Seattle, WA -- (SBWIRE) -- 09/25/2019 -- Global predictive maintenance market is estimated to be valued at US$ 2,123.8 Mn in 2018, up from US$ 1,639.2 Mn in 2017. By 2026, the market is projected to reach US$ 17,700.8 Mn, exhibiting a CAGR of 30.3% over the forecast period (2018–2026). Growing adoption of predictive maintenance in automotive aftermarket coupled with increasing industrial automation and increasing demand for periodic maintenance are expected to drive growth of global predictive maintenance market during the forecast period.

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Manufacturing industries constantly require maintenance, in order to improve performance, reliability, and service management. In this, data-based models are used to improve performance of manufacturing process and to offer improved manufacturing quality. Hence, such benefits offered by predictive maintenance is expected to increase its adoption and thereby drive the market growth. Furthermore, automotive companies use predictive maintenance to collect and assess real-time data, which is used to gain sights into vehicle and its engine parts. For instance, in 2017, Mercedes Ben implemented predictive maintenance for real-time data extraction, which allowed the company obtain data from the vehicle when it is being used by the customer. It assists the company to predict any mechanical failure or incident regarding the vehicle.

The solution segment held dominant position in the market in 2018

In component type, solution segment held dominant position in the market in 2018. Moreover, it is expected to retain its dominance over the forecast period. Increasing industrial automation across various verticals such as defense and aerospace coupled with growing manufacturing sector are expected to drive growth of solution segment in global predictive maintenance market. Emerging Economies in Asia Pacific such as China and India are the major contributor to this growth. For instance, in 2018, according to India Brand Equity Foundation, the manufacturing sector in India exhibited a CAGR of 4.34 during FY12 and FY18 (as per the second advance estimates of annual national income published by the Government of India).

A basic predictive maintenance solution has a well -designed process model, which includes connected equipment, feature engineering, machine learning, implementation, and prediction. A smart maintenance predictive solution deals with capturing data and offers automated feature generation and optimized predictive model with real-time estimates and outcomes. Moreover, growth of smart maintenance predictive solutions segment is attributed to increasing number of connected assets throughout industrial applications. For instance, according to World Economic Forum, in 2018, less than 20% of assets were connected worldwide and the number is rapidly surging due to increasing automation across various industry verticals.

North America held dominant position in the predictive maintenance market in 2017

North America held dominant position in the market in 2017 and is expected to retain its dominance throughout the forecast period. This is owing to high presence of manufacturing companies and increasing demand for lean manufacturing across different industry verticals in the region. New startup companies deploy and adopt predictive maintenance to optimize the overall production process and make the operations cost-effective.
The U.S. accounted for the largest share in North America and the global predictive maintenance market in 2017, and is projected to retain its dominance during the forecast period. This is owing to increasing investment by major companies to increase profitability and to achieve cost optimization.
In North America predictive maintenance market, the manufacturing segment held dominant position, followed by aerospace & defense, and energy & utilities sector. Key players operating in the North America predictive maintenance market include, Robert Bosch, General Electric, and Rockwell Automation.

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Global Predictive Maintenance Market: Key Players

Major players operating in the global predictive maintenance industry include, Amiral Technologies, Embitel, General Electric, Honeywell International, Inc., IBM Corporation, Microsoft Corporation, Rockwell Automation, Inc., Senseye Ltd., Softweb Solutions, Inc., Warwick Analytics, SAP SE, Robert Bosch GmbH, Software AG, and Siemens AG.

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