Sunday, July 7, 2024

AI in Manufacturing Market Size, Share, Analysis And Forecast 2032

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Artificial Intelligence (AI) in Manufacturing Market Overview:

Artificial intelligence can be defined as the ability of computer-controlled products to do particular tasks that are performed by human beings by using their intelligence and discernment. Artificial intelligence is aiding industry 4.0 in automatic production, advanced digitized networks, monitoring processes in factories, decentralized manufacturing system, and others.

The Artificial Intelligence (AI) in Manufacturing Market is projected to grow from USD 2.03 Billion in 2023 to USD 31.47 Billion by 2032, exhibiting a compound annual growth rate (CAGR) of 35.60% during the forecast period (2023 – 2032).

TOP KEY PLAYERS:

  • Nvidia Corporation
  • Intel, Inc.
  • IBM Corporation
  • Siemens AG
  • General Electric company
  • Google, Inc.
  • Microsoft Corporation
  • Amazon Web Services
  • Bosch
  • Rockwell Automation
  • Cisco Systems
  • SAP SE
  • Foxconn

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MARKET SEGMENTATION 

If we look at the latest research analysis of Artificial Intelligence (AI) in manufacturing market, the industry can be ramified based on component, application, technology, and vertical. Among all the segments of this market, the artificial intelligence and machine learning segment will experience noteworthy growth during the forecast period. The supply chain management segment will also register a significant CAGR of 8%. The demarcation of this market into various segments is as follows:

Based on components, it has hardware, services, and software.

Based on the application, it has supply chain management, field services, it management, predictive maintenance, robotics, quality control, and others.

Based on the technology, it has deep learning, artificial intelligence & machine learning, computer vision, natural language processing, and context-aware computing.

Based on vertical, it has automobile, energy & power, food & beverage, semiconductor & electronics, pharmaceuticals, aerospace & defense, and others.

AI Applications in Manufacturing:

AI in manufacturing encompasses various applications, including predictive maintenance, demand forecasting, quality control, and design optimization. These applications leverage machine learning (ML) solutions and deep learning neural networks to optimize manufacturing processes with improved data analysis and decision-making.

Generative AI, data-centric AI, and synthetic data are making AI more accessible and suitable for solving manufacturing operations challenges. These approaches put AI within reach of plant workers and manufacturing engineers, who understand everyday production requirements and process challenges but may not be well-versed in complex modeling.

AI plays a crucial role in additive manufacturing by optimizing material dispensing, design optimization, error detection, and correction in real-time.

AI facilitates quality assurance in manufacturing, particularly in the electronics space, by automating the process and ensuring proper configuration of circuits and components.

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Regional Analysis:

Looking at Artificial Intelligence (AI) in manufacturing market share and other details it becomes very clear that this industry is notably working in four major regions of the world that is Asia Pacific region, the North American region, the European region, and the rest of the world (the Middle East and Africa). The Asia Pacific region is anticipated to dominate this market during the forecast period as its developing countries such as India, China, and Japan are have huge manufacturing infrastructure for semiconductors, power, energy, pharmaceuticals, and electronics. Also, the rising adoption of robots in different manufacturing industries is another factor that helps this market in achieving greater heights by the end of the forecast period. The North American region will account for the second-largest market share during this period of research as countries of this region are adopting the new technologies for different applications such as process planning, automation of factory, scheduling of production, etc.

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