In terms of revenue, the Global Predictive Maintenance Market is expected to reach USD 19.3 Billion by 2028, growing at a CAGR (Compound Annual Growth Rate) of 29.80% from 2023 to 2030.
The increase in investments in preventative maintenance programs designed to cut costs and downtime drives the global market's expansion. Investments in preventive maintenance programs yield a noticeable return on investment (ROI). Users using Predictive Maintenance, for instance, reported KPIs like a 2-6% increase in availability, a 5-10% cost reduction in inventory, and a 10-40% decrease in reactive maintenance. Additionally, according to a recent study by Deutsche Messe AG and Roland Berger, VDMA, 81% of firms are presently investing time and resources in Predictive Maintenance, and 40% already believe that implementing PdM will be extremely important for future business. Therefore, the market is expected to grow in the following years due to this rise in awareness and trust in Predictive Maintenance solutions.
On the other hand, the industry for Predictive Maintenance has profitably expanded thanks to the combination of artificial intelligence and machine learning. A growing number of clients are embracing these AI-powered solutions to assist in the transition from a reactive to a proactive strategy. The market participants are also aggressively launching innovative AI-enabled solutions. For instance, TeamViewer, a remote connectivity solutions provider, introduced its AI-supported TeamViewer IoT software in September 2020.
Key Highlights from the Report
- Based on Components, the Solutions segment dominates the Predictive Maintenance market with the maximum market share. It will continue its dominance in the forecast period because it significantly influences the likelihood of future device failure.
- Among Verticals, the Manufacturing segment accounted for the highest CAGR in the forecast period. This is a result of the growing need for industrial manufacturing.
- In terms of region, North America holds the significant market share within the Predictive Maintenance market. This is brought on by the growing popularity of Predictive Maintenance solutions that utilize cutting-edge IoT, cloud computing, machine learning, and AI technology.
New opportunities are opening up for analyzing data gathered from industrial assets thanks to ongoing technical developments in Big Data, cloud computing, and Machine-to-Machine (M2M) communication. IoT devices generate many data from various sources, such as cameras, sensors, and other connected devices. The data must be turned into usable and pertinent information to be helpful. Users can gain fresh perspectives by leveraging big data and data visualization techniques, batch systems, and offline analysis. Real-time data analysis and decision-making are frequently done manually, but they should be done automatically to make them scalable. AI technology's main purpose is to evaluate the vast volumes of data produced by the various IoT ecosystem components and transform the data into insightful knowledge.
Every company area uses Predictive Maintenance, including those trying to create a future-oriented business plan. Adopting these technological advancements could shift the game and accelerate digitalization in the manufacturing and industrial sectors. Manufacturing units are being digitalized by integrating operations technology (OT) and information technology (IT) into production processes, manufacturing facilities, and maintenance plans. Predictive Maintenance using digital transformation as a service (DTaaS) and the widespread use of more sophisticated computer technologies enhance machine dependability, sustainability, and overall efficiency in manufacturing operations. With all of its service components, it combines a mutually beneficial ecology of man, machine, and technology.
One of the most considerable challenges to the effective operation of Predictive Maintenance is ensuring that data flows easily from devices to ERP software to maintain security and dependability with minimum latency. However, as more businesses adopt and engage in Predictive Maintenance because of its advantages, these barriers are anticipated to diminish eventually. Therefore, data protection is one of the main priorities for companies using digital technology. Similar precautions must be taken to guarantee that no one has access to or controls critical and private client data, equipment performance data, or Predictive Maintenance systems without authorization.
Due to numerous solution and service vendors in this area, North America accounts for the biggest share of worldwide market revenues. Additionally, a growing understanding of predictive analytics, their significance, and early technology adoption have contributed to the market's expansion. Further, the U.S. Air Force is increasingly turning to predictive analytics to keep up with the maintenance requirements of its sizable fleet of fighters, bombers, tankers, transports, and helicopters. Estimates for the Air Force alone reach 5,400 aircraft. Additionally, the North American region is seeing an increase in market participants for Predictive Maintenance, which is helping the local economy.
The Global Predictive Maintenance Market is Segmented as follows
- Deployment Modes
- Organization Sizes
- Large Enterprises
- Small & Medium-sized Enterprises (SMEs)
- Government & Defense
- Energy & Utilities
- Transportation & Logistics
- Healthcare & Life Sciences
- North America
- Asia Pacific
- Latin America
- Middle East & Africa
List of the Key Players of the Global Predictive Maintenance Market is
Microsoft(US), Google (US), SAP(Germany), Splunk (US), IBM(US), Oracle (US), OPEX Group (UK), GE (US), Schneider Electric (France), AWS (US), SAS Institute (US), Software AG (Germany), TIBCO Software (US), Hitachi (Japan), HPE (US), Altair (US), PTC (US), RapidMiner (US), Dingo (Australia)
The Global Predictive Maintenance Market Scope can be Tabulated as below
|Market Size Provided for Years||2017 - 2030|
|Historic Years||2017 - 2021|
|Forecast Years||2023 - 2030|
|Regions & Counties Covered||
|Report Coverage||Market growth drivers, restraints, opportunities, Porter’s five forces analysis, PEST analysis, value chain analysis, regulatory landscape, technology landscape, patent analysis, market attractiveness analysis by segments and North America, company market share analysis, and COVID-19 impact analysis|