Industrial Predictive Maintenance Market Size, Status and Forecast 2025

This report studies the global Industrial Predictive Maintenance market size, industry status and forecast, competition landscape and growth opportunity. This research report categorizes the global Industrial Predictive Maintenance market by companies, region, type and end-use industry.

Predictive maintenance (PdM) techniques are designed to help determine the condition of in-service equipment in order to predict when maintenance should be performed. This approach promises cost savings over routine or time-based preventive maintenance, because tasks are performed only when warranted. The main promise of predictive maintenance is to allow convenient scheduling of corrective maintenance, and to prevent unexpected equipment failures.

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Predictive maintenance evaluates the condition of equipment by performing periodic (offline) or continuous (online) equipment condition monitoring. The ultimate goal of the approach is to perform maintenance at a scheduled point in time when the maintenance activity is most cost-effective and before the equipment loses performance within a threshold. This results in a reduction in unplanned downtime costs because of failure where for instance costs can be in the hundreds of thousands per day depending on industry.

In 2017, the global Industrial Predictive Maintenance market size was xx million US$ and it is expected to reach xx million US$ by the end of 2025, with a CAGR of xx% during 2018-2025.

This report focuses on the global top players, covered

Augury Systems
Bosch Software Innovations
C3 IoT
Dell Technologies
Fluke Corporation
General Electric
Hitachi
Honeywell
IBM
PTC
Rapidminer
Rockwell Automation
SAP
SAS Institute
Schneider Electric
Senseye
SKF
Software
Softweb Solutions
T-Systems International
Warwick Analytics
Market segment by Regions/Countries, this report covers

United States
Europe
China
Japan
Southeast Asia
India
Market segment by Type, the product can be split into

Cloud-based
On-premises based
Market segment by Application, split into

Government
Aerospace and defense
Energy and utilities
Healthcare
Manufacturing
Transportation and logistics
The study objectives of this report are:

To study and forecast the market size of Industrial Predictive Maintenance in global market.
To analyze the global key players, SWOT analysis, value and global market share for top players.
To define, describe and forecast the market by type, end use and region.
To analyze and compare the market status and forecast between China and major regions, namely, United States, Europe, China, Japan, Southeast Asia, India and Rest of World.
To analyze the global key regions market potential and advantage, opportunity and challenge, restraints and risks.
To identify significant trends and factors driving or inhibiting the market growth.
To analyze the opportunities in the market for stakeholders by identifying the high growth segments.
To strategically analyze each submarket with respect to individual growth trend and their contribution to the market
To analyze competitive developments such as expansions, agreements, new product launches, and acquisitions in the market
To strategically profile the key players and comprehensively analyze their growth strategies.
In this study, the years considered to estimate the market size of Industrial Predictive Maintenance are as follows:

History Year: 2013-2017
Base Year: 2017
Estimated Year: 2018
Forecast Year 2018 to 2025
Key Stakeholders

Industrial Predictive Maintenance Manufacturers
Industrial Predictive Maintenance Distributors/Traders/Wholesalers
Industrial Predictive Maintenance Subcomponent Manufacturers
Industry Association
Downstream Vendors
Available Customizations

With the given market data, We offers customizations according to the company's specific needs. The following customization options are available for the report:

Regional and country-level analysis of the Industrial Predictive Maintenance market, by end-use.

Detailed analysis and profiles of additional market players.

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