ReleaseWire

Market Report, "Operational Predictive Maintenance Market - Global Forecast to 2020", Published

Fast Market Research announces the availability of the new Markets and Markets report, "Operational Predictive Maintenance Market - Global Forecast to 2020", on their comprehensive research portal

Posted: Wednesday, March 23, 2016 at 8:20 AM CDT

Boston, MA -- (SBWire) -- 03/23/2016 --Operational Predictive Maintenance Market by Solution, by Service (System Integration, Training and Support, Consulting, by Deployment Type (Cloud, on-Premise), by Application Area, by Region (NA, Europe, APAC, MEA, LA) - Global Forecast to 2020

"Rise in demand for reducing asset downtime has fueled the growth of the operational predictive maintenance market"

The operational predictive maintenace market size is expected to grow from USD 582.3 million in 2015 to USD 1,884.3 million by 2020, at a Compound Annual Growth Rate (CAGR) of 26.5%. The need to lower maintenance costs with reduced down time and Internet of Things (IoT) is expected to increase the demand for operational predictive maintenance solutions and services.

Get More Details on this Report and a Full Table of Contents at Operational Predictive Maintenance Market - Global Forecast to 2020

"Training and support services segment to grow at the highest CAGR during the forecast period"

The training and support services segment is estimated to grow at the highest CAGR duing the forecast period. The rise in the demand for training and support services is expected to witness traction in the APAC, MEA, and Latin America regions, as the predictive maintenance software solutions are dependent on the combination of technology and human skill. The software vendors provide training courses for the employees that last a few days and are basic in nature; but additional educational is required so that operators can understand and interpret the analysis from the captured data.

"North America to be the largest market for operational predictive maintenance during the forecast period"

The North American region holds the largest share of the operational predictive maintenance market. The major driver for this region is the increasing demand for a better monitoring and predictive technology. The U.S. has the largest market share in the region, followed by Canada. The European market is the second largest market after North America. The region consists of major growing economies such as the U.K., Germany, and France, which present great growth opportunities for the operational predictive maintenance market.

In the process of determining and verifying the market size for several segments and subsegments gathered through secondary research, extensive primary interviews were conducted with key people. Break-up of profile of primary participants is as follows:

-By Company Type: Tier 1 - 55 %, Tier 2 - 20% and Tier 3 - 25%
-By Designation: C level - 60%, Director level - 25%, Others - 15%
-By Region: North America - 10%, Europe - 20%, APAC - 40%, RoW - 30%

The various key operational predictive maintenance vendors profiled in the report are as follows:

1. IBM Corporation
2. Software AG
3. SAS Institute, Inc.
4. General Electric
5. Bosch
6. Rockwell Automation, Inc.
7. PTC
8. Schneider Electric
9. SKF
10. Emaint Enterprises, LLC

The report will help the market leaders/new entrants in this market in the following ways:

1. This report segments the operational predictive maintenance market comprehensively and provides the closest approximations of the revenue numbers for the overall market and the sub-segments across different application area and regions.
2. The report helps stakeholders to understand the pulse of the market and provides them information on key market drivers, restraints, challenges, and opportunities.
3. This report will help the stakeholders to better understand the competitors and gain more insights to better their positions in the business. The competitive landscape section includes competitor ecosystem, new product develpoments, partnerships, and mergers and acquisitions.

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