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Predictive Maintenance Software Market Size, Share & Industry Analysis, By Deployment (On-Premise, Cloud), By Organization Size (Large Enterprises, Small and Medium Enterprises (SMEs)), By Application (Manufacturing, Government, Energy and Utilities, Transportation, Healthcare) And Regional Forecast, 2024-2032

Report Format: PDF | Published Date: Ongoing | Report ID: FBI104854 | Status : Upcoming

Presently, maintenance takes up a substantial extent of business costs. It is crucial to put in place measures to diminish them. Predictive maintenance software is the consistent maintenance of equipment and assets to preserve their life. It efficiently helps in predicting any system failure before it takes place. The objective of predictive maintenance is to minimize equipment downtime and augment maintenance schedule. This real-time equipment assessment allows maintenance tasks to be performed cost-effectively and more accurately. Thus, predictive maintenance software is becoming popular each day. The capability to decrease maintenance costs is the key fact to drive software adoption. Predictive maintenance also knowingly reduces the occurrence of catastrophic or unexpected equipment failure. This can lead to more predictable capacity planning, reduced troubleshooting, and longer equipment life. Additionally, the capability to minimize equipment downtime, maintenance cost, and improve workforce efficiency further enhances the demand for predictive maintenance software across the manufacturing and corporate sectors.  


Internet of things, machine learning, and artificial intelligence-powered predictive maintenance software is most demandable amongst industry. The development of predictive maintenance software with the latest technologies is expected to stimulate market growth. Also, ongoing industrialization entices companies to adopt advanced technologies such as artificial intelligence, machine learning, and the internet of things. With the increasing adoption of such cutting-edge technologies, the implementation of effective predictive maintenance is probable to increase. Moreover, the growing proliferation of cloud applications would substantially augment the demand for cloud-based predictive maintenance software. The arrival of real-time condition monitoring solution would offer excellent growth opportunities for the market.



Key Players Covered:


The global predictive maintenance market's highly competitive landscape entices key players to implement various organic and inorganic growth strategies. As the competition in the global marketplace is intense, vendors take active measures to offer a diversified product portfolio to meet the customers' demand. Prominent companies adopt various business growth strategies such as partnerships, collaborations, mergers, and acquisitions to sustain their competence in a global marketplace. For instance, in November 2018, Rockwell Automation Inc. partnered with Metso Outotec Corporation to launch predictive maintenance solutions for mining equipment. The solution is aimed to maximize the performance of communication circuits and uptime. Similarly, in February 2018, Jacobs Engineering Group partnered with Atos SE to offer condition-based, predictive maintenance solutions.


Prominent companies in the global market includes Baker Hughes Group, Pegasystems Inc., Software AG, eMaint by Fluke Corporation, Totalmobile Ltd., AVEVA Group plc, SAP SE, Wipro Limited, SenseGrow Inc., MicroMain Corp., Robert Bosch GmbH  PTC, Inc., General Electric Company, IBM Corporation, Rockwell Automation Inc., SAS Institute Inc, eMaint Enterprises LLC, Schneider Electric SE, Software AG, and among others.


Regional Analysis:


The increasing adoption of innovative technologies such as the internet of things, artificial intelligence, machine learning, and data analytics drive the predictive maintenance market across North America. The presence of prominent vendors is further stimulating market growth. The developed industrial sector in North America is adopting advent technology to improve operational performance and system downtime. This factor is further flourishing the predictive maintenance software demand across the region. Progressive approaches towards advanced technologies lead European establishments to increase organizational investments. Thus, Europe is also expected to exhibit significant growth in a global marketplace.


Asia-Pacific would emerge as the most opportunistic region for the predictive maintenance market. This market growth has been attributed to the strong manufacturing base. Apart from this, market players are consistently focusing on establishing and expanding their business portfolio across the Asian countries, which would further boost the market growth.


 


Segmentation


























 ATTRIBUTE


  DETAILS

By Deployment


 




  • On-Premise

  • Cloud



By Organization Size




  • Large Enterprises

  • Small and Medium Enterprises (SMEs)



By Application




  • Manufacturing

  • Government

  • Energy and Utilities

  • Transportation

  • Healthcare

  • Aerospace and DEfense

  • Others



By Geography




  • North America (the United States, Canada, and Mexico)

  • South America (Brazil, Argentina, and Rest of South America)

  • Europe (the U.K., Germany, France, Italy, Spain, Russia, Benelux, Nordics, and Rest of Europe)

  • Middle East & Africa (Turkey, Israel, GCC, North Africa, South Africa, and Rest of the Middle East & Africa)

  • Asia Pacific (China, India, Japan, South Korea, ASEAN, Oceania, and Rest of Asia Pacific)



Key Industry Developments:



  • September 2020: TeamViewer Group has launched artificial intelligence supported predictive maintenance solution which helps to reduce downtimes and save costs.

  • August 2019: Cisco Systems, Inc has acquired a predictive maintenance-based, customer experience solution providing company ‘Cloudcherry,’ to augment its cognitive contact center solution using analytics and predictive maintenance capabilities.

  • Global
  • 2023
  • 2019-2022
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