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Predictive Maintenance Market 2019 Global Analysis and Industry Expansion Strategies 2022

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Predictive Maintenance Market Overview

The increasing emphasis on operating efficiency of machines and engines is expected to increase the reliance on predictive maintenance. Market reports related to the information and communication industry have been presented by Market Research Future which prepares reports on other industry verticals that plan to research the current market scenarios better. The Global Preventive Maintenance (PdM) Market is expected to expand at 25.5% CAGR to reach 23,051.4 million in 2025 during the forecast period.

The need to maintain optimal efficiency in the operating condition of machines is expected to create new opportunities for the progress of the market in the forecast period. The popularity of efficiency and productivity tools that can reduce loss from damages or shorten downtimes is anticipated to inspire the development of the predictive maintenance market favorably. The rise in the adoption of big data and concepts like the Internet of Things (IoT) is expected to encourage the development of the predictive maintenance market.

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 segmentation analysis of the predictive maintenance market is carried out on the basis of component, technique, deployment, end-user, and region. On the basis of component, the predictive maintenance market is segmented into service and solution. Based on the technique, the predictive maintenance market is segmented into thermo-graphic inspection, vibration monitoring, and oil analysis. On the basis of deployment, the predictive maintenance market is segmented into on-premise and cloud. Based on end-users, the predictive maintenance market is segmented into aerospace & defense, manufacturing, automotive, transportation, healthcare, and government. The regions included in the predictive maintenance market are Asia Pacific, North America, Europe and the rest of the world.

Predictive Maintenance Global Market- Regional Analysis

The region wise analysis of predictive maintenance market encompasses regions such as Asia Pacific, North America, Europe and the rest of the world. The analysis of the market for predictive maintenance observes that the North American region would lead the market in the forecast period due to the incidence of a huge number of service and solution vendors. The study also finds that Asia Pacific nations such as Japan, China, South Korea, India, and others are greatly investing to amplify the effectiveness of the production assets. Moreover, the Asia Pacific region is projected to illustrate positive expansion in predictive maintenance market through the forecast period.

Industry Updates:

Feb 2019 Mann+Hummel have recently chosen Sierra Wireless’ Smart SIMs and AirVantage IoT Platform to join and handle global deployments of Senzit, the company’s latest predictive maintenance platform for agricultural and industrial fleets. Senzit makes use of IoT connectivity services from Sierra Wireless to provide fleet managers visibility of dust load, equipment location and engine hours. The real-time monitoring capability will enable fleet managers to schedule maintenance only when vehicles need it and also avoid downtime due to engine damage.

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

TABLE OF CONTENTS

1 Executive Summary

2 Market Introduction

2.1 Definition 18

2.2 Scope Of The Study 18

2.3 Market Structure 19

3 Research Methodology

3.1 Research Process 20

3.2 Primary Research 21

3.3 Secondary Research 22

3.4 Market Size Estimation 22

3.5 Forecast Model 23

3.6 List Of Assumptions 24

4 Market Insights

5 Market Dynamics

5.1 Introduction 27

5.2 Drivers 28

5.2.1 Increasing Demand For Real-Time Streaming Analytics 28

5.2.2 Growing Adoption Of Robots In The Manufacturing Sector 28

5.2.3 Advancement In Sensor Technology 28

5.2.4 Drivers Impact Analysis 29

5.3 Restraint 29

5.3.1 Interoperability Problems 29

5.4 Opportunity 29

Continued…

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