Predictive Maintenance Market Research Report Covers,Future Trends
According to the new research report, titled “Predictive Maintenance Market — Global Analysis and Forecast to 2027,” published by The Insight Partners, the market is expected to reach US$ 10.83 billion by 2027, registering a CAGR of 15.1% during 2020–2027.
Predictive Maintenance Market in APAC is Expected to Grow at Highest CAGR
The predictive maintenance market in APAC is expected to witness the fastest CAGR during the forecast period. The growth of the market in the region is primarily attributed to the massive public and private sector investments to enhance asset maintenance solutions owing to which predictive maintenance solutions are deployed to automate the plant’s maintenance process.
The availability of cheap labor in the region has led to the establishment of a vast number of manufacturing units in the region. Additionally, the growing importance of reducing overall downtime and operating costs in manufacturing facilities is compelling plant owners to deploy these solutions in the system. APAC has recorded an increased focus on the new solutions, such as predictive maintenance, to optimize the output via asset maintenance. The adoption of predictive maintenance among the industries in China is another factor propelling the growth of the market. For example, suppliers of power generation in the country are said to use online condition monitoring to evaluate quality maintenance. The benefits of predictive maintenance increase its demand, thereby contributing to the growth of the APAC predictive maintenance market.
Furthermore, improving safety in factories is one of the primary concerns among manufacturing industry’s as machine breakdowns in the manufacturing industry cause severe production losses. Additionally, the demand for improved protection, cost reduction, and machine utilization drive the growth of the predictive maintenance market in APAC. However, the lack of data privacy and data storage problems is expected to limit market growth. Nonetheless, the predictive maintenance market in manufacturing is likely to thrive as the manufacturing industry looks forward to improving its operations through the adoption of new tools and techniques across the region.
Key findings of the study:
To analyze IoT data, companies leverage AI and ML technologies to achieve incredible precision, accuracy, and speed over traditional business intelligence tools. With the advent of predictive maintenance, businesses can make operational predictions up to 20 times faster and more accurate than threshold-based surveillance systems. Unplanned downtimes resulting from equipment breakdown can cause huge revenue loss in various industries, such as manufacturing and oil & gas. AI-based IoT solutions offer predictive maintenance applications for enterprises to predict equipment failures in advance. Predictive maintenance-based solutions help companies identify patterns for predicting equipment failure in constant data streams. Due to the growing awareness among manufacturing industry managers about maintenance operations and the need to reduce downtime, the demand for predictive maintenance solutions has significantly increased. Managers in manufacturing companies are continually working toward improving equipment maintenance processes in their manufacturing facilities and finding methods that can reduce faulty operations and increase process benefits.