AI In Industrial Machinery Market Analysis

AI in Industrial Machinery Market Analysis

Based on component, the market is segmented into hardware, software, and services. The software segment is expected to hold a significant share of over 40% in 2022. Artificial intelligence software and algorithms are essential to enable intelligent decision making, predictive maintenance, and automation of business automation. Software includes machine learning algorithms for tasks such as predictive maintenance, defect detection, optimization, and quality control. These algorithms analyze data from sensors, mechanical inputs, and other sources to gain useful insights and help make smarter decisions. In addition, software solutions focus on integrating AI technology with existing business systems such as Supervisory Control and Data Acquisition (SCADA) and Systems Operation (MES). They facilitate data exchange, interaction, and integration between AI systems and machines.

To get key market trends

  Download Free Sample

Based on technology, the market is segmented into machine learning, computer vision, context awareness, and natural language processing. The machine learning segment of the AI in industrial machinery market expanded at over 25% CAGR in 2022. Machine learning algorithms analyze sensor data from commercial machines to predict failures or maintenance needs. This effective approach to maintenance reduces unplanned downtime and increases machine reliability. The combination of machine learning algorithms with technology provides improvements in monitoring, operations, efficiency, quality control, and decision-making. These drivers facilitate the adoption and use of machine learning in the artificial intelligence technology of the business machine market.

Based on application, the AI in industrial machinery market is segmented into predictive maintenance, quality control, process optimization, supply chain optimization, intelligent robotics, autonomous vehicles & guided systems, energy management, and human-machine interfaces. The predictive maintenance segment of the market expanded at over 20% CAGR during the forecast period. Predictive maintenance in industrial machinery involves the use of artificial intelligence and machine learning algorithms to analyze sensor data and predictive maintenance needs. Predictive maintenance relies on the analysis of large amounts of sensor data including temperature, vibration, pressure, and other parameters. Artificial intelligence algorithms process and analyze this data to identify patterns, trends, and anomalies that may indicate equipment failure or maintenance needs. The integration of data analysis, health monitoring, reliability improvement, optimization, service life extension, safety improvement, and decision-making data has driven the adoption and use of predictive maintenance in the industrial machinery industry.

North America AI in industrial machinery market held the highest revenue share of over 50% in 2022. North America is one of the leading business regions in terms of market size and adoption of AI in the tech industry. The market has seen steady growth driven by increased demand for automation, efficiency, and optimization across various industries. In addition, North America has a strong technology ecosystem with AI technology providers, software companies, and technology manufacturers. The region is at the forefront of AI research & development, driving innovations and the use of AI in industrial machinery. Overall, the North America market is characterized by scale, industrial progress, strong market, investment, government support, and business competition. These factors have led to the growth and adoption of AI technology in the industrial sector in the region.