholders
9.3.7.3.5.Market size and forecast, by industry vertical
9.3.7.4.Italy
9.3.7.4.1.Market size and forecast, by component
9.3.7.4.2.Market size and forecast, by technique
9.3.7.4.3.Market size and forecast, by deployment type
9.3.7.4.4.Market size and forecast, by stakeholders
9.3.7.4.5.Market size and forecast, by industry vertical
9.3.7.5.Rest of Europe
9.3.7.5.1.Market size and forecast, by component
9.3.7.5.2.Market size and forecast, by technique
9.3.7.5.3.Market size and forecast, by deployment type
9.3.7.5.4.Market size and forecast, by stakeholders
9.3.7.5.5.Market size and forecast, by industry vertical
9.4.ASIA-PACIFIC
9.4.1.Key market trends, growth factors, and opportunities
9.4.2.Market size and forecast, by component
9.4.3.Market size and forecast, by technique
9.4.4.Market size and forecast, by deployment type
9.4.5.Market size and forecast, by stakeholders
9.4.6.Market size and forecast, by industry vertical
9.4.7.Market analysis, by country
9.4.7.1.Japan
9.4.7.1.1.Market size and forecast, by component
9.4.7.1.2.Market size and forecast, by technique
9.4.7.1.3.Market size and forecast, by deployment type
9.4.7.1.4.Market size and forecast, by stakeholders
9.4.7.1.5.Market size and forecast, by industry vertical
9.4.7.2.China
9.4.7.2.1.Market size and forecast, by component
9.4.7.2.2.Market size and forecast, by technique
9.4.7.2.3.Market size and forecast, by deployment type
9.4.7.2.4.Market size and forecast, by stakeholders
9.4.7.2.5.Market size and forecast, by industry vertical
9.4.7.3.India
9.4.7.3.1.Market size and forecast, by component
9.4.7.3.2.Market size and forecast, by technique
9.4.7.3.3.India size and forecast, by deployment type
9.4.7.3.4.Market size and forecast, by stakeholders
9.4.7.3.5.Market size and forecast, by industry vertical
9.4.7.4.South Korea
9.4.7.4.1.Market size and forecast, by component
9.4.7.4.2.Market size and forecast, by technique
9.4.7.4.3.Market size and forecast, by deployment type
9.4.7.4.4.Market size and forecast, by stakeholders
9.4.7.4.5.Market size and forecast, by industry vertical
9.4.7.5.Rest of Asia-Pacific
9.4.7.5.1.Market size and forecast, by component
9.4.7.5.2.Market size and forecast, by technique
9.4.7.5.3.Market size and forecast, by deployment type
9.4.7.5.4.Market size and forecast, by stakeholders
9.4.7.5.5.Market size and forecast, by industry vertical
9.5.LAMEA
9.5.1.Key market trends, growth factors, and opportunities
9.5.2.Market size and forecast, by component
9.5.3.Market size and forecast, by technique
9.5.4.Market size and forecast, by deployment type
9.5.5.Market size and forecast, by stakeholders
9.5.6.Market size and forecast, by industry vertical
9.5.7.Market analysis, by country
9.5.7.1.Latin America
9.5.7.1.1.Market size and forecast, by component
9.5.7.1.2.Market size and forecast, by technique
9.5.7.1.3.Market size and forecast, by deployment type
9.5.7.1.4.Market size and forecast, by stakeholders
9.5.7.1.5.Market size and forecast, by industry vertical
9.5.7.2.Middle East
9.5.7.2.1.Market size and forecast, by component
9.5.7.2.2.Market size and forecast, by technique
9.5.7.2.3.Market size and forecast, by deployment type
9.5.7.2.4.Market size and forecast, by stakeholders
9.5.7.2.5.Market size and forecast, by industry vertical
9.5.7.3.Africa
9.5.7.3.1.Market size and forecast, by component
9.5.7.3.2.Market size and forecast, by technique
9.5.7.3.3.Market size and forecast, by deployment type
9.5.7.3.4.Market size and forecast, by stakeholders
9.5.7.3.5.Market size and forecast, by industry vertical
CHAPTER 10:COMPETITIVE LANDSCAPE
10.1.COMPETITIVE DASHBOARD
10.2.TOP WINNING STRATEGIES
10.3.KEY DEVELOPMENTS
10.3.1.Product development
10.3.2.Partnership
10.3.3.Product Launch
10.3.4.Acquisition
10.3.5.Agreement
10.3.6.Collaboration
10.3.7.Business Expansion
CHAPTER 11:COMPANY PROFILES
11.1.ASYSTOM
11.1.1.Company overview
11.1.2.Key executives
11.1.3.Company snapshot
11.1.4.Product portfolio
11.1.5.Key strategic moves and developments
11.2.C3.AI, INC.
11.2.1.Company overview
11.2.2.Key executives
11.2.3.Company snapshot
11.2.4.Operating business segments
11.2.5.Product portfolio
11.2.6.Business performance
11.2.7.Key strategic moves and developments
11.3.ENGINEERING CONSULTANTS GROUP, INC.
11.3.1.Company overview
11.3.2.Key executives
11.3.3.Company snapshot
11.3.4.Product portfolio
11.3.5.Key strategic moves and developments
11.4.EXPERT MICROSYSTEMS, INC.
11.4.1.Company overview
11.4.2.Key Executives
11.4.3.Company snapshot
11.4.4.Product portfolio
11.5.FIIX INC.
11.5.1.Company overview
11.5.2.Key executives
11.5.3.Company snapshot
11.5.4.Product portfolio
11.5.5.Key strategic moves and developments
11.6.OPERATIONAL EXCELLENCE (OPEX) GROUP LTD
11.6.1.Company overview
11.6.2.Key Executives
11.6.3.Company snapshot
11.6.4.Product portfolio
11.6.5.Key strategic moves and developments
11.7.SIGMA INDUSTRIAL PRECISION
11.7.1.Company overview
11.7.2.Key Executives
11.7.3.Company snapshot
11.7.4.Product portfolio
11.8.SPARKCOGNITION
11.8.1.Company overview
11.8.2.Key Executives
11.8.3.Company snapshot
11.8.4.Product portfolio
11.8.5.Key strategic moves and developments
11.9.TIBCO SOFTWARE INC
11.9.1.Company overview
11.9.2.Key Executives
11.9.3.Company snapshot
11.9.4.Product portfolio
11.9.5.Key strategic moves and developments
11.10.UPTAKE TECHNOLOGIES INC.
11.10.1.Company overview
11.10.2.Key Executives
11.10.3.Company snapshot
11.10.4.Product portfolio
11.10.5.Key strategic moves and developments
11.11.GENERAL ELECTRIC
11.11.1.Company overview
11.11.2.Key executives
11.11.3.Company snapshot
11.11.4.Operating business segments
11.11.5.Product portfolio
11.11.6.R&D expenditure
11.11.7.Business performance
11.11.8.Key strategic moves and developments
11.12.HITACHI, LTD.
11.12.1.Company overview
11.12.2.Key executives
11.12.3.Company snapshot
11.12.4.Operating business segments
11.12.5.Product portfolio
11.12.6.R&D Expenditure
11.12.7.Business performance
11.12.8.Key strategic moves and developments
11.13.INTERNATIONAL BUSINESS MACHINES CORPORATION
11.13.1.Company overview
11.13.2.Key Executives
11.13.3.Company snapshot
11.13.4.Operating business segments
11.13.5.Product portfolio
11.13.6.R&D Expenditure
11.13.7.Business performance
11.13.8.Key strategic moves and developments
11.14.MICROSOFT CORPORATION
11.14.1.Company overview
11.14.2.Key executives
11.14.3.Company snapshot
11.14.4.Operating business segments
11.14.5.Product portfolio
11.14.6.R&D Expenditure
11.14.7.Business performance
11.14.8.Key strategic moves and developments
11.15.PTC INC.
11.15.1.Company overview
11.15.2.Key Executives
11.15.3.Company snapshot
11.15.4.Operating business segments
11.15.5.Product portfolio
11.15.6.R&D Expenditure
11.15.7.Business performance
11.15.8.Key strategic moves and developments
11.16.SAP
11.16.1.Company overview
11.16.2.Key Executives
11.16.3.Company snapshot
11.16.4.Operating business segments
11.16.5.Product portfolio
11.16.6.R&D Expenditure
11.16.7.Business performance
11.16.8.Key strategic moves and developments
11.17.SAS INSTITUTE INC.
11.17.1.Company overview
11.17.2.Key Executives
11.17.3.Company snapshot
11.17.4.Product portfolio
11.17.5.Key strategic moves and developments
11.18.SCHNEIDER ELECTRIC SE
11.18.1.Company overview
11.18.2.Key executives
11.18.3.Company snapshot
11.18.4.Operating business segments
11.18.5.Product portfolio
11.18.6.R&D Expenditure
11.18.7.Business performance
11.18.8.Key strategic moves and developments
11.19.SOFTWARE AG
11.19.1.Company overview
11.19.2.Key Executives
11.19.3.Company snapshot
11.19.4.Operating business segments
11.19.5.Product portfolio
11.19.6.R&D Expenditure
11.19.7.Business performance
11.19.8.Key strategic moves and developments
11.20.RELIABILITY SOLUTIONS SP. Z O.O.
11.20.1.Company overview
11.20.2.Key Executives
11.20.3.Company snapshot
11.20.4.Product portfolio
11.20.5.Key strategic moves and developments
LIST OF TABLES
TABLE 01.GLOBAL PREDICTIVE MAINTENANCE MARKET, BY COMPONENT, 2019-2027 ($MILLION)
TABLE 02.PREDICTIVE MAINTENANCE MARKET FOR SOLUTION REVENUE, BY REGION 2019-2027 ($MILLION)
TABLE 03.PREDICTIVE MAINTENANCE MARKET REVENUE FOR SERVICE, BY REGION, 2019-2027 ($MILLION)
TABLE 04.GLOBAL PREDICTIVE MAINTENANCE MARKET, BY SERVICE, 2019-2027 ($MILLION)
TABLE 05.GLOBAL PREDICTIVE MAINTENANCE MARKET, BY PROFESSIONAL SERVICE, 2019-2027 ($MILLION)
TABLE 06.GLOBAL PREDICTIVE MAINTENANCE MARKET, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 07.PREDICTIVE MAINTENANCE MARKET REVENUE FOR VIBRATION MONITORING, BY REGION 2019-2027 ($MILLION)
TABLE 08.PREDICTIVE MAINTENANCE MARKET REVENUE FOR ELECTRICAL TESTING, BY REGION, 2019-2027 ($MILLION)
TABLE 09.PREDICTIVE MAINTENANCE MARKET REVENUE FOR OIL ANALYSIS, BY REGION, 2019-2027 ($MILLION)
TABLE 10.PREDICTIVE MAINTENANCE MARKET REVENUE FOR ULTRASONIC LEAK DETECTORS, BY REGION, 2019-2027 ($MILLION)
TABLE 11.PREDICTIVE MAINTENANCE MARKET REVENUE FOR SHOCK PULSE, BY REGION, 2019-2027 ($MILLION)
TABLE 12.PREDICTIVE MAINTENANCE MARKET REVENUE FOR INFRARED, BY REGION 2019-2027 ($MILLION)
TABLE 13.PREDICTIVE MAINTENANCE MARKET REVENUE FOR OTHERS, BY REGION 2019-2027 ($MILLION)
TABLE 14.GLOBAL PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 15.PREDICTIVE MAINTENANCE MARKET REVENUE FOR CLOUD, BY REGION 2019-2027 ($MILLION)
TABLE 16.PREDICTIVE MAINTENANCE MARKET REVENUE FOR ON-PREMISE, BY REGION 2019-2027 ($MILLION)
TABLE 17.GLOBAL PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDER, 2019-2027 ($MILLION)
TABLE 18.PREDICTIVE MAINTENANCE MARKET REVENUE FOR MRO, BY REGION 2019-2027 ($MILLION)
TABLE 19.PREDICTIVE MAINTENANCE MARKET REVENUE FOR OEM/ODM, BY REGION 2019-2027 ($MILLION)
TABLE 20.GLOBAL PREDICTIVE MAINTENANCE MARKET, BY TECHNOLOGY INTEGRATORS, 2019-2027 ($MILLION)
TABLE 21.PREDICTIVE MAINTENANCE MARKET REVENUE FOR TECHNOLOGY INTEGRATORS, BY REGION 2019-2027 ($MILLION)
TABLE 22.GLOBAL PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 23.PREDICTIVE MAINTENANCE MARKET REVENUE FOR MANUFACTURING, BY REGION 2019-2027 ($MILLION)
TABLE 24.PREDICTIVE MAINTENANCE MARKET REVENUE FOR ENERGY & UTILITIES, BY REGION 2019-2027 ($MILLION)
TABLE 25.PREDICTIVE MAINTENANCE MARKET REVENUE FOR AEROSPACE & DEFENSE, BY REGION 2019-2027 ($MILLION)
TABLE 26.PREDICTIVE MAINTENANCE MARKET REVENUE FOR TRANSPORTATION & LOGISTICS, BY REGION 2019-2027 ($MILLION)
TABLE 27.PREDICTIVE MAINTENANCE MARKET REVENUE FOR GOVERNMENT, BY REGION 2019-2027 ($MILLION)
TABLE 28.PREDICTIVE MAINTENANCE MARKET REVENUE FOR HEALTHCARE, BY REGION 2019-2027 ($MILLION)
TABLE 29.PREDICTIVE MAINTENANCE MARKET REVENUE FOR OTHERS, BY REGION 2019-2027 ($MILLION)
TABLE 30.PREDICTIVE MAINTENANCE MARKET REVENUE, BY REGION, 2019–2027($MILLION)
TABLE 31.NORTH AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 32.NORTH AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 33.NORTH AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 34.NORTH AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 35.NORTH AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 36.NORTH AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY COUNTRY, 2019-2027 ($MILLION)
TABLE 37.U.S. PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 38.U.S. PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 39.U.S. PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 40.U.S. PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 41.U.S. PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 42.CANADA PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 43.CANADA PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 44.CANADA PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 45.CANADA PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 46.CANADA PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 47.EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 48.EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 49.EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 50.EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 51.EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 52.EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, BY COUNTRY, 2019-2027 ($MILLION)
TABLE 53.GERMANY PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 54.GERMANY PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 55.GERMANY PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 56.GERMANY PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 57.GERMANY PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 58.FRANCE PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 59.FRANCE PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 60.FRANCE PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 61.FRANCE PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 62.FRANCE PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 63.UK PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 64.UK PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 65.UK PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 66.UK PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 67.UK PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 68.ITALY PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 69.ITALY PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 70.ITALY PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 71.ITALY PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 72.ITALY PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 73.REST OF EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 74.REST OF EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 75.REST OF EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 76.REST OF EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 77.REST OF EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 78.ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 79.ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 80.ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 81.ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 82.ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 83.ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, BY COUNTRY, 2019-2027 ($MILLION)
TABLE 84.JAPAN PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 85.JAPAN PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 86.JAPAN PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 87.JAPAN PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 88.JAPAN PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 89.CHINA PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 90.CHINA PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 91.CHINA PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 92.CHINA PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 93.CHINA PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 94.INDIA PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 95.INDIA PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 96.INDIA PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 97.INDIA PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 98.INDIA PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 99.SOUTH KOREA PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 100.SOUTH KOREA PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 101.SOUTH KOREA PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 102.SOUTH KOREA PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 103.SOUTH KOREA PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 104.REST OF ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 105.REST OF ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 106.REST OF ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 107.REST OF ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 108.REST OF ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 109.LAMEA PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 110.LAMEA PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 111.LAMEA PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 112.LAMEA PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 113.LAMEA PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 114.LAMEA PREDICTIVE MAINTENANCE MARKET REVENUE, BY COUNTRY, 2019-2027 ($MILLION)
TABLE 115.LATIN AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 116.LATIN AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 117.LATIN AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 118.LATIN AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 119.LATIN AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 120.MIDDLE EAST PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 121.MIDDLE EAST PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 122.MIDDLE EAST PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 123.MIDDLE EAST PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 124.MIDDLE EAST PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 125.AFRICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 126.AFRICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019-2027 ($MILLION)
TABLE 127.AFRICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY DEPLOYMENT TYPE, 2019-2027 ($MILLION)
TABLE 128.AFRICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY STAKEHOLDERS, 2019-2027 ($MILLION)
TABLE 129.AFRICA PREDICTIVE MAINTENANCE MARKET REVENUE, BY INDUSTRY VERTICAL, 2019-2027 ($MILLION)
TABLE 130.PRODUCT DEVELOPMENT (2017-2020)
TABLE 131.PARTNERSHIP (2017-2020)
TABLE 132.PRODUCT LAUNCH (2017-2020)
TABLE 133.ACQUISITION (2017-2020)
TABLE 134.AGREEMENT (2017-2020)
TABLE 135.COLLABORATION (2017-2021)
TABLE 136.BUSINESS EXPANSION (2017-2020)
TABLE 137.ASYSTOM: KEY EXECUTIVES
TABLE 138.ASYSTOM: COMPANY SNAPSHOT
TABLE 139.ASYSTOM: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 140.C3.AI, INC.: KEY EXECUTIVES
TABLE 141.C3.AI, INC.: COMPANY SNAPSHOT
TABLE 142.C3.AI, INC.: OPERATING SEGMENTS
TABLE 143.C3.AI, INC.: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 144.ENGINEERING CONSULTANTS GROUP, INC.: KEY EXECUTIVES
TABLE 145.ENGINEERING CONSULTANTS GROUP, INC.: COMPANY SNAPSHOT
TABLE 146.ENGINEERING CONSULTANTS GROUP, INC.: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 147.EXPERT MICROSYSTEMS, INC.: KEY EXECUTIVES
TABLE 148.EXPERT MICROSYSTEMS, INC.: COMPANY SNAPSHOT
TABLE 150.FIIX INC.: KEY EXECUTIVES
TABLE 151.FIIX INC.: COMPANY SNAPSHOT
TABLE 152.FIIX INC.: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 153.OPERATIONAL EXCELLENCE (OPEX) GROUP LTD: KEY EXECUTIVES
TABLE 154.OPERATIONAL EXCELLENCE (OPEX) GROUP LTD: COMPANY SNAPSHOT
TABLE 155.OPERATIONAL EXCELLENCE (OPEX) GROUP LTD: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 156.SIGMA INDUSTRIAL PRECISION: KEY EXECUTIVES
TABLE 157.SIGMA INDUSTRIAL PRECISION: COMPANY SNAPSHOT
TABLE 158.SIGMA INDUSTRIAL PRECISION: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 159.SPARKCOGNITION: KEY EXECUTIVES
TABLE 160.SPARKCOGNITION: COMPANY SNAPSHOT
TABLE 161.SPARKCOGNITION: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 162.TIBCO SOFTWARE INC.: KEY EXECUTIVES
TABLE 163.TIBCO SOFTWARE INC.: COMPANY SNAPSHOT
TABLE 164.TIBCO SOFTWARE INC.: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 165.UPTAKE TECHNOLOGIES INC.: KEY EXECUTIVES
TABLE 166.UPTAKE TECHNOLOGIES INC.: COMPANY SNAPSHOT
TABLE 167.UPTAKE TECHNOLOGIES INC.: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 169.GENERAL ELECTRIC: COMPANY SNAPSHOT
TABLE 170.GENERAL ELECTRIC: OPERATING SEGMENTS
TABLE 171.GENERAL ELECTRIC: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 173.HITACHI, LTD.: COMPANY SNAPSHOT
TABLE 174.HITACHI, LTD.: OPERATING SEGMENTS
TABLE 175.HITACHI LTD: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 176.INTERNATIONAL BUSINESS MACHINES CORPORATION: KEY EXECUTIVES
TABLE 177.INTERNATIONAL BUSINESS MACHINES CORPORATION: COMPANY SNAPSHOT
TABLE 178.INTERNATIONAL BUSINESS MACHINES CORPORATION: OPERATING SEGMENTS
TABLE 179.INTERNATIONAL BUSINESS MACHINES CORPORATION: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 180.MICROSOFT CORPORATION: KEY EXECUTIVES
TABLE 181.MICROSOFT CORPORATION: COMPANY SNAPSHOT
TABLE 182.MICROSOFT CORPORATION: OPERATING SEGMENTS
TABLE 183.MICROSOFT CORPORATION: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 184.PTC INC.: KEY EXECUTIVES
TABLE 185.PTC INC.: COMPANY SNAPSHOT
TABLE 186.PTC INC.: OPERATING SEGMENTS
TABLE 187.PTC INC.: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 188.SAP: KEY EXECUTIVES
TABLE 189.SAP: COMPANY SNAPSHOT
TABLE 190.SAP: OPERATING SEGMENTS
TABLE 191.SAP SE: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 192.SAS INSTITUTE INC.: KEY EXECUTIVES
TABLE 193.SAS INSTITUTE INC.: COMPANY SNAPSHOT
TABLE 194.SAS INSTITUTE INC.: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 195.SCHNEIDER ELECTRIC: KEY EXECUTIVES
TABLE 196.SCHNEIDER ELECTRIC: COMPANY SNAPSHOT
TABLE 197.SCHNEIDER ELECTRIC: OPERATING SEGMENTS
TABLE 198.SCHNEIDER ELECTRIC SE: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 199.SOFTWARE AG: KEY EXECUTIVES
TABLE 200.SOFTWARE AG: COMPANY SNAPSHOT
TABLE 201.SOFTWARE AG: OPERATING SEGMENTS
TABLE 202.SOFTWARE AG: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
TABLE 203.RELIABILITY SOLUTIONS SP. Z O.O.: KEY EXECUTIVES
TABLE 204.RELIABILITY SOLUTIONS SP. Z O.O.: COMPANY SNAPSHOT
TABLE 205.RELIABILITY SOLUTIONS SP. Z O.O.: PREDICTIVE MAINTENANCE PRODUCT PORTFOLIO
LIST OF FIGURES
FIGURE 01.KEY MARKET SEGMENTS
FIGURE 02.PREDICTIVE MAINTENANCE MARKET, 2019–2027
FIGURE 03.PREDICTIVE MAINTENANCE MARKET, BY REGION, 2019–2027
FIGURE 04.TOP INVESTMENT POCKETS
FIGURE 05.TOP IMPACTING FACTORS
FIGURE 06.BARGAINING POWER OF SUPPLIERS
FIGURE 07.THREAT OF NEW ENTRANTS
FIGURE 08.THREAT OF SUBSTITUTES
FIGURE 09.COMPETITIVE RIVALRY
FIGURE 10.BARGAINING POWER AMONG BUYERS
FIGURE 11.KEY PLAYER POSITIONING
FIGURE 12.VALUE CHAIN ANALYSIS
FIGURE 13.END TO END SAP DIGITAL OPERATION ARCHITECURE OVERVIEW
FIGURE 14.GLOBAL PREDICTIVE MAINTENANCE MARKET REVENUE, BY COMPONENT, 2019–2027 ($MILLION)
FIGURE 15.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE MAINTENANCE MARKET FOR SOLUTION, BY COUNTRY, 2019 & 2027 (%)
FIGURE 16.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE MAINTENANCE MARKET FOR SERVICE, BY COUNTRY, 2019 & 2027 (%)
FIGURE 17.GLOBAL PREDICTIVE MAINTENANCE MARKET REVENUE, BY TECHNIQUE, 2019–2027 ($MILLION)
FIGURE 18.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE MAINTENANCE MARKET FOR VIBRATION MONITORING, BY COUNTRY, 2019 & 2027 (%)
FIGURE 19.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE MAINTENANCE MARKET FOR ELECTRICAL TESTING, BY COUNTRY, 2019 & 2027 (%)
FIGURE 20.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE MAINTENANCE MARKET FOR OIL ANALYSIS, BY COUNTRY, 2019 & 2027 (%)
FIGURE 21.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE MAINTENANCE MARKET FOR ULTRASONIC LEAK DETECTORS, BY COUNTRY, 2019 & 2027 (%)
FIGURE 22.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE MAINTENANCE MARKET FOR SHOCK PULSE, BY COUNTRY, 2019 & 2027 (%)
FIGURE 23.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE MAINTENANCE MARKET FOR INFRARED, BY COUNTRY, 2019 & 2027 (%)
FIGURE 24.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE MAINTENANCE MARKET FOR OTHERS, BY COUNTRY, 2019 & 2027 (%)
FIGURE 25.GLOBAL PREDICTIVE MAINTENANCE MARKET, BY DEPLOYMENT TYPE, 2018-2026
FIGURE 26.COMPARATIVE SHARE ANALYSIS PREDICTIVE MAINTENANCE MARKET FOR CLOUD, BY COUNTRY, 2019 & 2027 (%)
FIGURE 27.COMPARATIVE SHARE ANALYSIS PREDICTIVE MAINTENANCE MARKET FOR ON-PREMISE, BY COUNTRY, 2019 & 2027 (%)
FIGURE 28.GLOBAL PREDICTIVE MAINTENANCE MARKET, BY STAKEHOLDER, 2018-2026
FIGURE 29.COMPARATIVE SHARE ANALYSIS PREDICTIVE MAINTENANCE MARKET FOR MRO, BY COUNTRY, 2019 & 2027 (%)
FIGURE 30.COMPARATIVE SHARE ANALYSIS PREDICTIVE MAINTENANCE MARKET FOR OEM/ODM, BY COUNTRY, 2019 & 2027 (%)
FIGURE 31.COMPARATIVE SHARE ANALYSIS PREDICTIVE MAINTENANCE MARKET FOR TECHNOLOGY INTEGRATORS, BY COUNTRY, 2019 & 2027 (%)
FIGURE 32.GLOBAL PREDICTIVE MAINTENANCE MARKET, BY INDUSTRY VERTICAL, 2018-2026
FIGURE 33.COMPARATIVE SHARE ANALYSIS PREDICTIVE MAINTENANCE MARKET FOR MANUFACTURING, BY COUNTRY, 2019 & 2027 (%)
FIGURE 34.COMPARATIVE SHARE ANALYSIS PREDICTIVE MAINTENANCE MARKET FOR ENERGY & UTILITIES, BY COUNTRY, 2019 & 2027 (%)
FIGURE 35.COMPARATIVE SHARE ANALYSIS PREDICTIVE MAINTENANCE MARKET FOR AEROSPACE & DEFENSE, BY COUNTRY, 2019 & 2027 (%)
FIGURE 36.COMPARATIVE SHARE ANALYSIS PREDICTIVE MAINTENANCE MARKET FOR TRANSPORTATION & LOGISTICS, BY COUNTRY, 2019 & 2027 (%)
FIGURE 37.COMPARATIVE SHARE ANALYSIS PREDICTIVE MAINTENANCE MARKET FOR GOVERNMENT, BY COUNTRY, 2019 & 2027 (%)
FIGURE 38.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE MAINTENANCE MARKET FOR HEALTHCARE, BY COUNTRY, 2019 & 2027 (%)
FIGURE 39.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE MAINTENANCE MARKET FOR OTHERS, BY COUNTRY, 2019 & 2027 (%)
FIGURE 40.U.S. PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 41.CANADA PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 42.GERMANY PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 43.FRANCE PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 44.UK PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 45.ITALY PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 46.REST OF EUROPE PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 47.JAPAN PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 48.CHINA PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 49.INDIA PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 50.SOUTH KOREA PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 51.REST OF ASIA-PACIFIC PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 52.LATIN AMERICA PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 53.MIDDLE EAST PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 54.AFRICA PREDICTIVE MAINTENANCE MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 55.COMPETITIVE DASHBOARD
FIGURE 56.COMPETITIVE DASHBOARD
FIGURE 57.COMPETITIVE DASHBOARD
FIGURE 58.COMPETITIVE DASHBOARD
FIGURE 59.COMPETITIVE HEATMAP OF KEY PLAYERS
FIGURE 60.TOP WINNING STRATEGIES, BY YEAR, 2017-2020
FIGURE 61.TOP WINNING STRATEGIES, BY DEVELOPMENT, 2017-2020
FIGURE 62.TOP WINNING STRATEGIES, BY COMPANY, 2017-2020
FIGURE 63.C3.AI, INC.: REVENUE, 2017–2019 ($MILLION)
FIGURE 64.C3.AI, INC.: REVENUE SHARE, BY SEGMENT, 2019 (%)
FIGURE 65.C3.AI, INC.: REVENUE SHARE, BY REGION, 2019 (%)
FIGURE 66.R&D EXPENDITURE, 2018-2020 ($MILLION)
FIGURE 67.GENERAL ELECTRIC: REVENUE, 2018-2020 ($MILLION)
FIGURE 68.GENERAL ELECTRIC: REVENUE SHARE, BY SEGMENT, 2020 (%)
FIGURE 69.GENERAL ELECTRIC: REVENUE SHARE, BY REGION, 2020 (%)
FIGURE 70.R&D EXPENDITURE, 2017-2019 ($MILLION)
FIGURE 71.HITACHI, LTD.: REVENUE, 2017-2019 ($MILLION)
FIGURE 72.HITACHI, LTD.: REVENUE SHARE, BY SEGMENT, 2019 (%)
FIGURE 73.HITACHI, LTD.: REVENUE SHARE, BY REGION, 2019 (%)
FIGURE 74.R&D EXPENDITURE, 2017–2019 ($MILLION)
FIGURE 75.INTERNATIONAL BUSINESS MACHINES CORPORATION: REVENUE, 2017–2019 ($MILLION)
FIGURE 76.INTERNATIONAL BUSINESS MACHINES CORPORATION: REVENUE SHARE, BY SEGMENT, 2019 (%)
FIGURE 77.INTERNATIONAL BUSINESS MACHINES CORPORATION: REVENUE SHARE, BY REGION, 2019 (%)
FIGURE 78.R&D EXPENDITURE, 2017–2019 ($MILLION)
FIGURE 79.MICROSOFT CORPORATION: REVENUE, 2017–2019 ($MILLION)
FIGURE 80.MICROSOFT CORPORATION: REVENUE SHARE, BY SEGMENT, 2019 (%)
FIGURE 81.MICROSOFT CORPORATION: REVENUE SHARE, BY REGION, 2019 (%)
FIGURE 82.R&D EXPENDITURE, 2017-2019 ($MILLION)
FIGURE 83.PTC INC.: REVENUE, 2017-2019 ($MILLION)
FIGURE 84.PTC INC.: REVENUE SHARE, BY SEGMENT, 2018 (%)
FIGURE 85.PTC INC.: REVENUE SHARE, BY REGION, 2018 (%)
FIGURE 86.R&D EXPENDITURE, 2017–2018 ($MILLION)
FIGURE 87.SAP: REVENUE, 2017–2019 ($MILLION)
FIGURE 88.SAP: REVENUE SHARE, BY SEGMENT, 2018 (%)
FIGURE 89.SAP: REVENUE SHARE, BY REGION, 2019 (%)
FIGURE 90.R&D EXPENDITURE, 2017–2019 ($MILLION)
FIGURE 91.SCHNEIDER ELECTRIC SE: REVENUE, 2017–2019 ($MILLION)
FIGURE 92.SCHNEIDER ELECTRIC SE: REVENUE SHARE, BY SEGMENT, 2019 (%)
FIGURE 93.SCHNEIDER ELECTRIC SE: REVENUE SHARE, BY REGION, 2019 (%)
FIGURE 94.R&D EXPENDITURE, 2018–2019 ($MILLION)
FIGURE 95.SOFTWARE AG: REVENUE, 2017–2019 ($MILLION)
FIGURE 96.SOFTWARE AG: REVENUE SHARE, BY SEGMENT, 2019 (%)
FIGURE 97.SOFTWARE AG: REVENUE SHARE, BY REGION, 2019 (%)
The workers in the manufacturing and fabrication industries embrace changing technologies, such as workflow automation, particularly in post-pandemic, when automation has become a necessity rather than a desirable feature. IIoT predictive maintenance offers new insights to activate effective maintenance events, hence, its adoption is anticipated to be easier. Furthermore, increase in need to reduce equipment downtime and improve overall life of crucial industrial equipment are some of the major factors that drive the predictive maintenance market growth. Moreover, vibration monitoring, electrical testing, and oil analysis are expected to be the major segments, in terms of revenue in the predictive maintenance market. Furthermore, the manufacturing sector has been greatly impacted by COVID-19. As the industry strives to resurrect its operations in these troubling times, it must move to analytics-driven processes to streamline operations as efficiently as possible. Even after recent economic slowdowns, the manufacturing industry is anticipated to be a leading segment in the global predictive maintenance market in the coming years.
Even after the global economic downturn following the COVID-19 pandemic, major corporations are still trusting IoT based solutions to improve their productivity. According to a report published in the Guardian, 47% of companies are planning to increase their IoT expenditures in coming years. Further, the market comprises several international and regional players. The global players focus on increasing their presence in many regions. This increases competition, in terms of features, quality, and price for local vendors. Market players are adopting various business strategies to enhance their product offerings, business expansion, and increase their market penetration. For instance, the predictive maintenance market strengthened it base in the healthcare asset management market during the COVID-19 pandemic.
The US based solutions provider, Accurent, a PdM solutions provider, introduced a new predictive maintenance application for ventilators in hospitals for free of cost during the pandemic.
Moreover, in January 2019, Hitachi Ltd., announced that it will strengthen its wind power generator maintenance services and expand its core products of wind power generation solution business. The move is a part of Hitachi’s efforts to strengthen its renewable energy business, including collaborative and community-based creation-oriented energy projects including storage batteries, solar power, and other elements.
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