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Predictive Maintenance Market Ingights 2020: Key Growth Factors and Company Profiled Such as Microsoft Corporation, SparkCognition, SAP SE, General Electric,Asystom,Sigma Industrial Precision,Schneider Electric,Hitachi

04-08-2020 06:32 PM CET | IT, New Media & Software

Press release from: Allied Market Research

Predictive Maintenance Market Ingights 2020: Key Growth

The Objective of the "Global Predictive Maintenance Market" report is to depict the trends and upcoming for the Predictive Maintenance Market industry over the forecast years. Predictive Maintenance Market report data has been gathered from industry specialists/experts. Although the market size of the market is studied and predicted from 2020 to 2027 mulling over 2019 as the base year of the market study. Attentiveness for the market has increased in recent decades due to development and improvement in the innovation.

According to the report, the global predictive maintenance industry garnered $2.80 billion in 2018, and is estimated to reach $23.01 billion by 2026, growing at a CAGR of 30.2% from 2019-2026. The report also provides a detailed analysis of the drivers & opportunities, top investment pockets, top winning strategies, market size & estimations, competitive landscape, and wavering market trends.

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The need to improve uptime of equipment and increase in investment on predictive maintenance fuel the growth of the global predictive maintenance market. On the other hand, lack of skilled staff, difficulties in implementation, and data privacy & security concerns are some of the factors that restrain the growth to certain extent. However, integration of predictive maintenance with IIoT and use of machine learning are expected to create a number of lucrative opportunities in the near future.

Based on component, the solution segment contributed to nearly three-fourths of the global predictive maintenance market share in 2018 and is expected to rule the roost during the forecast period. The need to reduce unplanned downtime with optimized maintenance scheduling and failure prevention, make better business decisions to quickly respond for upsurge in demand and emergency situations, maximize throughput by identifying process bottlenecks, reduce defects, and improve product quality with accurate predictive quality and optimized machine performance drive the growth of global predictive maintenance solution market. The service segment, on the other hand, would grow at the fastest CAGR of 32.9% throughout the study period. Rise in need to train the staffs, and effective utilization of predictive maintenance technology are expected to drive the growth of the segment.

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Based on deployment, the on-premise segment accounted for nearly three-fifths of the global predictive maintenance market revenue in 2018 and is anticipated to dominate till 2026. To avoid cyber-threats, companies tend to prefer on-premise predictive maintenance solution which, in turn, drives the growth of this segment. At the same time, the cloud segment would showcase the fastest CAGR of 32.20% by 2026. Direct IT control, internal data delivery & handling, faster data processing, efficient resource utilization, and cost-effectiveness of cloud deployment are some of the advantages offered by this model, which are projected to propel the growth.

Based on geography, North America held the major share in 2018, generating more than one-third of the global predictive maintenance market. It is due to the presence of a large number of solution and service vendors in this region. Furthermore, great awareness regarding predictive maintenance measures, its importance and early adoption of technology in this region have also spurred the demand for predictive maintenance in this region. Simultaneously, the Asia-Pacific region would cite the fastest CAGR of 31.90% during the forecast period. Surge in focus on trying innovative solution for achieving optimized output for maintenance of assets is expected to fuel the growth of predictive maintenance market in the region.

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Frontrunners in the industry

Microsoft Corporation
SparkCognition
SAP SE
General Electric
Asystom
Sigma Industrial Precision
Schneider Electric
Hitachi, Ltd.
PTC Inc.
TIBCO Software Inc.
SAS Institute Inc.
Operational Excellence (Opex) Group Ltd.
Engineering Consultants Group, Inc.
IBM Corporation
Expert Microsystems, Inc.
C3.ai, Inc.
Software AG
Uptake Technologies Inc.
Fiix Inc.

Key questions answered in Predictive Maintenance Market research study:

o What is the market growth rate of Predictive Maintenance Market from 2020-2027?
o What will be the global market size of the market from 2020 to 2027?
o Who are the leading global players in the Predictive Maintenance Market?
o What are the current trends and predicted trends?
o What are the challenges faced in the Predictive Maintenance Market?
o Which will be the niches at which players profiling with thorough plans, financials, and also recent advancements should set a presence?
o Which will be the anticipated growth rates for your own Predictive Maintenance Market economy altogether and also for every segment inside?
o Which will be the Predictive Maintenance Market application and types and forecast accompanied closely by producers?
o What are the conclusions of the Predictive Maintenance Market report?

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About Us:

Allied Market Research (AMR) is a full-service market research and business-consulting wing of Allied Analytics LLP based in Portland, Oregon. Allied Market Research provides global enterprises as well as medium and small businesses with unmatched quality of "Market Research Reports" and "Business Intelligence Solutions." AMR has a targeted view to provide business insights and consulting to assist its clients to make strategic business decisions and achieve sustainable growth in their respective market domain.

We are in professional corporate relations with various companies and this helps us in digging out market data that helps us generate accurate research data tables and confirms utmost accuracy in our market forecasting. Each and every data presented in the reports published by us is extracted through primary interviews with top officials from leading companies of domain concerned. Our secondary data procurement methodology includes deep online and offline research and discussion with knowledgeable professionals and analysts in the industry.

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