Covid-19 Impact on Predictive Maintenance Market 2020 Industry Analysis, Growth Factors, Development Status, Competitive Landscape, Future Plans and Global Opportunities Explored 2024

Covid-19 Impact on Predictive Maintenance Market 2020 Industry Analysis, Growth Factors, Development Status, Competitive Landscape, Future Plans and Global Opportunities Explored 2024

Market Research Future
Market Research Future published a research report on “Covid-19 Impact on Predictive Maintenance Market Research Report- Global Forecast to 2024” – Market Analysis, Scope, Stake, Progress, Trends and Forecast to 2024.

Market Overview

The global preventive maintenance (PdM) market is expected to obtain a CAGR of 25.5% during the forecast period (2017-2024), estimates Market Research Future (MRFR). The market has the potential to touch a valuation of USD 23,051.4 million by 2024.

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Primary Drivers and Top Challenges

Predictive maintenance systems help collect information that is related to the equipment, and then helps processes it, and predicts the failure period. This process helps avoid equipment failure and consequent incidents, thus providing asset management. These advantages are boosting the demand for predictive maintenance systems across the globe, stimulating market growth.

The Predictive Maintenance Market requires the implementation of massive data, analytics and the internet of things. Most of the end-use industries like manufacturing, automotive, oil and gas, and others are concerned with issues like high maintenance cost as well as asset operation. Effective use of predictive maintenance solutions backed by IoT technologies assist these organizations in reducing the downtime and operations as well as maintenance cost.

Covid-19 Impact on Predictive Maintenance Market is progressing at a remarkable pace, on account of advancing the use of latest technologies to garner valuable insights, coupled with the rising need to bring down maintenance cost and downtime.

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.

Market Segmentation

The worldwide predictive maintenance (PdM) market can be segmented depending on component, testing type, deployment, technique and vertical.

Component-based segments in the market are hardware, solution, and services. The services segment can be split into consulting, support and maintenance, and system integration. Among the component types, the hardware segment controlled the largest portion of the market in 2018, while the services segment has the potential to achieve the highest CAGR during the review period.

Considering the testing type, the PdM market comprises electrical insulation, vibration monitoring, temperature monitoring, infrared thermography, oil analysis, and ultrasonic leak detector. The vibration monitoring segment had been identified as the largest market in 2018, with the oil analysis segment reckoned to record the fastest growth rate.

With regard to deployment, the PdM market covers cloud and on-premise. In 2018, the on-premise segment held the biggest share in the market, and the cloud segment is estimated to achieve a higher growth rate in the coming years.

With respect to the technique, the market can be segregated into traditional and advanced techniques. The advanced techniques types are IoT/Big Data technique and machine learning-based technique. The traditional techniques segment makes for the bigger market, as estimated in 2018. The advanced techniques segment is not far behind, as it is touted to garner the higher CAGR in the following years.

Vertical-wise segments in the market are healthcare, manufacturing, automotive, energy & utility, transportation, aerospace & defense, and others. Manufacturing was the biggest market in 2018, and energy & utility was identified as the fastest-growing segment.

Regional Outlook

The Middle East & Africa (MEA), Asia Pacific (APAC), North America, Europe, and South America are considered to be the primary markets for predictive maintenance.

North America is the most profitable market for predictive maintenance, backed by technological advancements across industries as well as surge in IoT connectivity. Rapid adoption of latest technologies, mostly machine learning has given a significant boost to the predictive maintenance market in the region. Some of the esteemed vendors in the region like Oracle Corporation, IBM Corporation, XMPro, Microsoft Corporation, and RapidMiner are working towards achieving a larger chunk of the market, by adopting effective marketing hacks and strategies. This factor is bound to work in favor of the regional market in the years ahead.

Europe is the second-leading market for predictive maintenance, as analyzed in 2018. The top contributing markets in the region are the United Kingdom (UK), France, Germany, Spain, Italy, and others. Germany is anticipated to seize the largest share in the regional market, with the UK, France, and Italy following suit in the near future. The market growth in the region is induced by the surge in IoT connectivity and considerable investment in predictive maintenance. The thriving automotive sector in the region also benefits the market.

The APAC market is flourishing as a result of sizeable investments by public and private sectors in enhancement of maintenance solutions, leading to strong demand for predictive maintenance solutions. In addition, growing acceptance of innovative solutions to achieve optimized output for maintenance of assets is also expected to stimulate growth of the predictive maintenance market in the region.

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1 Executive Summary

2 Market Introduction

2.1 Definition

2.2 Scope Of The Study

2.3 Market Structure

3 Research Methodology

3.1 Research Process

3.2 Primary Research

3.3 Secondary Research

3.4 Market Size Estimation

3.5 Forecast Model

3.6 List Of Assumptions


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