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The market trends in Artificial Intelligence (AI) within the manufacturing sector reflect a transformative shift towards greater efficiency, flexibility, and innovation. One prevailing trend is the increased adoption of predictive maintenance powered by AI. Manufacturers are leveraging machine learning algorithms to analyze data from sensors and equipment, enabling them to predict potential breakdowns and schedule maintenance activities proactively. This trend not only minimizes unplanned downtime but also optimizes equipment performance, reducing overall operational costs for manufacturing facilities.
Industry 4.0 is a significant trend shaping the AI landscape in manufacturing. The integration of AI into smart factories, characterized by interconnected systems and real-time data analytics, is gaining momentum. Manufacturers are deploying AI technologies to create intelligent and adaptive production environments, facilitating data-driven decision-making and automation of complex processes. This trend reflects the industry's commitment to embracing the next phase of industrial evolution, marked by the convergence of digital technologies and physical manufacturing processes.
Customization and flexibility have become key trends in manufacturing, driven by consumer demands for personalized products. AI is playing a pivotal role in enabling agile and adaptive manufacturing processes that can quickly respond to changing customer preferences. Manufacturers are implementing AI-driven solutions to customize production lines, allowing for efficient shifts between different product configurations. This trend reflects the industry's focus on meeting consumer expectations for tailor-made products in an increasingly competitive market.
Supply chain optimization is another notable trend fueled by AI in manufacturing. Manufacturers are leveraging AI algorithms for demand forecasting, inventory management, and logistics optimization. By analyzing vast datasets in real-time, AI enables manufacturers to make more accurate predictions and optimize supply chain processes. This trend addresses the challenges of global supply chain complexities, enhancing responsiveness to market fluctuations and improving overall operational efficiency.
Collaborative robots, or cobots, are increasingly becoming a trend in the manufacturing sector. These robots work alongside human workers, enhancing efficiency and safety in various manufacturing tasks. AI integration allows cobots to adapt to changing production requirements, collaborate seamlessly with human workers, and contribute to increased productivity. The trend emphasizes a harmonious coexistence of human and machine capabilities on the manufacturing floor, fostering a collaborative and innovative work environment.
Quality control and defect detection are witnessing advancements through AI-driven technologies. Machine vision systems equipped with AI algorithms enable 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 trend reflects the industry's commitment to achieving higher levels of precision and quality assurance through AI technologies, ultimately leading to improved customer satisfaction.
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Data security and privacy considerations are emerging as critical trends in the AI in manufacturing market. As manufacturers accumulate and analyze vast amounts of sensitive data for AI-driven insights, securing this information becomes paramount. The trend involves implementing robust cybersecurity measures, ensuring compliance with data protection regulations, and fostering a culture of responsible data handling. This reflects the industry's acknowledgment of the importance of safeguarding sensitive information in the age of AI-driven manufacturing.
The convergence of AI with other emerging technologies, such as the Internet of Things (IoT) and edge computing, is a trend reshaping manufacturing processes. AI is utilized to analyze data generated by interconnected devices, enabling real-time decision-making at the edge of the network. This trend enhances the efficiency of data processing, reduces latency, and supports the seamless integration of AI into various manufacturing applications.
Covered Aspects:
| Report Attribute/Metric | Details |
|---|---|
| Market Opportunities | 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. |
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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