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The market dynamics of Artificial Intelligence (AI) in the manufacturing sector are experiencing transformative shifts, redefining how industries approach production processes and efficiency. A significant dynamic is the integration of AI-driven technologies to enhance operational efficiency and optimize production workflows. Manufacturers are leveraging AI for predictive maintenance, quality control, and demand forecasting, allowing for proactive decision-making and minimizing downtime. This dynamic reflects the industry's recognition of AI as a pivotal tool for achieving operational excellence and ensuring a competitive edge in the rapidly evolving manufacturing landscape.
Another notable dynamic in the AI in manufacturing market is the emergence of smart factories. AI technologies, including machine learning and robotics, are instrumental in creating intelligent and interconnected manufacturing environments. Smart factories leverage AI to enable real-time data analysis, predictive analytics, and adaptive manufacturing processes. This dynamic marks a paradigm shift towards Industry 4.0, where AI plays a central role in transforming traditional manufacturing facilities into agile, data-driven, and interconnected ecosystems.
The customization trend is influencing the dynamics of AI adoption in manufacturing. As consumer demands for personalized and customized products rise, manufacturers are turning to AI-driven solutions to accommodate these preferences efficiently. AI enables adaptive manufacturing processes that can quickly reconfigure production lines to meet changing demands. This dynamic reflects the industry's responsiveness to evolving consumer expectations and the need for agile manufacturing systems.
Supply chain optimization is a key dynamic driven by AI in the manufacturing sector. Manufacturers are increasingly relying on AI algorithms for demand forecasting, inventory management, and logistics optimization. AI enables real-time analysis of vast datasets, allowing for more accurate predictions and agile responses to supply chain disruptions. This dynamic reflects the industry's commitment to creating resilient and responsive supply chains, especially in the face of global uncertainties and market fluctuations.
Collaborative robots, or cobots, are shaping the dynamics of AI adoption on the manufacturing floor. These robots work alongside human workers, enhancing efficiency and safety in various manufacturing tasks. The integration of AI allows cobots to adapt to changing production requirements, collaborate seamlessly with human workers, and contribute to increased productivity. This dynamic represents a collaborative and synergistic approach to leveraging AI technologies in manufacturing, emphasizing the coexistence of human and machine capabilities.
AI is also influencing quality control and defect detection in manufacturing processes. Advanced machine vision systems, powered by AI algorithms, enable real-time inspection and identification of defects in products. Manufacturers leverage AI-driven quality control to enhance product quality, reduce waste, and ensure compliance with industry standards. This dynamic reflects the industry's commitment to achieving higher levels of precision and quality assurance through AI technologies.
Data security and privacy considerations are becoming increasingly important dynamics in the AI in manufacturing market. As manufacturers accumulate vast amounts of sensitive data for AI-driven analysis, ensuring the security and privacy of this information becomes paramount. Manufacturers are investing in robust cybersecurity measures and compliance frameworks to address these concerns. This dynamic underscores the industry's recognition of the importance of securing data in the age of AI-driven manufacturing.
The talent gap is a notable challenge influencing the dynamics of AI adoption in manufacturing. While the demand for AI expertise in manufacturing is growing, there is a shortage of skilled professionals with the necessary knowledge. Manufacturers are addressing this challenge through training programs, collaborations with educational institutions, and strategic partnerships with AI solution providers. This dynamic highlights the industry's proactive efforts to bridge the talent gap and cultivate a workforce capable of harnessing the full potential of AI technologies.
Covered Aspects:
| Report Attribute/Metric | Details |
|---|---|
| Segment Outlook | by Component, by Technology |
Artificial Intelligence (AI) in manufacturing Market Highlights:
Artificial Intelligence (AI) in Manufacturing Market Synopsis:
The Artificial Intelligence (AI) in Manufacturing Market industry 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).
Figure 1: Artificial Intelligence (AI) in Manufacturing Market Size, 2023 - 2030 (USD Billion)
Developing market of industry 4.0 and smart factories, increasing adoption of automation by SMEs as well as large enterprises, and development in advanced technologies such as artificial intelligence, machine learning & deep learning are some of the prime factors driving the growth of the Artificial Intelligence (AI) in Manufacturing Market. However, data security & privacy concerns, and high integrating cost of AI-based solutions are some major factors hindering the market growth. The developing market of big data technology and increasing application of AI for business intelligence are some factors bringing fruitful opportunities for the market in the coming years. Whereas, the lack of skilled expertise is a major challenge in the Artificial Intelligence (AI) in Manufacturing Market.
Industry 4.0 or smart maintenance, predictive maintenance, testing, and quality optimization, supply chain communication, and yield enhancement are some of the use cases of artificial intelligence in manufacturing. Artificial intelligence and machine learning are benefitting industry 4.0 in automated production and monitoring process in smart factories, advanced digitized networks, automation of quality and inspection process, decentralized manufacturing system, and others.
AI in Manufacturing Market Segmentation
The global artificial intelligence (AI) in manufacturing market has been segmented into component, technology, application, vertical, and region.
- By component, the market has been segmented into hardware, software, and services. By hardware the market has been segmented into processor, memory, and network. The processor segment covers microprocessor unit (MPU), graphical processing unit (GPU), field programmable gate array (FPGA), and application-specific integrated circuits (ASICs). Whereas, the services segment has been further breakdown into deployment & integration, and support & maintenance.
- By technology, the Artificial Intelligence (AI) in Manufacturing Market market has been segmented into machine learning & deep learning, natural language processing, context-aware computing, and computer vision.
- By application, the Artificial Intelligence (AI) in Manufacturing Market has been sub-segmented into predictive maintenance, supply chain management, IT management, field services, quality control, robotics, and others
- By vertical, the Artificial Intelligence (AI) in Manufacturing Market has been classified into automobile, aerospace & defense, energy & power, semiconductor & electronics, food & beverage, pharmaceuticals, and others.
- By region, the Artificial Intelligence (AI) in Manufacturing Market has been segmented into North America, Europe, Asia-Pacific, and the rest of the world.
AI in Manufacturing Market Regional Analysis
Market Research Future (MRFR) study has covered the following countries in the regional analysis of artificial intelligence (AI) in the manufacturing market—the US, Canada, and Mexico in North America; Germany, the UK, France, Russia, Spain, the Netherlands, and Italy in Europe; China, Japan, India, Singapore, Australia, the Philippines, and South Korea in Asia-Pacific; and the Middle East & Africa and South America in the rest of the world.
Artificial intelligence in manufacturing market is currently dominated by Asia-Pacific region as the primary economic countries such as China, India, South Korea, and the Philippines are the major manufacturing centers of semiconductors, electronics, energy & power, and pharmaceuticals. Further, increasing adoption of robots in manufacturing processes is expected to aid the region in dominating the Artificial Intelligence (AI) in Manufacturing Market throughout the forecast period.
North America is the second highest contributor in artificial intelligence market. The US is the early adopter of new technologies for application such as factory automation, process planning, engineering design, and production scheduling among others.
Artificial intelligence (AI) in the manufacturing market in Europe is projected to gain high momentum during the forecast period due to increasing adoption of industry 4.0 and robotics by automotive, and aerospace industry.
AI in manufacturing Market Key Players
Market Research Future has identified following key players in the market
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Intel Inc.
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IBM Corporation
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Siemens AG
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General Electric company
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Google, Inc.
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Amazon Web Services
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Bosch
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Rockwell Automation
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Cisco Systems
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SAP SE
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Foxconn, and others.
Intended Audience
- Investors and consultants
- System Integrators
- Government Organizations
- Research/Consultancy firms
- Technology solution providers
- Software Developers
- OEMs
Latest Industry News of AI in Manufacturing Market
Oden Technologies Ltd., a 2024 manufacturer of AI-driven solutions, said on Wednesday that it had raised $28.5 million in a new funding round headed by Nordstjernan Growth to address productivity issues in manufacturing through the use of AI and data analytics products. Oden client INX International Ink Co., Flat Capital, and Recurring Capital Partners are among the new investors participating in the Series B round. Participating in the round were almost all of the current investors, including Atomico and EQT Ventures. Oden raised a total of $58.7 million with the current fundraising round, which was led by Atomico in its $10 million Series A round in 2018. The world's first enterprise platform for AI governance, called AILM (AI Lifecycle Management Platform), will formally open in 2023, according to a statement made by Profet AI, an enterprise AI application supplier for the industrial sector. Manufacturers may control, manage, and disseminate their core domain know-how both internally and externally to support growth into new markets or nations thanks to AILM.
April 2023
Siemens and Microsoft collaborate to integrate AI into industrial processes, enhancing productivity and innovation. Through AI-powered apps and automation software engineering, they aim to streamline workflows and accelerate development in manufacturing. Industrial AI enables real-time quality inspection, defect detection, and prevention, fostering efficiency and cost-effectiveness in production.
May 2023
Leading electronics manufacturers like Foxconn, Innodisk, Pegatron, Quanta, and Wistron are utilizing NVIDIA Generative AI and Omniverse to digitalize their factories, enhancing production efficiency and lowering costs. Through a comprehensive reference workflow, these companies are leveraging NVIDIA technologies for generative AI, 3D collaboration, simulation, and autonomous machines to optimize factory operations. This collaboration aims to improve quality and safety while reducing costly surprises and delays in the manufacturing process. NVIDIA's ecosystem of partners, including Foxconn Industrial Internet, Innodisk, Pegatron, Quanta, and Wistron, is instrumental in advancing industrial digitalization efforts across the electronics manufacturing sector.
November 2023
AWS and Siemens collaborate to integrate OT and IT in manufacturing, leveraging AI to enhance efficiency and decision-making. The deployment of AWS IoT SiteWise Edge from Siemens Industrial Edge Marketplace streamlines data ingestion, enabling AI-driven insights from machine to cloud. This integration aims to break down data silos, facilitating seamless exchange of AI-driven insights for improved operational efficiency and decision-making in manufacturing. The offering enables scalable deployment of AI-driven edge-to-cloud applications, empowering manufacturers to optimize their operations effectively.
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