AI technology is making a way in the manufacturing sector, with its varying applications in every manufacturing industry, ranging from automotive to pharmaceuticals. The machine learning technology and pattern-recognition software act as the key to transforming manual factories units into AI manufacturing units. In the manufacturing sector, AI assists in organizing data, visual inspection, predictive maintenance, quality control, shortening design time, reducing materials waste, improving production reuse, assembling, and transforming predictive analysis in the manufacturing tasks. The global AI in manufacturing market was valued at nearly $2.0 billion in 2020 and is expected to grow at a robust pace over the forecast period.
A significant rise in big data has contributed to the adoption of big data analytics in manufacturing. With the growing digitalization across the globe, big data is on a continuous rise. Big data is quickly becoming a significant element of the fourth generation of ERP (Enterprise Resource Planning) technology. Big data’s ability to engage data, people, and processes is assisting in creating a new era for manufacturing. Further, the rising demand for human-robot collaboration in the manufacturing sector for overall cost reduction is substantially driving the market. Robots are playing an imperative role in the manufacturing sector. The rise of AI industrial robots witnessed a hefty expansion in developed countries and certainly seems to be inevitable, being driven by a range of production demands, including continued adaptation to the proliferation of automation and the IoT, increased resource efficiency, and the need for safer and more simplified robotic technologies to work in collaboration with humans.
Predictive maintenance application dominates the market while quality control application is growing rapidly
Maintenance is a key area that drives major cost savings and production value in every manufacturing sector. AI and advanced analytics can play a powerful tool for predictive maintenance. It refers to analyzing attributes of components along with production parameters at different timeframes, with which the system gains insights about when a critical failure is expected to occur. AI predictive maintenance enables manufacturers to save a large number of resources by reducing downtime to a minimum. Moreover, AI-based quality control applications have been gaining traction in recent years. AI quality control and reclamation are finding applications in the automotive industry. For instance, the optical inspection solutions are developed by Isra Vision, which makes it possible to automatically detect surface irregularities, whatever color or type of paint is used. Further, the application of AI in supply chain related-tasks holds great potential for boosting bottom-line and top-line manufacturing value. AI can revolutionize the optimization and agility of supply chain decision-making. The intelligence in shipping has become a center-stage kind of focus within SCM in recent years. Faster and accurate shipping possibly reduces lead times along with transportation expenses, reduces labor costs, and, most important of all, it widens the gap between competitors.
Global AI in Manufacturing Market: Regional Outlook
North America is leading the global AI in manufacturing market in 2022. The market growth is attributed to the contribution of the major economies, including the US and Canada. The market in the US is growing due to the rising manufacturing sector coupled with the government efforts to promote the implementation of AI. For instance, in February 2019, the US president signed an executive order for the American AI initiative. Further, there is a rising need to meet the increasing demand for high efficiency in the manufacturing sector, further strengthening the market share in the region. Moreover, Europe is expected to contribute significantly to the global market on account of factors such as the presence of major market players, well-developed automotive, industrial equipment, and pharmaceutical industries, fast adoption of new technology, and significant adoption of industrial robots. Additionally, the Asia Pacific region is expected to observe the fastest growth rate due to the increasing R&D and investments by big pharmaceutical companies in life science research coupled with harnessing innovation, which spurs the growth of AI-based manufacturing in the healthcare industry. Further, the advancement in consumer electronics, growing automotive production, and the significant growth of major economies, such as China, India, Japan, and South Korea, will further boost the growth of AI in manufacturing in these industries.
Competition Landscape and Key Market Developments
The global AI in manufacturing market is fragmented in nature with the presence of various players operating in the market. Some of the prominent players that contribute significantly to the market growth include NVIDIA Corp., IBM Corp., Intel Corp., Siemens AG, General Electric Company, Alphabet Inc. (Google LLC), Microsoft Corp., Micron Technology Inc., Amazon.com Inc. (Amazon Web Services Inc.), Oracle Corp., SAP SE, Cisco Systems Inc., Mitsubishi Electric Corp., Salesforce Inc., and SparkCognition among others. These players adopt various strategies in order to reinforce their market share and gain a competitive edge over other competitors in the market. Acquisitions and product launches are among the key strategies adopted by major industry players. For instance,
- In January 2022, the GeForce RTX 3050 product was launched by NVIDIA Corp. GeForce RTX 3050 product brings next-generation graphics and AI to games. Ray tracing technology is equipped in the RTX line-up for real-time, cinematic-quality rendering. Moreover, features such as deep learning super sampling and boosts frame rate are also equipped in this product.
- In December 2021, IBM Z and Cloud Modernization Center digital platforms were launched by IBM. These platforms offers a wide range of tools and resources, as well as ecosystem partners, which enable users to accelerate the modernization of data, processes, and applications in an open hybrid cloud architecture.
- In November 2021, Mitsubishi Electric Corp. and the National Institute of Advanced Industrial Science and Technology (AIST) announced that they have developed an AI technology that predicts changes during automated manufacturing processes and then makes real-time adjustments in the factory automation (FA) equipment, such as motion speeds, etc., during operation. In addition to eliminating the need for time-consuming manual adjustments, the AI estimates the confidence level of inferences regarding factors such as machining error and then controls the FA equipment based on suitable levels of confidence. The technology is expected to lead to more stable, reliable, and productive operations, particularly in agile manufacturing.
Key Market Segmentation
RationalStat has segmented the global AI in manufacturing market on the basis of component, deployment model, technology, application, end-user, and region.
- By Component
- By Deployment Model
- By Technology
- Machine Learning
- Natural Language Processing
- Context-Aware Computing
- Computer Vision
- By Application
- Predictive Maintenance and Machinery Inspection
- Inventory Optimization
- Production Planning
- Quality Control
- Cyber Security
- Industrial Robots
- Others (Field Services)
- By End-User
- Food & Beverages
- Healthcare & Pharmaceutical
- Semiconductor & Electronics
- Energy & Power
- Others (Textile, Aerospace & Defense)
- By Region
- North America
- Latin America
- Rest of Latin America
- Western Europe
- Rest of Western Europe
- Eastern Europe
- Rest of Eastern Europe
- Asia Pacific
- South Korea
- ASEAN (Indonesia, Vietnam, Malaysia, etc.)
- Rest of Asia Pacific
- Middle East & Africa
- South Africa
- Rest of the Middle East & Africa
- North America
RationalStat has developed a state-of-the-art research methodology to crunch numbers and provide the best possible real-time insights to clients. We combine a varied range of industry experience, data analytics, and experts’ viewpoint to create a research methodology for market sizing and forecasting.
RationalStat combines a mix of secondary sources as well as primary research to assess the market size and develop a forecast. Key steps involved in accurately deriving the market numbers are:
- Defining the problem by understanding the type of market and data required by the client.
- Data gathering and collection through relevant paid databases, publicly available sources, company reports, annual reports, surveys, and interviews.
- Formulating a hypothesis to create market numbers, forecast, influencing factors, and their relevance.
- Evaluating and analyzing the data by referring to data sources utilized and leveraged.
- Validating, interpreting, and finalizing the data by combining the details gathered from primary and secondary sources with the help of experienced analysts.
- Annual reports, company filings, investor presentations, product catalogs, industry associations, and company documents
- Industry and market-related documents available in the public domain
- Paid database including Bloomberg, Factiva, S&P Capital IQ, FactSet, Refinitiv Eikon, ICIS, EUWID, Thomson Reuters, among others
- Whitepapers, research papers, and industry blogs.
Why Buy this Report?
The report is intended for AI in manufacturing service providers, automotive organizations, consumer electronics manufacturers, packaging companies, food & beverages manufacturing companies, government organizations, market educational organizations, regulatory agencies, and market research firms, among others. The report provides an in-depth analysis of AI in manufacturing market size, consumption pattern, ongoing market trends and challenges, and future market opportunities. The report will serve as a source for a 360-degree analysis of the market thoroughly delivering insights to clients to find the right answers to their business questions.
Frequently Asked Questions (FAQs)
The expected CAGR of the global AI in Manufacturing market is over 40% during 2022-2028.
The leading region in the global AI in Manufacturing Market is Asia Pacific in 2022.
The global AI in Manufacturing market is estimated at around US$ 2.3 billion in 2022.
A substantial increase in big data is one of the key trends in the market.
Leading companies operating in the Global AI in Manufacturing Market are NVIDIA Corp., IBM Corp., Intel Corp., Siemens AG, General Electric Company, Alphabet Inc. (Google LLC), Microsoft Corp.