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.
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.
The 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.
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Latest Developments
October 2019
SKF Group (Stockholm) is in the process of acquiring Haifa-based predictive maintenance company Presenso Ltd. this year. Presenso’s employees are expected to be integrated into SKF, following the acquisition.
Key Players
The prominent players in the Predictive Maintenance (PdM) Industry 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 (PdM) Industry 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.
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TABLE OF CONTENTS
List of Figures
Figure 1 Market Synopsis 17
Figure 2 Global Predictive Maintenance (Pdm) Market: Market Structure 19
Figure 3 Research Process Of Mrfr 20
Figure 4 Top Down & Bottom Up Approach 23
Figure 5 Global Market Size & Market Share By Region (2018 Vs 2024) 25
Figure 6 North America Market Size & Market Share By Country (2018 Vs 2024) 25
Figure 7 Asia-Pacific Market Size & Market Share By Country (2018 Vs 2024) 26
Figure 8 Europe Market Size & Market Share By Country (2018 Vs 2024) 26
Figure 9 Dro Analysis Of Global Predictive Maintenance (Pdm) Market 27
Figure 10 Drivers Impact Analysis: Predictive Maintenance Market 29
Figure 11 Value Chain: Global Predictive Maintenance (Pdm) Market 30
Continued…
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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.
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Market ScenarioAs per the predictions by Market Research Future (MRFR), the The Global Predictive Maintenance (PDM) Market is expected to expand at 25.5% CAGR to reach 23,051.4 million in 2025 during the forecast period.Market Drivers and Growth RestraintsThe major benefits of predictive maintenance include its ability to reduce the required for maintenance as well as decreasing the cost of maintenance.
Backed by the recent surge in demand for the transformation of maintenance and the need to reduce the asset downtime, Predictive Maintenance (PDM) Market is set to ride high on the back of these factors in the coming years.Furthermore, the growing dependence on big data along with the emergence of concepts like the Internet of Things (IoT) and the increasing focus of organizations on the reduction of operational cost will further accentuate the lucrative market shape during the forecast period.
However, the report also takes note of the lack of training for operators as a factor that could prove to be a major threat to the Predictive Maintenance (PDM) Market.But, given the ability of predictive maintenance to specifically predict asset failure that allows enterprises to take the asset out of production before its failure takes place, the production does not get affected in any way.
This particular ability of predictive maintenance will make sure that the market not only remain unaffected by the mentioned threat, but also soars higher than its present position in the near future.Get More Details of Report @ https://www.abnewswire.com/pressreleases/covid19-impact-on-predictive-maintenance-market-2020-industry-analysis-growth-factors-development-status-competitive-landscape-future-plans-and-global-opportunities-explored-2024_488128.htmlKey PlayersThe prominent players in the Predictive Maintenance (PdM) Industry 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 SegmentationThe 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.
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 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.
Product Data Management (PDM) Software Market:WiseGuyReports.com adds “Global Product Data Management (PDM) Software Market Research Report 2020 Analysis and Forecast 2026” reports to its database.Executive SummaryThe report lays out a detailed form of database with regard to the recent discoveries and the key technological advancements in the industry, along with the assessment of the impact that these developments can have on the growth prospects of the market.
The report primarily focuses on the business conditions coupled with the potential headways as well as the entryways in the global Product Data Management (PDM) Software market.
In summary, the report throws light on the market status throughout the forecast period, which starts with 2020, and ends with 2026.Request Free Sample Report @ https://www.wiseguyreports.com/sample-request/5463071-covid-19-impact-on-global-product-data-managementPrimary Boosters & ChallengesApart from offering an in-depth appraisal of the main dynamics that mold the Product Data Management (PDM) Software market, the report also outlines the pricing record, volume trends and the market size in the coming years.
The significant opportunities, challenges along with the primary boosters are also outlined in the report, for providing an enhanced comprehension of the market.Regional StudyThe opportunities, threats, inadequacies and strengths in the Product Data Management (PDM) Software market have been elucidated in the report, with respect to certain regions.
The oncoming and the latest trends combined with the market size across these regions are provided in this section of the report.Method of ResearchThe Product Data Management (PDM) Software market research provides hands-on data, after an acute analysis conducted by the experts, who have used the Porter’s Five Force Model’s parameters.
Experts’ valuable inputs are outlined in the report, outlining the current norms along with the names of the leading industry participants and the chain network around the world.
A malfunctioning piece of equipment might not seem like a big deal, but if it’s a crucial piece of manufacturing equipment, that malfunction can have a devastating impact on that company’s ability to produce and, consequently, generate revenue.The idea is to have a system in place that can predict when an asset will fail.
AI-based predictive maintenance in the pharma sector is a powerful tool for manufacturers to minimize downtime and maximize production.
Website: Predictive Maintenance in Pharmaceutical Industry
