The Artificial Intelligence (AI) in Manufacturing Market is expected to be valued at USD XX billion in 2020 and is likely to reach USD 16.7 billion by 2027; it is expected to grow at a CAGR of 57.2% during the forecast […]
The Artificial Intelligence (AI) in Manufacturing Market is expected to be valued at USD XX billion in 2020 and is likely to reach USD 16.7 billion by 2027; it is expected to grow at a CAGR of 57.2% during the forecast period.
Latest added Artificial Intelligence (AI) in Manufacturing Market research study by MarketDigits offers detailed product outlook and elaborates market review till 2027. The market Study is segmented by key regions that is accelerating the marketization. At present, the market is sharping its presence and some of the key players in the study are NVIDIA Corporation, IBM Corporation, Alphabet, Google, Microsoft Corporation, Intel Corporation, Siemens AG. The study is a perfect mix of qualitative and quantitative Market data collected and validated majorly through primary data and secondary sources.
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This report studies the Artificial Intelligence (AI) in Manufacturing Market size, industry status and forecast, competition landscape and growth opportunity. This research report categorizes the Artificial Intelligence (AI) in Manufacturing Market by companies, region, type and end-use industry.
Scroll down 100s of data Tables, charts and graphs spread through Pages and in-depth Table of Content on “Artificial Intelligence (AI) in Manufacturing Market, By Offering (Hardware, Software, Services), Technology (Machine Learning, Natural Language Processing), Application, Industry Vertical and Geography – Global Forecast to 2027”. Early buyers will get 10% customization on study.
To Avail deep insights of Artificial Intelligence (AI) in Manufacturing Market Size, competition landscape is provided i.e. Revenue Analysis (M $US) by Company (2018-2020), Segment Revenue Market Share (%) by Players (2018-2020) and further a qualitative analysis is made towards market concentration rate, product/service differences, new entrants and the technological trends in future.
Unlock new opportunities in Artificial Intelligence (AI) in Manufacturing Market; the latest release from MarketDigits highlights the key market trends significant to the growth prospects, Let us know if any specific players or list of players needs to consider to gain better insights.
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The major drivers for the market are the increasing number of large and complex datasets (often known as big data), evolving Industrial IoT and automation, improving computing power, and increasing venture capital investments.
COVID-19 Impact on the Global AI in Manufacturing Market
The ongoing COVID-19 pandemic has caused disruptions in economies. It is likely to cause supply chain mayhem and eventually force companies and entire industries to rethink and adapt to the global supply chain model. Many manufacturing companies have halted their production, which has collaterally damaged the supply chain and the industry. The industries have started to restructure their business model for 2020, and many SMEs and large manufacturing plants have halted/postponed any new technology upgrade in their factories in order to recover from the losses caused by the lockdown and economic slowdown.
The growth in the adoption of AI solutions is completely dependent on the growth of manufacturing units. However, in the current situation, manufacturing ecosystems have been disrupted, and thus, the growth of AI solutions will also get affected negatively in such industries. On the other hand, industries such as pharmaceuticals are expected to witness a moderate impact. Many factors have contributed to the disruptions in manufacturing industries. Broadly, three major factors are disrupting the manufacturing industries, namely, supply chain disruption, shutdown of manufacturing units, and decrease in demand amidst lockdown in many countries.
AI in Manufacturing Market Dynamics
Driver: Evolution of industrial IoT and automation
Industrial Internet of Things (IIoT) plays a key role in the adoption of AI-based technology in the manufacturing sector. Industrial IoT makes industrial processes efficient, productive, and innovative by enabling an architecture that provides real-time information about operational and business systems. The data that is derived from the IoTs need to be converted into instructions that would instruct the machines to perform specific activities. These instructions designed by an AI system learn human behavior through deep learning, context awareness, and natural language processing (NLP). The AI-based system takes lesser time and can work continuously without error. As a result, manufacturing efficiency improves, which further helps in business growth.
Restraint: Reluctance among manufacturers to adopt AI-based technologies
AI technologies offer manufacturers the tools that would help them in a better predictive maintenance and machinery inspection process. However, manufacturers are reluctant to adopt new technologies or AI-based solutions in their costly machines or equipment. Any mismanagement could add to the costs. Furthermore, many manufacturers are doubtful about the capabilities of AI-based solutions in terms of the accuracy of the maintenance and inspection processes. Considering these factors, it is slightly difficult to convince the manufacturers and make them understand that AI-based solutions are cost-effective, efficient, and safe. However, manufacturers are now increasingly accepting the potential benefits of AI-based solutions and the spectrum of applications they serve.
Opportunities: Adoption of automation technologies to curb effects of COVID-19
Adoption of automation technologies such as artificial intelligence, robotics, and the Industrial Internet of Things is among the most critical factors for restarting the business operations of the manufacturing sector during this global pandemic. Large-scale lockdowns, shortage of labor force, and supply chain disruptions are likely to drive the automation needs across the manufacturing sector. AI-based solutions could help manufacturers to digitally transform operations (such as autonomous material movement using industrial robots) and make prompt data-driven decisions. In addition, AI can play a crucial role in automating several stages of manufacturing and limit human involvement.
Challenges: Limited skilled workforce
For developing, managing, and implementing AI systems that are complex in nature, companies require a workforce with certain skill sets, i.e., personnel dealing with AI systems should be aware of technologies such as cognitive computing, ML and machine intelligence, deep learning, and image recognition. In addition, the integration of AI solutions into existing systems is a difficult task requiring extensive data processing for replicating a human brain behavior. Even a minor error can result in system failure or can adversely affect the desired result. Furthermore, the absence of professional standards and certifications in AI/ML technologies is restraining the growth of AI. Additionally, AI service providers are facing challenges with regard to deploying/servicing their solutions at their customers’ sites. This is because of the lack of technology awareness and expertise.
AI in manufacturing market for hardware segment is expected to dominate in the APAC region
Most of the AI hardware manufacturers have been in the business of providing the same hardware components for other technologies such as connected cars, machine vision cameras, and IoT for a long time. This will enable the companies to transfer the technology easily and accordingly develop the AI hardware. Moreover, the increasing participation of startups in AI hardware is complementing the growth of the hardware segment. A large number of manufacturing plants, huge presence of hardware manufacturers, and high adoption rate of robotics in China, Japan, and South Korea are driving the growth of the AI in manufacturing market in the APAC region
Predictive maintenance and machinery inspection application is projected to hold the largest share during forecast period
The predictive maintenance and machinery inspection application expected to hold the largest share of the AI in manufacturing market from 2020-2027. Extensive use of computer vision cameras in machinery inspection, adoption of Industrial Internet of Things (IIoT), and use of big data in the manufacturing industry are the factors driving the growth ofmarket for the predictive maintenance and machinery inspection application. The increasing demand for reducing the operational costs and machine downtime is also supplementing the growth of predictive maintenance and machinery inspection application in industries.
Deep learning technology expected to be extensively adopted during the forecast period
The market for deep learning technology is estimated to witness the highest growth throughout the forecast period. Growing adoption of deep learning in various manufacturing applications, rapid adoption of robotics in the manufacturing industry, and the huge volume of data generated by the computer vision technology, and big data are driving the growth of the AI in manufacturing market for deep learning technology.
The adoption of AI based manufacturing technology was significant in the APAC region
APAC accounted for the largest share of the AI in manufacturing market. The presence of a large number of manufacturing companies in China and Japan, along with the strong presence of automobile and electronics and semiconductor companies, is driving the growth of market in APAC. Moreover, the high adoption of industrial robots is expected to play a vital role in the growth of the said market in APAC.
Due the COVID-19 pandemic, lockdown has been implemented in APAC, especially in China, which has led to supply chain disruptions, which have eventually affected the global economy. China was successful in containing the COVID-19 outbreak in Wuhan by implementing lockdown, and the same model was replicated across other countries in APAC. The decrease in the number of COVID-19 patients in China is slowly leading to normalcy in manufacturing activities. This, in turn, is expected to drive the growth of the AI in manufacturing market in APAC. However, it is expected that this growth will not be as significant as it would have been in the pre-COVID-19 estimates.
AI in manufacturing market is dominated by globally established players such as NVIDIA (US), IBM (US), Intel (US), Siemens (Germany), and General Electric Company (US).
Scope of the report
AI in manufacturing market segmentation:
In this report, the AI in manufacturing market has been segmented into the following categories:
Based on Offering:
- AI Solutions
- AI Platform
- Deployment & Integration
- Support & Maintenance
Based on Technology:
- Machine Learning
- Deep Learning
- Supervised Learning
- Reinforced Learning
- Unsupervised Learning
- Natural Language Processing
- Context-aware Computing
- Computer Vision
Based on Application:
- Predictive Maintenance and Machinery Inspection
- Material Movement
- Production Planning
- Field Services
- Quality Control
- Industrial Robots
Based on Industry:
- Energy and Power
- Heavy Metals and Machine Manufacturing
- Seiconductors and Electronics
- Food & Beverages
Based on Region:
- North America
- Asia Pacific
- Rest of the World (RoW)
- In June 2020, Wipro Limited (India) announced a collaboration with IBM to assist Wipro customers in embarking on a seamless and secure hybrid cloud journey. Through this alliance, Wipro will develop hybrid cloud offerings to help businesses migrate, manage, and transform mission-critical workloads and applications, with security across public or private cloud and on-premises IT environments. Wipro will leverage IBM Cloud offerings and technologies alongside in-house services to develop industry solutions for clients in banking and financial services, energy and utilities, retail, manufacturing, and healthcare space.
- In May 2020, NVIDIA launched two powerful products for its EGX Edge AI platform — the EGX A100 for larger commercial off-the-shelf servers and the tiny EGX Jetson Xavier NX for micro-edge servers — delivering high-performance, secure AI processing at the edge. With the NVIDIA EGX Edge AI platform, hospitals, stores, farms, and factories can carry out real-time processing and protection of massive amounts of data streaming from trillions of edge sensors. The platform makes it possible to securely deploy, manage, and update fleets of servers remotely.
- In February 2020, Micron, together with technology company Continental (Germany), announced plans to enter into a collaboration agreement to explore and adapt Micron’s deep learning accelerator for next-generation machine learning automotive applications. This agreement brings together two world leaders in the automotive and memory markets to advance machine learning to meet the extreme memory requirements of modern vehicles.
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