Artificial Intelligence (AI) in Manufacturing Market Size By Component (Hardware [Processor {Central Processing Unit (CPU), Graphics Processing Unit (GPU), Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC)}, Memory], Solution [Software, AI Platform, Application Program Interface(API)], Services [Managed Services, Professional Services), By Technology (Machine Learning (ML), Computer Vision, Context Awareness, Natural Language Processing (NLP)), By Application (Quality Management, Predictive Maintenance & Machinery Inspection, Material Movement, Production Planning, Cybersecurity, Field Services), By End-use (Semiconductor & Electronics, Energy & Power, Pharmaceutical & Chemical, Automobile, Heavy Metals & Machine Manufacturing, Food & Beverages) Industry Analysis Report, Regional Outlook, Growth Potential, Competitive Market Share & Forecast, 2019 – 2025

Published Date: Feb 2019  |  Report ID: GMI3124  |  Authors: Ankita Bhutani, Preeti Wadhwani

Report Format: PDF   |   Pages: 300   |   Base Year: 2018




Summary Table of Contents Industry Coverage Methodology

Industry Trends

Artificial Intelligence in Manufacturing Market size estimated at over USD 1 billion in 2018 and is anticipated to grow at a CAGR of more than 40% from 2019 to 2025.
 

U.S. Artificial Intelligence in Manufacturing Market Revenue, By Technology, 2018 & 2025

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Increasing venture capital investments in AI are fostering growth of artificial intelligence in manufacturing market. In 2016, the total external investment in AI was anticipated to be between approximately USD 12 billion. The number of deals in the market space witnessed a five-year high last year, from 160 deals in 2012 to 658 deals in 2016. The value of deals also increased significantly in 2016 by over 60%. Investments in the technology are led by tech giants and digital native companies including Google, Nvidia, and Intel. They are collectively investing billions of dollars in a wide variety of AI-based applications ranging from machine learning to robotics, virtual autonomous vehicles, assistance technology, and natural language to computer vision.
 

The exponential growth in digital data is driving growth of artificial intelligence (AI) in manufacturing market. It is estimated that by 2020, approximately 1.7 megabytes of new data will be created every second. It is further estimated to grow at an annual growth rate of 40% over the next 10 years. This growth is credited to the increasing adoption of big data technologies and IoT devices along with the rise in popularity of cloud platforms among enterprises. This is encouraging the adoption of the advance data analytics solutions among the manufacturers to process the data and extract actionable insights.
 

However, the adoption of the technology in the manufacturing sector is still in the nascent stage due to the presence of several challenges in implementation of the AI technology in the industries. The complex nature of the industrial data and lack of skilled IT workforce in the industrial plants is hindering the adoption of AI in manufacturing market.
 

Artificial Intelligence (AI) in Manufacturing Market Report Coverage
Report Coverage Details
Base Year: 2018
Historical Data for: 2014 to 2018 Forecast Period: 2019 to 2025
Pages: 300 Tables, Charts & Figures: 611
Geographies covered (19): U.S., Canada, UK, Germany, France, Italy, Spain, Netherlands, Australia, China, India, Japan, South Korea, Taiwan, Brazil, Mexico, UAE, Israel, South Africa
Segments covered: Component, Technology, Application, End-use and Region
Companies covered (19): Advanced Micro Devices, Inc., Amazon Web Services, Inc., Canvas Analytics, Fallonry, General Vision, Google LLC, Graphcore, IBM Corporation, Intel Corporation, Landing AI, Micriosoft Corporation, Nvidia Corporation, Oracle Corporation, Progress Software Coroporation, Qualcomm Incorporated, SAP SE, Sight Machine, Ubtech Robotics, Vicarious,

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Artificial Intelligence (AI) in Manufacturing Market, By Component

Hardware is leading the artificial intelligence in manufacturing market over 57% industry share in 2018. The growth of the market is driven by the increasing demand for the AI processors among the industry sectors. GPUs account for more than 45% share in 2018 in the AI processors market and estimated to dominate the market during the forecast period. Its heavy compute capabilities are encouraging its demand among the organizations. Moreover, the increasing need for enhanced visual content and high memory graphic is augmenting its demand in the market.
 

Germany AI in Manufacturing Market Share, By Processors, 2018
Germany AI in Manufacturing Market Share, By Processors, 2018

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Software segment is projected to grow at a CAGR of more than 48% over the timeline. The increasing demand of the customized AI powered solutions among the manufactures is accelerating the AI in manufacturing market growth. By deploying the right combination of the AI solutions, manufacturers can increase their operational efficiency, accelerate process, gain flexibility, and can optimize the operations. It has been estimated that the AI can reduce the operational cost by 20% by increasing the workforce productivity by more than 70%. It can also assist manufactures in increasing their sales by enabling manufacturers to develop customized products for the customers.
 

Services are estimated to grow at CAGR of over 54% during the forecast period. The increasing integration and deployment of AI solutions is driving the AI in manufacturing market. The lack of skilled professional among the industry sector along with the growing demand for the third-party service providers is augmenting the market growth. Moreover, the growing need among the manufactures to focus on the core business competencies is accelerating the service market.
 

Artificial Intelligence in Manufacturing Market, By Technology

Machine learning held more than 47% share in the artificial intelligence in manufacturing market. The technology is used in the manufacturing industry due to rising needs to ensure quality management at every stage of the manufacturing process. ML predicts the quality of the product from the early stages of production with a high degree of precision. This detects minuscule deviations from ideal product standards and its self-learning algorithms allow it to detect errors, which were previously unknown.
 

The context awareness technology is predicted to grow at a CAGR of over 41% during the projected timeframe. The need for highly flexible manufacturing processes is promoting the adoption of context awareness systems. The technology enhances the availability and efficiency of modern production systems simultaneously. It enables self-adaptation to support fluctuations in process parameters aimed at increasing flexibility and efficiency. It also allows effective knowledge acquisition & sharing to support maintenance, increasing the availability of production systems.
 

AI in Manufacturing Market, By Application

The quality management application segment is estimated to account for over 20% stake in the AI in manufacturing market. Rising competition in the manufacturing landscape is promoting AI technology as a key differentiator to ensure quality control. The lack of quality poses major risks to the performance and competitive position of the company in the market, leading to high costs to the company. This is encouraging manufacturing companies to adopt deep learning & machine learning platforms to reinforce their existing infrastructure and proactivity identify mistakes & errors that can weaken the production chain and the quality of products.
 

The material movement market is projected to grow at a CAGR of 43% over the forecast timeframe. As a skilled workforce is becoming increasingly difficult to recruit and retain, companies are shifting toward AI-based machine movement solutions to manage their labor challenges while ensuring productivity and profitability.

 

Artificial Intelligence (AI) in Manufacturing Market, By End-use

The energy & power end-use segment for artificial intelligence (AI) in manufacturing market is expected to grow at a CAGR of over 41.2% during the forecast period. Companies are investing in AI technology due to its ability to learn and adapt to changing environments. The technology will enable power generation companies to create predictions for the energy demand and its generation based on weather forecast. This will reduce the dependence on backup mechanisms for predicting & managing fluctuations in the production. The speed and the complex nature of the task are encouraging the use of advanced AI technologies in the manufacturing sector.

 

The heavy metal & machinery industry for artificial intelligence in manufacturing market is expected to grow at a CAGR of over 43% during the projected timespan. The players operating in the heavy metal & machinery industry are using AI technology to optimize their raw material consumption, improve melt costs, and ensure quality finished products. It allows manufacturers to build accurate models based on previous raw material consumption. It reduces the quantity of raw materials consumed, enabling significant cost savings when raw materials used are precious metals such as gold, zinc, or copper.
 

Artificial Intelligence in Manufacturing Market, By Region

Asia Pacific dominated the artificial intelligence in manufacturing market with share of over 43% in 2018 and is anticipated to resonate the trend during the forecast period. The market growth is credited to the highly developed manufacturing plants in the countries such as Japan, South Korea, and China. The rapid adoption of the industry 4.0 revolution in the region also promotes the adoption of AI solutions. Moreover, the increasing investment in the AI technology in the emerging economies such as India and China are driving the market growth.
 

North America’s AI in manufacturing market will grow at a CAGR of 43% over the projected timeline. The increasing investments by companies to modernize their manufacturing facilities are driving growth of the market. The early adoption of various advanced technology, such as IoT, is also driving the penetration of AI-enabled manufacturing systems. In addition, efforts by the government to bring back manufacturing operations to North America are supporting the use of AI technologies in the manufacturing sector.

 

Competitive Market Share

Multinational players, such as NVIDIA, Intel, and IBM, are investing heavily in developing new and high-performance enterprise AI solutions. The major players in the artificial intelligence in manufacturing market are forming partnerships with various technology players to develop new product offerings. With the increasing adoption of industry 4.0 manufacturing technologies, the demand for AI chips has grown significantly driven by traditional chipmakers to invest in enterprise solutions. They are also acquiring new start-ups working on machine learning to solidify their position in the market. For instance, in August 2016, Intel acquired Nervana Systems, a deep learning startup. This acquisition is aimed at expanding its AI-based product capabilities to solidify Intel’s position in the artificial intelligence in manufacturing market.

 

Industry Background  

AI has emerged as the most disruptive technology in the last five years. The technology is transforming business processes and enabling the development of new business models across the business sector. Recent advancements in hardware capabilities, platforms, applications, and new intelligent algorithms have accelerated the commercialization of this technology and driven its application across various industry sectors.
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The manufacturing sector is also following the footprints of the other industry verticals and embracing AI technology. As the adoption of Industry 4.0 is increasing across the industry and the manufacturing sector is moving toward digital channels, AI can play a vital role in this transformation and automation of industrial processes. AI technology can significantly increase the efficiency of manufacturing processes and simplify many complex processes and machine-to-machine interactions spanning products & assets within the factories and across the international supply chain.


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