Predictive Maintenance (PdM) Market 2020 Size,Share Global Growth Analysis, Trends, Industry Analysis, Key Players and Forecast to 2024

Predictive Maintenance (PdM) Market Players influencing the market are profiled in the study along with their SWOT analysis and market strategies. The report also focuses on leading industry players with information such as company profiles, products and services offered financial information. Furthermore, the report also caters the detailed information about the crucial aspects such as drivers and restraining factors which will define the future growth of the Predictive Maintenance (PdM) market.

This Global Predictive Maintenance (PdM) Market report presents a comprehensive overview, market shares, and growth opportunities of Predictive Maintenance (PdM) market by product type, application, key manufacturers and key regions and countries. Ongoing research and development in the field of Predictive Maintenance (PdM) market is expected to assist the overall market growth in the near future from 2020 to 2024.

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Global Predictive Maintenance (PdM) Market Research Report: by Component (Hardware, Solution, Services (System Integration Services, Support and Maintenance Services, Consulting Services), Testing Type (Vibration Monitoring, Electrical Insulation, Infrared Thermography, Temperature Monitoring, Ultrasonic Leak Detector, Oil Analysis), Deployment Mode (Cloud, On-premise), Technique (Traditional Technique, Advanced Technique (IoT/Big Data Technique, Machine Learning Technique), by Vertical (Manufacturing, Energy and Utilities, Healthcare, Automotive, Aerospace and Defense, Transportation) and by Region (North America (US, Canada, Mexico), Europe (Germany, UK, France, Italy, Spain, Rest of Europe), Asia-Pacific (China, Japan, South Korea, Rest of Asia-Pacific), Middle East and Africa and South America) – Forecast till 2024

Market analysis

Generally, most of the nation’s implement analytical upkeep for situation-checking to gauge an asset’s performance in real time. Nevertheless, advanced methods are significantly used in developed economies such as the US, few states in Western European, and few established economies of Asia-Pacific and the Middle East region. The key element of an advanced process is the Internet of Things (IoT) technology that allows different assets and systems to connect, work cooperatively, share, analyze, and act on the data. IoT relies on predictive protection sensors to capture information, analyze it, and identify any areas that need immediate attention. In October 2018, Hitachi, Ltd launched an AI-Assisted predictive maintenance service for petrochemical plants to detect real-time operational conditions. This helps petrochemical plants to increase their operational efficiency and maintenance tasks. Predictive maintenance (PdM) is a maintenance strategy driven by predictive analytics technology. The solutions are installed to monitor and detect failures or anomalies in equipment but are engaged only upon the possibility of critical failure. This helps in deploying limited resources, increasing device or apparatus uptime, enhancing quality and supply chain processes, and improving the overall satisfaction for all the stakeholders involved. Equipment is monitored using traditional and advanced techniques which allow maintenance of the apparatus to be planned before a failure occurs. Both these techniques are outfitted with various testing or monitoring tools for vibration monitoring, electrical protection, ultraviolet thermography, temperature monitoring, ultrasonic leak detection, and oil evaluation.

Market segmentation

The predictive maintenance (PdM) market is segmented based element, testing type, deployment, technique, vertical, and region respectively. By testing type, the PdM market has been segmented into juddering observing, electrical protection, infrared thermography, temperature monitoring, ultrasonic leak detector, oil analysis. The vibration monitoring segment accounted for the leading market share in 2018, whereas the oil analysis is expected to register the highest CAGR. By technique, the market has been classified as traditional and pioneering techniques. The advanced techniques sector has been further bifurcated into the IoT/Big Data technique, and machine learning-based technique. The traditional techniques segment settled for the larger market share in 2018, whereas the advanced techniques segment is expected to register the higher CAGR. By technique, the market has been grouped as traditional and advanced methods. The enhanced techniques segment has been further branched into the IoT/Big Data technique, and machine learning-based technique. The traditional techniques segment accounted for the larger market share in 2018, although the advanced techniques segment is expected to register the higher CAGR. By testing type, the PdM market has been segmented into vibration monitoring, electrical insulation, infrared thermography, temperature monitoring, ultrasonic leak detector, oil analysis. The vibration monitoring segment accounted for the largest market share in 2018, whereas the oil analysis is expected to reach the maximum CAGR.

In March 2019, IBM launched a new collection of IIOT (industrial internet of things) solutions for predictive maintenance that uses advanced analytics and artificial intelligence technologies. The solution will minimize the risk of failure associated with physical assets including manufacturing robots, vehicles, turbines, electrical transformers, elevators, and mining apparatus. The increasing adoption of real-time streaming analytics technology is one of the driving factors for the growth of the predictive maintenance market. It requires critical computations of real-time data streamed from applications, sensors, devices, and others. It provides quick and suitable time-sensitive information and language incorporation for specialized applications. Streaming analytics is one of the pillars of predictive maintenance as it provides real-time data to automatic supervising systems to maintain asset health or to personnel to perform maintenance operations when required. By implementation, the PdM market has been segmented into cloud and on-premise. The on-premise segment settled for the larger market share in 2018, whereas the cloud segment is expected to register the higher CAGR. By vertical, the market has been segmented into manufacturing, healthcare, energy and utility, automotive, aerospace and defense, transportation, and others. The manufacturing division settled for the greatest market share in 2018, whereas the energy and efficiency segment is likely to list the highest CAGR.

Regional analysis

Geographically the predictive maintenance (PdM) market is split in regions like North and South America, Europe, Asia-Pacific, Middle east and Africa and Rest of the world. Europe held the second-largest share in the preventive maintenance market in 2018. Europe has been divided into the UK, Germany, France, Italy, Spain, and the rest of Europe. Corresponding to the analysis, Germany is supposed to gain the greatest market share followed by the UK, France, and Italy. Some of the factors responsible for the market expansion include growth of IoT connectivity, increasing investment in predictive maintenance, and growth in the automotive sector during the forecast period. The presence of companies such as Robert Bosch GmbH, Schneider Electric SA, and SAP SE is pushing development of proactive maintenance emulsions in the region. North America settled for the major market in the predictive preservation market. Advances in technology across industries, expansion of IoT connectivity, and fast adoption of advanced technologies, particularly machine learning, are some of the factors responsible for the growth of the predictive maintenance market in the region. The leading players in the region involve IBM Corporation, Oracle Corporation, Microsoft Corporation, XMPro, and RapidMiner that manage throughout the region.

Major players

The proposed spectators in the predictive maintenance (PdM) market are manufacturers, Retailers, distributors, wholesalers, Investors and trade experts, Governments, associations, industrial bodies, etc. The major companies functioning in the predictive maintenance (PdM) market are concentrating on firming their global ways by entering into untouched markets. The projected onlookers in the predictive maintenance (PdM) market are companies like IBM Corporation (US), Axiomtek Co. Ltd (Taiwan), Oracle Corporation (US), Microsoft Corporation (US), XMPro (US), Hitachi, Ltd (Japan), SAP SE (Germany), Comtrade (Ireland), C3 IoT (US), Software AG (Germany) and RapidMiner (US).

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Strategic Recommendations Forecast Growth Areas of the Predictive Maintenance (PdM) Market.

–Emerging opportunities, competitive landscape, the revenue shares of main manufacturers.

-This report discusses the Market summary; Market scope gives a brief outline of the Market

-Key performing regions (APAC, EMEA, Americas) along with their major countries are detailed in this report.

-Company profiles, product analysis, Marketing strategies, emerging Market segments and comprehensive analysis of Market

-Challenges for the new entrants, trends Market drivers.

-The market share year-over-year growth of key players in promising regions.

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This report studies the global market size of Predictive Maintenance (PdM) in key regions like North America, Europe, Asia Pacific, Central and South America and Middle East and Africa, focuses on the consumption of Predictive Maintenance (PdM) in these regions. This research report categorizes the global Predictive Maintenance (PdM) market by top players/brands, region, type and end user. This report also studies the global Predictive Maintenance (PdM) market status, competition landscape, market share, growth rate, future trends, market drivers, opportunities and challenges, sales channels and distributors.

Lastly, this report covers the market landscape and its growth prospects over the coming years, the Report also brief deals with the product life cycle, comparing it to the relevant products from across industries that had already been commercialized details the potential for various applications, discussing about recent product innovations and gives an overview on potential regional market shares.

Total Chapters in Predictive Maintenance (PdM) Market Report are:

Chapter 1 Overview of Predictive Maintenance (PdM) Market

Chapter 2 Global Market Status and Forecast by Regions

Chapter 3 Global Market Status and Forecast by Types

Chapter 4 Global Market Status and Forecast by Downstream Industry

Chapter 5 North America Market Status by Countries, Type, Manufacturers and Downstream Industry

Chapter 6 Europe Market Status by Countries, Type, Manufacturers and Downstream Industry

Chapter 7 Asia Pacific Market Status by Countries, Type, Manufacturers and Downstream Industry

Chapter 8 Latin America Market Status by Countries, Type, Manufacturers and Downstream Industry

Chapter 9 Middle East and Africa Market Status by Countries, Type, Manufacturers and Downstream Industry

Chapter 10 Market Driving Factor Analysis of Low End Servers

Chapter 11 Predictive Maintenance (PdM) Market Competition Status by Major Manufacturers

Chapter 12 Predictive Maintenance (PdM) Major Manufacturers Introduction and Market Data

Chapter 13 Upstream and Downstream Market Analysis of Predictive Maintenance (PdM) Market

Chapter 14 Cost and Gross Margin Analysis of Predictive Maintenance (PdM) Market

And Continued…

Some of Major Points From Toc :

Table of Contents:

1Executive Summary
2Market Introduction
2.1Definition
2.2Scope of the Study
2.3Market Structure
3Research Methodology
3.1Research Process
3.2Primary Research
3.3Secondary Research
3.4Market Size Estimation
3.5Forecast Model
3.6List of Assumptions
4Market Insights
5Market Dynamics
5.1Introduction
5.2Drivers
5.2.1Increasing Demand for Real-Time Streaming Analytics
5.2.2Growing adoption of robots in the manufacturing sector
5.2.3Advancement in Sensor Technology
5.2.4Drivers Impact Analysis
5.3Restraint
5.3.1Interoperability problems
5.4Opportunity
5.4.1Increasing Trend of Connected Devices
5.5Challenge
5.5.1Lack of Expertise
6Market Factor Analysis
6.1Value Chain Analysis
6.1.1Software Providers
6.1.2Solution providers
6.1.3System Integrators
6.1.4End Users
6.2Porter’s Five Forces Model
6.2.1Threat of New Entrants
6.2.2Bargaining Power of Suppliers
6.2.3Threat of Substitutes
6.2.4Bargaining Power of Buyers
6.2.5Competitive Rivalry
6.3Industry Insights and Technological Impact Analysis
6.3.1Selection Parameters for Predictive maintenance and Predictive Analytics
6.3.2Use Cases
6.3.2.1Industry 4.0
6.3.2.2Connected Cars
7Global Predictive Maintenance (PdM) Market, by Component
7.1Overview
7.2Hardware
7.3Solution
7.4Services
7.4.1System Integration Services
7.4.2Support and Maintenance Services
7.4.3Consulting Services
8Global Predictive Maintenance (PdM) Market, By Testing Type
8.1Overview
8.2Vibration Monitoring
8.3Electrical Insulation
8.4Infrared Thermography
8.5Temperature Monitoring
8.6Ultrasonic Leak Detector
8.7Oil Analysis
9Global Predictive Maintenance (PdM) Market, By Deployment Mode
9.1Overview
9.2Cloud
9.3On-Premise
10Global Predictive Maintenance (PdM) Market, by Technique
10.1Overview
10.2Traditional Technique
10.3Advanced Technique
10.3.1IoT/Big Data Technique
10.3.2Machine Learning Technique
11Global Predictive Maintenance (PdM) Market, By Vertical
11.1Overview
11.2Manufacturing
11.3Energy and Utilities
11.4Healthcare
11.5Automotive
11.6Aerospace and Defense
11.7Transportation
11.8Others
12Global Predictive Maintenance (PdM) Market, by Region
12.1Overview
12.2North America
12.2.1US
12.2.2Canada
12.2.3Mexico
12.3Europe
12.3.1Germany
12.3.2UK
12.3.3France
12.3.4Italy
12.3.5Spain
12.3.6Rest of Europe
12.4Asia-Pacific
12.4.1China
12.4.2Japan
12.4.3Singapore
12.4.4South Korea
12.4.5Rest of Asia-Pacific
12.5Middle East and Africa
12.6South America
13Competitive Landscape
13.1Competitive Overview
13.2Market Share Analysis 2018 (%)
13.3Competitive Benchmarking
14Company Profiles
14.1IBM Corporation
14.1.1Company Overview
14.1.2Financial Overview
14.1.3Products/Solutions/Services/Software Offered
14.1.4Key Developments
14.1.5SWOT Analysis
14.1.6Key Strategies
14.2SAP SE
14.2.1Company Overview
14.2.2Financial Overview
14.2.3Products/Services/Solutions Offered
14.2.4Key Developments
14.2.5SWOT Analysis
14.2.6Key Strategies
14.3Software AG
14.3.1Company Overview
14.3.2Financial Overview
14.3.3Products/Services/Solutions Offered
14.3.4Key Developments
14.3.5SWOT Analysis
14.3.6Key Strategies
14.4Hitachi, Ltd
14.4.1Company Overview
14.4.2Financial Overview
14.4.3Products/Services/Solutions Offered
14.4.4Key Developments
14.4.5SWOT Analysis
14.4.6Key Strategies
14.5Oracle Corporation
14.5.1Company Overview
14.5.2Financial Overview
14.5.3Product/Service/Solutions Offered
14.5.4Key Developments
14.5.5SWOT Analysis
14.5.6Key Strategies
14.6Microsoft Corporation
14.6.1Company Overview
14.6.2Financial Overview
14.6.3Product/Service/Solutions Offered
14.6.4Key Developments
14.6.5SWOT Analysis
14.6.6Key Strategies
14.7Axiomtek Co, Ltd
14.7.1Company Overview
14.7.2Financial Overview
14.7.3Products/Services/Solutions Offered
14.7.4SWOT Analysis
14.7.5Key Developments
14.7.6Key Strategies
14.8XMPro
14.8.1Company Overview
14.8.2Financial Overview
14.8.3Product/Service/Solutions Offered
14.8.4Key Developments
14.8.5Key Strategies
14.9RapidMiner
14.9.1Company Overview
14.9.2Financial Overview
14.9.3Product/Service/Solutions Offered
14.9.4Key Developments
14.9.5Key Strategies
14.1Comtrade
14.10.1Company Overview
14.10.2Financial Overview
14.10.3Products/Services/Solutions Offered
14.10.4Key Developments
14.10.5Key Strategies
14.11C3 IoT
14.11.1Company Overview
14.11.2Financial Overview
14.11.3Products/Services/Solutions Offered
14.11.4Key Developments
14.11.5Key Strategies

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