Predictive Maintenance Market size is poised to reach USD 81.5 Billion by the end of 2031, growing at a CAGR of 31.9% during the forecast period, i.e., 2022-2031. In the year 2021, the industry size of predictive maintenance was USD 5.2 Billion. The growth of the market can be attributed to the growing need to reduce downtime and maintenance costs. Predictive maintenance predicts the best time for the maintenance of the equipment which also makes the maintenance procedure cost-effective, therefore it reduces the wastage of time and resources on the occasion of machine breakdown. Large factories lose 323 productivity hours annually on average. The average cost of lost sales, fines, downtime for employees, and restarting production lines is USD 532,000 per hour, or USD 172 million per facility yearly.
In addition to these, factors that are believed to fuel the market growth of the predictive maintenance market include digital transformation taking place in the organization is boosting the company’s progress along with the data consumption and production. The digital transformation of industries into industry 4.0, has introduced new predictive maintenance methods which are creating a new concept known as Maintenance 4.0. Organizations that have undergone digital transformation are anticipated to generate more than half of the global GDP by 2023. Moreover, every day, it is estimated that 1.145 trillion MB of data are produced. Around 300 billion emails were sent daily in 2022. Users sent about 650 million Tweets daily in 2022.
Growth Drivers
Challenges
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Base Year |
2021 |
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Forecast Year |
2022-2031 |
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CAGR |
31.9% |
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Base Year Market Size (2021) |
USD 5.26 Billion |
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Forecast Year Market Size (2031) |
USD 81.58 Billion |
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Regional Scope |
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End-user (Government, Defence, Automotive, Energy, Utilities, Transportation, Logistics, Healthcare, Life Sciences, Food, Beverage, Digital)
The global predictive maintenance market is segmented and analyzed for demand and supply by end-use vertical into government and defense, automotive, energy and utilities, transportation and logistics, healthcare and life sciences, food and beverage, digital industry, and others. Out of all types of end-use verticals, the energy and utilities segment is estimated to gain the largest market size of USD 14.3 billion by the end of 2031, by growing at a CAGR of 32.6% over the projected time frame. Moreover, in 2021, the segment collected a revenue of USD 857.3 million. The growth of the segment can be attributed to the increasing need for minimizing productivity loss and maintenance costs. Predictive maintenance detects the possible issues in the equipment, which improves its productivity. Unplanned downtime costs the average oil and gas complex 32 hours of lost output each month, or USD 220,000 per hour. At each site, that comes to an annual total of USD 84 million.
Component (Solutions, Services)
The global predictive maintenance market is also segmented and analyzed for demand and supply by component into solutions and services. Amongst these two segments, the solutions segment is expected to garner a significant market revenue by growing at a CAGR of 31.6% over the forecast period. Moreover, the segment garnered a modest revenue in 2021. Furthermore, the solutions segment is categorized into integrated, and standalone. Growing need for a system, that combines all the technologies, to provide more integrated solutions. Such solutions are imperative in vast sectors, such as healthcare, food & beverage, and manufacturing. For instance, higher adoption of electronic medical records in the healthcare sector is expected to create huge demand for predictive maintenance solutions that integrated entire healthcare systems. During the period of the pandemic, nearly 73% of hospitals maintained electronic medical records in Japan. Moreover, in the United States, around 90% of office-based physicians use any one of the electronic health record (HER) systems. Furthermore, the growing need for solutions that have the ability to solve different issues in the industry is also expected to boost the growth of the segment. For instance, supply chain management needs predictive maintenance solutions for better safety & security, integration of the different regions, and most importantly enhances customer experience. On receiving better customer experience, around 89% of customers are believes to come back to the company make another purchase.
Our in-depth analysis of the global market includes the following segments:
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By Component |
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By Deployment Mode |
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By Organization Size |
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By End User Vertical |
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APAC Market Statistics
The Asia Pacific predictive maintenance market, amongst the market in all the other regions, is projected to hold the largest market revenue of USD 23.98 billion by the end of 2031. The region’s market is to grow at the highest CAGR of 35.4% over the forecast period. The market in Asia Pacific garnered a revenue of USD 1.18 billion in 2021. The growth of the market can be attributed majorly to the rapid penetration of digitization in the company. Around 70% of major corporations and middle-market businesses in the APAC region have a digital transformation strategy in place, with Taiwan leading the pack with 95%. This represents an increase from 2020 when 57% of APAC businesses had a digital strategy. Furthermore, the rise in the downtime occurring in the industry, which in turn leads to production loss is also expected to boost the market growth. Disruption in the supply chain management had increased the average downtime days by approximately 95% in the energy industries of the Asia Pacific region.
Software AG launched ARIS, a new toolkit that assists the planning, execution, and evaluation of sustainability activities. This free solution centers processes around its clients' sustainability plans, aiding in their execution and making them transparent and verifiable.
Asystom announced its selection for the predictive maintenance project implemented by Northumbrian Water Limited. The organization aims at implementing predictive maintenance in order to prevent breakdowns, offer their customers with uninterrupted services, and lower operating costs.
Author Credits: Abhishek Verma, Hetal Singh
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