The predictive maintenance market forecast
The global predictive maintenance market was valued at USD 4.16 billion in 2021 and is expected to grow at a CAGR of 30.9% during the forecast period, according to Polaris Market Research.
Market growth is primarily driven by the need to reduce costs and downtime associated with predictive maintenance. For instance, the data from the U.S. Department of Energy indicates that predictive maintenance is very cost-effective and that it helps an enterprise to gain remarkable results such as a tenfold increase in ROI, 70-75% decrease in breakdowns, 25-30% reduction in costs, and 35-45% reduction in downtime. In addition, the industry enables the technicians to plan and prepare for a repair by taking steps, including shifting the capacity to other equipment or scheduling activity for times with the minimum impact on production.
This results in the elimination of unplanned downtime during the production process. The Covid-19 pandemic disrupted industrial networks and manufacturing, including demand-side shocks along with the supply disruptions that had a negative impact on the industry.
The enterprises were forced to take harsh actions for their staff and employees, as SMEs were shut down, and production & manufacturing facilities were put on hold for a longer period of time. However, this situation has led to significant growth in focus on digital transformation among enterprises. For instance, the pandemic has boosted the need for enhanced manufacturing processes with the integration of technologies such as Machine Learning (ML) and Artificial Intelligence (AI) for the industry.
This has made manufacturing systems more agile and helped manufacturing companies increase their production capacity. Upsurge in investment in predictive maintenance solutions to reduce cost and downtime fuels the growth of the global market.
Investment in predictive maintenance initiatives generates a tangible return on investment (ROI). For instance, predictive maintenance users reported metrics such as 2-6% increased availability, 5-10% inventory cost reduction, and 10-40% reduction in reactive maintenance. In addition, as per the recent study by Deutsche Messe AG and Roland Berger, VDMA 81% of companies are currently devoting time and resources to predictive maintenance subject, while 40% already have confidence that practicing predictive maintenance PdM will be most significant for future business.
This increase in awareness and trust in predictive maintenance solutions is projected to fuel the growth of the industry in upcoming years. On the other hand, the integration of artificial intelligence and machine learning has created lucrative growth opportunities for the predictive maintenance industry. An increasing number of customers are using such solutions powered by AI to help shift from a reactive to a proactive approach. In addition, the market players are actively introducing new AI-enabled solutions. For instance, in September 2020, TeamViewer, a provider of remote connectivity solutions, launched TeamViewer IoT software, an AI-supported.
