The report "Predictive Maintenance Market with COVID-19 Impact Analysis by By Component (Solutions, Services), Deployment Mode (On-premises, Cloud), Organization Size (Large Enterprises, SME), Vertical and Region - Global Forecast to 2026", size to grow from USD 4.2 billion in 2021 to USD 15.9 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 30.6% during the forecast period. Various factors such as increasing spending on marketing and advertising activities by enterprises, changing landscape of customer intelligence to drive the market, and proliferation of customer channels are expected to drive the adoption of predictive maintenance technologies and services.
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Predictive maintenance is an approach used by enterprises to predict future failure points as well as monitor the condition of an asset in real-time. Besides passive monitoring, the predictive maintenance technique leverages ML algorithms that take critical historical data, such as temperature, pressure, and vibration, as an input, thus providing prediction related to the condition of an asset in real-time. This, in turn, enables enterprises to significantly reduce unplanned machine downtime and decide whether any particular asset needs maintenance. Predictive maintenance ensures the machine is taken for maintenance before it fails, due to which there are minimal losses in production. Traditional maintenance software currently cannot manage these expectations, as these maintenance solutions are reactive and periodic, which might affect the productivity of an enterprise due to unexpected downtime of the asset. Predictive maintenance solutions leverage technologies, such as Artificial Intelligence (AI), Internet of Things (IoT), and big data, to gather meaningful insights from all the data received from the machines, thus helping in taking necessary actions before the breakdown of the asset.
Public Cloud segment to account for a larger market size during the forecast period
Public cloud deployment mode in the predictive maintenance market offers a cloud-based environment and is available to the general public over the internet. It requires minimal investment, no hardware setup, and no infrastructure management. It is a type of virtual network environment wherein various service providers provide cloud-based analytical solutions. Organizations are moving their complex core applications to public cloud due to its compatibility, security, and performance.
Government and Defense vertical to have the largest market size during the forecast period
Government and public institutions are shifting toward a digital mode of operations, with the developed IT infrastructure in place, to improve reliability and efficiency. Government and public authorities are taking various initiatives, such as smart cities and traffic management, to enhance the lifestyle of its citizens and administer the cities. Public sector organizations all over the world have the responsibility of employing high-value assets and operations associated with utilities, public venues, roads, bridges, transit and mobility systems, airports, ports, and public health systems.
APAC to hold higher CAGR during the forecast period
The predictive maintenance market has been segmented into five major regions: North America, Europe, APAC, Latin America, and MEA. APAC is expected to grow at a good pace during the forecast period. The region will be booming, as it is experiencing a lot of new entrepreneur setups, which would be looking forward to acquiring new customers and gaining customer trust by involving new paradigms of maintenance technologies to have a competitive advantage over the established players. Predictive maintenance vendors in this region focus on innovations related to their product line. China, Japan, India, and Bangladesh have displayed ample growth opportunities in the predictive maintenance market.
The major vendors in the global predictive maintenance market include Microsoft (US), IBM (US), SAP (Germany), SAS Institute (US), Software AG (Germany), TIBCO Software (US), HPE (US), Altair (US), Splunk (US), Oracle (US), Google (US), AWS (US), GE (US), Schneider Electric (France), Hitachi (Japan), and PTC (US).
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