Global Predictive Maintenance Market is expected to reach USD 32.30 billion by 2030

The Global Predictive Maintenance Market is valued at USD 5.93 billion in 2023, and is expected to reach USD 32.30 billion by 2030, with a CAGR of 27.4% from 2024 to 2030, according to new research by Next Move Strategy Consulting.

The widespread adoption of IoT devices enables real-time data collection and predictive analytics, transforming maintenance practices. This technology-driven approach improves equipment reliability, reduces downtime, and allocates resources efficiently. This factor drives the growth of the predictive maintenance industry.

However, the high cost and complexity of implementing and integrating predictive maintenance solutions discourage many organizations from adopting this promising technology. This can hinder the widespread adoption of predictive maintenance across various industries. On the contrary, the introduction of the predictive maintenance (PdM) 4.0 is changing the landscape of various industries, as it enables companies to move beyond traditional visual and instrument inspections to real-time condition monitoring.

With the power of big data analytics, companies can use predictive techniques such as regression analysis to identify meaningful patterns in vast amount of data. According to a PwC survey, about 11% of businesses have reached predictive maintenance 4.0. The remaining two-thirds remain at stages 1 or 2. Around half of the respondents have plans to implement PdM 4.0 in the future.

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According to the report, leading players in the predictive maintenance market include IBM Corporation, Microsoft Corporation, SAP SE, Schneider Electric, Hitachi Ltd., SAS Institute, Inc., Oracle Corporation, Siemens, SparkCognition, Axiomtek Co. Ltd., Banner Engineering Corp., SIGMA IT, RFMicron, Inc., Larsen & Toubro Infotech Limited, SPSS Analytics Partner, Predictive Maintenance Solutions LLC, Fujitsu Ltd., Software AG, Engineering Consultants Group, Inc., General Electric, and others.

These market players are adopting strategies such as collaboration and product launches across various regions to maintain their dominance in the predictive maintenance market. 
For instance, in May 2023, IBM Watson planned to integrate with SAP, bringing AI-driven insights and automation to enhance user experiences. This collaboration aimed to boost productivity and provide predictive insights, benefiting retail, manufacturing, and utilities sectors.

Also, in June 2022, Microsoft and P&G partnered to make manufacturing smarter using Microsoft Azure, AI, and the Industrial Internet of Things (IIoT) to enable scalable predictive quality, predictive maintenance, controlled release, touchless operations, and manufacturing sustainability optimization. This partnership will accelerate P&G's growth and business transformation by seamlessly integrating digital technology across its people, assets, workflows, and business processes, fostering resilience and adaptability.

Moreover, in January 2023, Willow Innovations launched the Willow 3.0 predictive maintenance companion app for Apple Watch. This will empower lactating parents to seamlessly track, control, and view their pumping sessions from their wrists.

Furthermore, in November 2022, Smart Eye introduced Smart Eye Pro 10.1 and a Mobile Stand unit, featuring an enhanced remote predictive maintenance system that optimizes performance for all participants, including those with eye disorders.

In April 2022, Ardo Medical launched the Ardo Alyssa predictive maintenance, the world's first predictive maintenance with a personal power pump function that helps mothers produce more milk. 

Key Insights from the Predictive Maintenance Market Report:

  • The information related to key drivers, restraints, and opportunities and their impact on the predictive maintenance market is provided in the report.

  • The value chain analysis in the market study provides a clear picture of the role of each stakeholder.

  • The market share of the global predictive maintenance market players and their competitive analysis are provided in the report.

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