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The market factors influencing the adoption and evolution of Artificial Intelligence (AI) in the manufacturing sector are multifaceted, reflecting a complex interplay of technological, economic, and operational dynamics. One significant factor is the relentless pursuit of operational efficiency and cost optimization. Manufacturers are increasingly turning to AI-driven solutions to streamline production processes, reduce downtime, and enhance overall operational efficiency. The potential for AI to analyze vast datasets, predict equipment failures, and optimize resource allocation aligns with the manufacturing industry's ongoing quest for lean and agile operations, making it a pivotal factor driving the adoption of AI technologies.
The growing complexity of manufacturing processes and the demand for more sophisticated products are key factors influencing the adoption of AI. As manufacturing becomes increasingly intricate, traditional approaches struggle to cope with the intricacies involved. AI, with its ability to process complex data patterns and learn from diverse datasets, offers a solution to navigate the complexities of modern manufacturing. This factor reflects the industry's recognition of AI as an enabler for handling intricate processes and delivering high-quality, technologically advanced products to meet market demands.
Another critical factor is the surge in data availability within manufacturing ecosystems. The proliferation of sensors, IoT devices, and interconnected machinery generates vast amounts of data. AI leverages this data to extract actionable insights, providing manufacturers with valuable information for decision-making. The availability of data is a driving force behind the integration of AI, enabling manufacturers to transition from reactive to proactive decision-making, optimize production workflows, and achieve a data-driven competitive advantage.
The trend towards Industry 4.0 and the adoption of smart manufacturing practices contribute significantly to the growth of AI in the manufacturing market. Industry 4.0 emphasizes the integration of digital technologies, including AI, into manufacturing processes, creating intelligent and interconnected ecosystems. The concept of smart factories leverages AI to enable real-time data analytics, predictive maintenance, and adaptive manufacturing. This factor reflects the broader industrial trend towards digital transformation, positioning AI as a central element in reshaping the future of manufacturing.
Supply chain optimization is a compelling factor influencing the adoption of AI in manufacturing. The complexity of global supply chains, coupled with the need for just-in-time production, demands a level of responsiveness and flexibility that traditional approaches struggle to provide. AI-driven solutions enhance supply chain visibility, improve demand forecasting, and optimize inventory management, addressing the challenges associated with globalized manufacturing. This factor underscores the role of AI in creating resilient and adaptive supply chain networks.
Market factors also include the increasing emphasis on quality control and defect detection in manufacturing processes. AI, particularly through machine vision systems, enables real-time inspection and identification of defects in products. Manufacturers are adopting AI-driven quality control to enhance product quality, reduce waste, and ensure compliance with industry standards. This factor aligns with the industry's commitment to delivering high-quality products and meeting stringent quality assurance requirements through the integration of AI technologies.
The shortage of skilled labor in manufacturing is another factor influencing the adoption of AI. As the industry grapples with a diminishing pool of skilled workers, AI-driven automation becomes a strategic imperative. Manufacturers are turning to AI-powered robotic systems and collaborative robots to augment human labor, mitigate the impact of the skills gap, and optimize production processes. This factor reflects the industry's proactive approach to addressing workforce challenges through the integration of AI-driven technologies.
Data security and privacy considerations play a crucial role in shaping the market factors for AI in manufacturing. With the increasing reliance on AI to analyze sensitive production data, manufacturers are prioritizing robust cybersecurity measures and compliance frameworks. Ensuring the security and privacy of data generated and processed by AI systems becomes paramount, influencing the selection and deployment of AI solutions in manufacturing environments.
Covered Aspects:
| Report Attribute/Metric | Details |
|---|---|
| Growth Rate | Â 47.1% (2023-2030 |
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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