The Growing Importance of Predictive Maintenance in Today’s Market
Predictive Maintenance is a plan for monitoring equipment performance and condition that decreases the risk of machine failure under normal operating conditions.
Predictive Maintenance utilizes data analytics, machine learning, and artificial intelligence to forecast when machines or equipment will need repair, allowing businesses to do maintenance effectively.
Market Growth and Forecast
In 2022, the Global Predictive Maintenance market was valued at $7.85 billion. The market is expected to increase and reach approximately $80.41 billion by 2030.
During the forecast period, 2022 to 2030, the market will be growing at an approximate CAGR of 29.5%.
The Predictive Maintenance Market is expanding as a result of technology improvements, increased industrial automation adoption, and the need for organizations to optimize their maintenance procedures.
Top Global Players
Recent Trends and User-based Statistics
In 2021, Using the new lubrication technology which comprised of predictive maintenance technology, the Noranda Alumina factory in Gramercy, LA, reduced bearing changes by 60%, saving roughly $900,000 in bearing purchases and avoiding costly downtime.
According to Deloitte, companies that used predictive maintenance during 2020-2022 saw a 5-15% reduction in downtime, a 3-5% drop in new equipment costs, up to a 20% increase in labor productivity, and around 30% decrease in inventory levels, causing a 5-20% reduction in carrying costs.
In 2022, P&G and Microsoft established a collaboration to expand P&G’s digital manufacturing platform and use the Industrial Internet of Things (IIoT) to bring products to consumers faster, raise customer happiness, and improve efficiency to lower costs by using Microsoft’s Azure suite.
SAS Institute’s SAS Viya platform was launched in May 2021. The technology helped to increase the efficiency of information and analysis by integrating a data management system into its other cloud services, the SASViya platform, which benefited several users.
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Data Sources: GrandViewResearch, AlliedMarketResearch, PolarisMarketResearch, FutureMarketInsights, MarketsAndMarkets, and others.
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