Predictive Maintenance Market Forecast 2025 With Bosch Software Innovations, RapidMiner, Dell, IBM, Hitachi, SAS, SAP, Rockwell Automation, PTC, Augury, Schneider Electric, GE, Software AG, T-Systems International GmbH, Fluke Corporation, C3 IoT, Softweb

The report appreciates the key factors influencing market growth (drivers, constraints, opportunities and challenges) derived from the Porter Five Forces tool and the SWOT analysis. The report tactically analyzes the predictive maintenance market in terms of individual growth trends, prospects and market contributions. The aim of this predictive maintenance report is to define, describe and forecast the global predictive maintenance market based on types of applications, major sectors, deployment models, organizational size and regions.

It comprises the predictive maintenance company profiles of the key supplier and thoroughly analyzes its core competences. The report also tracks and dissects competitive developments, including partnerships, acquisitions, product and market research developments and various other development activities.

The predictive maintenance market will continue to increase in the forecast years 2018-2025 and how it will be actively supported by the predictive maintenance industry.

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The predictive maintenance industry accounted to USD XX.XX million in 2017 growing at a CAGR of XX.XX% during the forecast period of 2018 to 2025, Globally. Predictive maintenance market report contains data for historic years 2016, the base year of calculation is 2017 and the forecast period is 2018 to 2025.

Major Market Drivers & Restraints:

· Reduction in Operation & Maintenance Costs and Asset Downtime

· Increasing Demand for Transforming Maintenance

· Helps in Decision-Making and Increasing Operational Efficiency

· Big Data and IoT Driving the Market

· Lack of Training

· Lack of Trust in Predictive Maintenance Technologies


Market Segmentation

· The global predictive maintenance market is segmented on the basis of component into solutions, and services. The services segment is further sub segmented into

· System integration

· Maintenance and support

· Consulting services

· On the basis of organization size, the global predictive maintenance market is segmented into

· Large enterprises

· Small and medium-sized enterprises

· On the basis of deployment type, the global predictive maintenance market is segmented into

· Cloud

· On-Premises

· On the basis of vertical, the global predictive maintenance market is segmented into

· Government

· Aerospace And Defense

· Energy And Utilities

· Manufacturing

· Healthcare

· Transportation And Logistics

· Others

· On the basis of geography, the global Predictive Maintenance market report covers data points for 28 countries across multiple geographies such as North America, South America, Europe, Asia-Pacific, and Middle East & Africa.

· Some of the major countries covered in this report are U.S., Canada, Germany, France, U.K., Netherlands, Switzerland, Turkey, Russia, China, India, South Korea, Japan, Australia, Singapore, Saudi Arabia, South Africa, and Brazil among others.

· North America is expected to dominate the market.

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The aim of predictive maintenance is to first predict when equipment failure might occur, then to take preventive actions by performing maintenance. It involves testing and monitoring machines to predict machine failures. This helps in maximizing device or equipment uptime, enhancing quality. It is widely applicable in government, aerospace and defense, energy and utilities, manufacturing, healthcare, transportation and logistics, and others. Some of the major players of the global predictive maintenance market are

· T-Systems International GmbH

· Augury

· Bosch Software Innovations

· C3 IoT

· Dell Inc.

· Fluke Corporation

· General Electric

· Hitachi, Ltd.

· Honeywell International Inc.

· IBM Corporation

· PTC

· RapidMiner

Others: Rockwell Automation, Inc., SAP SE, SAS Institute, Inc., Schneider Electric, Senseye Ltd, SKF, Software AG, Softweb Solutions Inc, Warwick Analytics and others. Reduction in operation and maintenance costs may act as major driver in the growth of predictive maintenance market. On the other side, lack of proper training about the technology may hamper the market.


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