Artificial Intelligence in Manufacturing Market Analysis | 2023-2029

Market Insights

The artificial intelligence in manufacturing market was estimated at USD 2.14 billion in 2022 and is likely to grow at a CAGR of 42.0% during 2023-2029 to reach USD 24.90 billion in 2029.

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Market Dynamics

Introduction

Artificial Intelligence (AI) in manufacturing refers to the use of AI technologies to enhance manufacturing processes and optimize production. AI can be used to automate tasks, analyze data, and improve decision-making processes. For instance, AI can be used to optimize manufacturing schedules, predict maintenance needs, and improve product quality. Machine learning algorithms can analyze large amounts of data and identify patterns of behavior, enabling manufacturers to predict equipment failures and schedule maintenance activities proactively. Additionally, AI can be used to automate quality control processes, reducing the risk of defective products and increasing production efficiency. 

Market Drivers 

Emerging IIoT and Technological Automation: The Industrial Internet of Things (IIoT) improves efficiency, productivity, and innovation in industrial processes by transforming device data into instructions using AI systems that learn human behavior through deep learning, context awareness, and natural language processing.

Time-Efficient and Enhanced Growth: General Motors Company has integrated industrial IoT devices into its automobile manufacturing plant to improve car body painting quality. AI-based systems work continuously without errors, enhancing manufacturing efficiency and business growth, compared to traditional methods.

Monitoring Facilities: IIoTs in plants monitor humidity levels and transmit data to AI systems, triggering processes like engine inspections and electrical testing. Siemens uses AI to optimize gas turbines, monitor smart grids, and maintain industrial facilities. IIoT solutions minimize toxic nitrogen oxide emissions and enhance productivity and efficiency in the manufacturing industry.

Market Challenge: Dearth of skilled workforce

Requirement of a Skilled Workforce: Companies developing complex AI systems require a skilled workforce with specific skills in cognitive computing, machine learning, machine intelligence, deep learning, and image recognition. Emerging economies face a shortage of skilled workforce compared to advanced AI-advanced countries like the US, UK, Japan, and Germany.

Continuous Requirement of Skill Development: The transition to AI-enabled factory floors requires manufacturers to re-skill their workforce and develop AI systems. Integrating AI into existing systems is challenging due to extensive data processing and potential system failure.

Lack of Professional Standards and Certification: The growth of AI is hindered by a lack of professional standards and certifications in AI/ML technologies, and AI service providers face challenges in deploying and servicing their solutions at customers' sites.

Key Players

The following are the key players in the artificial intelligence in manufacturing market:

• Aibrain
• Amazon Web Services (Aws)
• Aquant
• Bright Machines
• Cisco Systems
• Flutura
• General Electric (GE) Company
• Google
• General Vision
• IBM
• Intel
• Microsoft Corporation
• Micron Technology
• Mitsubishi Electric
• NVIDIA
• Oracle
• Progress Software Corporation (Datarpm)
• Rethink Robotics GmbH
• Rockwell Automation
• Siemens
• Sight Machine
• SAP
• SparkCognition
• Ubtech Robotics
• Vicarious

Note: The above list does not necessarily include all the top players in the market.

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Segment Analysis

By Industry Type

"Semiconductor and Electronics industry to witness the highest CAGR over the forecast period".

The semiconductor and electronics industry leverages AI for several functions, including production planning, quality control, and material movement. The integration of AI-based solutions is expected to optimize production costs, facilitate technology implementation, and enhance component integration for manufacturers.

Due to the complexity of the electronics equipment manufacturing process, real-time manufacturing-related data is crucial for efficient planning and maintenance of the production process. AI solutions help companies in the semiconductor and electronics equipment industry analyze data collected from all points, leading to improved decision-making and significant growth potential for the manufacturing process.

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By Application Type

"Growing adoption of AI-powered quality control systems to drive market growth".

AI-based quality control applications enable plant operators to swiftly detect variations in product properties during production. These applications rely on 3D and 2D data collected by a laser-based scanning system that converts the data into digital images. These images are used as input to an artificial neural network, which assigns a predefined class to the sample.

This quality control system helps plant operators verify product quality, and if a problem arises, the AI-based system removes the object from the conveyor belt. The pharmaceutical, food and beverage, and semiconductor industries widely use this AI-based quality control system. Machine learning, computer vision, and context-aware computing technologies are predominantly utilized in quality control applications within manufacturing plants.

Regional Analysis

"Japan is to witness high growth in adopting AI technologies in manufacturing".

Japan has initiated the Industrial Value Chain Initiative to investigate cutting-edge technologies. Major electric, IT, machinery, and automobile companies such as Mitsubishi Electric, Fujitsu, Nissan Motor, and Panasonic are participating in this initiative. Connected machines and transport robots have been utilized on shop floors for a considerable period, with Toyota being one such example.

Additionally, the ministries in Japan have been promoting IT projects within the country. Japan has a strong presence in information and communication technology, manufacturing processes, automotive and machinery industries, automation and robotics, and electronic components.

In addition, Japanese companies Fujitsu and Hitachi are recognized providers of big data and cybersecurity solutions to a wide range of sectors, including agriculture, manufacturing, and services. Consequently, the implementation of AI in Japanese manufacturing industries has been significant. Japan has formulated a phased development plan for AI aimed at developing and deploying data-driven AI in various fields and establishing an AI ecosystem by connecting different areas.

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Recent Developments

• In February 2023, Mitsubishi Electric launched a new AI solution that aspires to address skilled labor shortages on manufacturing lines.
• In December 2022, IBM and Rapidus entered into a strategic partnership to build advanced semiconductor technology and ecosystem in Japan and support the country's initiatives to become a global leader in semiconductor research, development, and manufacturing.
• In October 2022, Sight Machine, a developer of the data foundation for manufacturing, launched Sight Machine Blueprint, a tool developed in collaboration with Microsoft and NVIDIA that provides manufacturers with high-speed, automated data labeling, mapping data tags to plant assets and the context they require to interpret their plant data.
• In June 2022, Siemens and NVIDIA partnered to enable the industrial metaverse. The partnership empowers the manufacturing industry with immersive experiences across the lifecycle from design through operation.

Research Methodology

• This strategic assessment report, from Stratview Research, provides a comprehensive analysis that reflects today’s artificial intelligence in manufacturing market realities and future market possibilities for the forecast period.
• The report segments and analyzes the market in the most detailed manner to provide a panoramic view of the market.
• The vital data/information provided in the report can play a crucial role for market participants as well as investors in the identification of the low-hanging fruits available in the market as well as to formulate growth strategies to expedite their growth process.
• This report offers high-quality insights and is the outcome of a detailed research methodology comprising extensive secondary research, rigorous primary interviews with industry stakeholders, and validation and triangulation with Stratview Research’s internal database and statistical tools.
• More than 1,000 authenticated secondary sources, such as company annual reports, fact books, press releases, journals, investor presentations, white papers, patents, and articles, have been leveraged to gather the data.
• We conducted more than 15 detailed primary interviews with market players across the value chain in all four regions and industry experts to obtain both qualitative and quantitative insights.

Report Features

This report provides market intelligence in the most comprehensive way. The report structure has been kept such that it offers maximum business value. It provides critical insights into market dynamics and will enable strategic decision-making for existing market players as well as those willing to enter the market. The following are the key features of the report:

• Market structure: Overview, industry life cycle analysis, supply chain analysis.
• Market environment analysis: Growth drivers and constraints, Porter’s five forces analysis, SWOT analysis.
• Market trend and forecast analysis.
• Market segment trend and forecast.
• Competitive landscape and dynamics: Market share, Service portfolio, New Product Launches, etc.
• COVID-19 impact and its recovery curve
• Attractive market segments and associated growth opportunities.
• Emerging trends.
• Strategic growth opportunities for the existing and new players.
• Key success factors.

Market Segmentation

This report studies the market covering 12 years of trend and forecast. The report provides detailed insights into the market dynamics to enable informed business decision-making and growth strategy formulation based on the opportunities present in the market

The artificial intelligence in manufacturing market is segmented into the following categories

By Offering Type

• Hardware
• Software
• Services

By Technology Type 

• Machine Learning
• Natural Language Processing
• Context-aware Computing
• Computer Vision

By Application Type 

• Predictive Maintenance and Machinery Inspection
• Inventory Optimization
• Production Planning
• Field Services
• Quality Control
• Cybersecurity
• Industrial Robots
• Reclamation

By Industry Type 

• Automotive
• Energy and Power
• Semiconductor & Electronics
• Pharmaceutical
• Heavy Metals and Machine Manufacturing
• Food and Beverage

Customization Options

With this detailed report, Stratview Research offers one of the following free customization options to our respectable clients:

Company Profiling

• Detailed profiling of additional market players (up to three players)
• SWOT analysis of key players (up to three players)

Competitive Benchmarking

• Benchmarking of key players on the following parameters: product portfolio, geographical reach, regional presence, and strategic alliances

Custom Research: Stratview research offers custom research services across the sectors. In case of any custom research requirement related to market assessment, competitive benchmarking, sourcing and procurement, target screening, and others, please send your inquiry to sales@Stratviewresearch.com