Chicago, June 06, 2024 (GLOBE NEWSWIRE) -- The Global Artificial Intelligence in Manufacturing Market size is estimated to be valued USD 3.2 billion in 2023 and is anticipated to reach USD 20.8 billion by 2028, at a CAGR of 45.6% during the forecast period. The market growth is ascribed to emerging industrial IoT and automation technology. AI in manufacturing market’s growth in the US is fueled by automation for increased efficiency and lower costs, with predictive maintenance and quality control optimizing processes. Supply chain enhancements and customization capabilities improve overall productivity.
<>To know about the assumptions considered for the study.
Artificial Intelligence in Manufacturing Market Segmentation:
By Technology
By Application
By Industry
Regional Analysis of Artificial Intelligence in Manufacturing Market:
This Artificial Intelligence in Manufacturing market in Asia Pacific is further divided into China, Japan, South Korea, and Rest of Asia Pacific. the Asia Pacific, led by China, Japan, and South Korea, is considered the largest market for industrial robots. Industrial robots generate a huge amount of data. This data is used in deep learning algorithms to further train the robots. Rapid industrialization in Asia Pacific has boosted the manufacturing sector. Furthermore, Many small and mid-sized enterprises (SMEs) are present in the countries in Asia Pacific considered in this study.
Artificial Intelligence in Manufacturing Companies:
Major vendors in the Artificial Intelligence in Manufacturing companies include Siemens, IBM, Intel Corporation, NVIDIA Corporation, and General Electric, Microsoft Corporation, Google, Amazon Web Services are among others.
Artificial Intelligence in Manufacturing Market Applications:
Predictive maintenance & machinery inspection application to account for the largest share in the market during forecast period.
AI technology in predictive maintenance and machinery inspection is used in regular examination, inspection, lubrication, testing, and making equipment adjustments. The Predictive maintenance is a data-driven approach utilizing artificial intelligence to predict when equipment or machinery will fail.
This prevents breakdowns by allowing maintenance to be performed just in time. AI algorithms, such as machine learning and deep learning models, analyze historical data to identify breakdown patterns and trends. By making predictions about equipment failures and performance degradation, these models can help prevent future issues.
Metals & heavy machinery industry to grow at a highest CAGR during the forecast period.
Metals & heavy machinery comprise the production of different machinery used in construction, infrastructure development, and manufacturing applications. Implementing AI in the metals & heavy machinery industry can help manufacturers analyze machine conditions in advance to avoid unplanned downtime and wastage. Also, AI solutions exhibit predictive maintenance capabilities that help the industry players save time and cost. Field services also play a major role in this industry. Field services are used to collect and sense different data such as heat, sound, light, odor, and eddy current. The collected data is sent to operators to analyze and take action according to the situation in the plant.
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