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Predictive Maintenance Market Synopsis and Highlights, Key Findings, Major Companies Analysis and Forecast to 2022

11-16-2017 06:43 PM CET | IT, New Media & Software

Press release from: Market Research (MRFR) Future Reports

Predictive Maintenance Market Synopsis and Highlights, Key

Market Scenario:
Predictive maintenance is regular monitoring of the actual mechanical condition, operating efficiency, and other indicators of the operating condition of machines and process systems will provide the data required to ensure the maximum interval between repairs and minimize the number and cost of unscheduled outages created by the failures. Predictive maintenance actually means to improve productivity, product quality, and overall effectiveness of manufacturing and production plants. Predictive maintenance is a condition-driven preventive maintenance program. Predictive maintenance uses direct monitoring of the mechanical condition, system efficiency, and other indicators to determine the actual mean-time-to-failure or the loss of efficiency for each machine and system in the plant. The main reasons for implementing predictive maintenance would be it can be used as- a maintenance tool, a plant optimizing tool and a reliability improvement tool.
Predictive maintenance major benefits are, it reduces time required for maintenance and reduces the costs of maintenance. Recently there has been a rise in demand for transforming maintenance and reducing asset downtime, these are the key market drivers for predictive maintenance market. The rising dependence on big data and emerging concepts such as the Internet of Things (IoT) and the rising focus of organizations on reducing the operational cost is further expected to influence the growth of predictive maintenance market during the forecast period. The study indicates that lack of training for operators and lack of trust in predictive maintenance technology is a major threat for the predictive maintenance market.
Predictive maintenance has the ability to specifically predict asset failure, enabling enterprises to take the asset out of production just before it is to fail, thus it ensures that the production is not hampered in any way due to the failure of the asset. This ability of predictive maintenance is the major driving force for the predictive maintenance market.
The global Predictive Maintenance market is expected to grow at USD ~6334 Million by 2022, at 27% of CAGR between 2016 and 2022.
Study Objectives of Predictive Maintenance Market:
• To provide detailed analysis of the market structure along with forecast of the various segments and sub-segments of the Predictive Maintenance market.
• To provide insights about factors affecting the market growth.
• To analyze the Predictive Maintenance market based porter’s five force analysis etc.
• To provide historical and forecast revenue of the market segments and sub-segments with respect to four main geographies and their countries- North America, Europe, Asia, and Rest of the World (ROW).
• To provide country level analysis of the market with respect to the current market size and future prospective.
• To provide country level analysis of the market for segment on the basis component, technique, deployment and end-user.
• To provide strategic profiling of key players in the market, comprehensively analyzing their core competencies, and drawing a competitive landscape for the market.
• To track and analyze competitive developments such as joint ventures, strategic alliances, mergers and acquisitions, new product developments, and research and developments in the Predictive Maintenance

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Key Players:
The prominent players in the Predictive Maintenance Market are – IBM (U.S.), SAP SE (Germany), Software AG (Germany), General Electric (U.S.), Robert Bosch (Germany), Rockwell Automation (U.S.), PTC (U.S.), Warwick Analytics (U.K.), RapidMiner (U.S.), Schneider Electric SE (France), eMaint Enterprises, LLC (U.S.) and SKF (Sweden) among others

Segments:

Predictive Maintenance by Component:
By Solution
by Service

• Support and Maintenance
• System integration
• Consulting
Predictive Maintenance by Techniques:
• Vibration monitoring
• Oil analysis
• Visual inspection
• Shock pulse
• Ultrasonic leak detectors
• Electrical insulation
• Performance testing
• Wear and dimensional measurements
• Signature analysis, time and frequency domain
• Nondestructive testing
Predictive Maintenance by Deployment Type:
• Cloud
• On premise
Predictive Maintenance by End-user:
• Manufacturing
• Aerospace & defense
• Healthcare
• Automotive
• Transportation
• Government

Regional Analysis:
The regional analysis of Predictive Maintenance market is being studied for region such as Asia pacific, North America, Europe and Rest of the World. The study indicates that North America region would dominate the Predictive Maintenance market by the forecast period owing to the presence of a large number of solution and service vendors. The study indicates that Asia-Pacific countries like China, Japan, South Korea, India and others are highly investing to increase the efficiency of production assets. The study reveals that Asia-Pacific region would show a positive growth in predictive maintenance market by the forecast period.
Intended Audience
• Predictive maintenance vendors
• Resellers and distributors
• Technology investors
• System Integrators
• Government Organizations
• Research/Consultancy firms

Browse Report @ https://www.marketresearchfuture.com/reports/predictive-maintenance-market-2377

At Market Research Future (MRFR), we enable our customers to unravel the complexity of various industries through our Cooked Research Report (CRR), Half-Cooked Research Reports (HCRR), Raw Research Reports (3R), Continuous-Feed Research (CFR), and Market Research & Consulting Services.

MRFR team have supreme objective to provide the optimum quality market research and intelligence services to our clients. Our market research studies by Components, Application, Logistics and market players for global, regional, and country level market segments, enable our clients to see more, know more, and do more, which help to answer all their most important questions.

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