Global AI in Manufacturing Market Research Report Information By Type By Technology By Deployment By Organization Size By Application Area Forecast Till 2032
제조업용 AI 시장 규모는 2023년 35억 4,460만 달러, 2024년 43억 8,410만 달러에서 예측 기간 동안 29.7%의 연평균 복합 성장률(CAGR)을 나타내고, 2032년 283억 4,360만 달러 규모로 성장할 것으로 예상됩니다.
제조업에서의 AI는 생산량, 효과 및 품질을 향상시키기 위해 AI 기술을 제조 공정에 통합하는 것을 의미합니다. 머신러닝, 컴퓨터 비전, 로봇, 데이터 분석은 프로세스 자동화, 유지보수 요구사항 예측, 공급망 간소화, 품질 관리 보장, 의사결정 강화를 위해 사용됩니다. 제조업체는 AI를 활용하여 비용을 절감하고 가동 중지 시간을 제한하며 보다 적응력이 뛰어나고 반응성이 뛰어난 생산 환경을 구축할 수 있습니다.
지역별 전망
아시아태평양은 2023년 31.2% 시장 점유율로 제조업용 AI 시장을 선도하고 있으며, 2023년 시장 규모는 13억 2,700만 달러로 연평균 31.2% 성장하여 2032년에는 116억 3,950만 달러에 달할 것으로 예상됩니다.
북미도 2023년 큰 비중을 차지할 것으로 보입니다. 미국에서는 정밀 제조에 AI를 통합하여 예지보전과 지능형 자동화를 실현하고 있습니다. 이 기술은 세계 제조 시장에서 미국의 경쟁력을 강화할 뿐만 아니라 이 분야의 큰 발전을 촉진하고 있습니다.
세계 제조업용 인공지능(AI) 시장을 조사했으며, 시장 정의와 개요, 시장 성장에 영향을 미치는 각종 영향요인 분석, 시장 규모 추이 및 예측, 각 부문별/지역별/주요 국가별 분석, 경쟁 환경, 주요 기업 프로파일 등의 정보를 정리하여 전해드립니다.
목차
제1장 주요 요약
제2장 시장 개요
제3장 조사 방법
제4장 시장 역학
- 시장 동향 및 성장에 영향을 미치는 요인
- 성장 촉진요인
- 성장 억제요인
- 기회
- COVID-19의 영향 분석
제5장 시장 요인 분석
- 밸류체인 분석
- Porter의 Five Forces 분석
제6장 세계의 제조업용 AI시장 : 컴포넌트별
제7장 세계의 제조업용 AI시장 : 기술별
- 머신러닝(ML)
- 컴퓨터 비전
- 자연언어처리(NLP)
- 상황 인식 컴퓨팅
- 기계 추론
- 딥러닝
제8장 세계의 제조업용 AI시장 : 전개 형태별
제9장 세계의 제조업용 AI시장 : 조직 규모별
제10장 세계의 제조업용 AI시장 : 응용 분야별
- 개요
- 예지보전 및 기계 검사
- 품질관리 및 검사
- 생산계획 및 관리
- 재고 관리
- 예측 분석
- 로봇 공학 및 자동화
- 에너지 관리
- 공급망 최적화
제11장 세계의 제조업용 AI시장 : 최종사용자 산업별
- 개요
- 자동차
- 일렉트로닉스 및 반도체
- 의약품 및 화학제품
- 식품 및 음료
- 중금속 및 기계
- 에너지 및 유틸리티
- 섬유 및 의류
- 항공우주 및 방위
- 소비재
- 기타
제12장 세계의 제조업용 AI시장 : 지역별
- 개요
- 북미
- 유럽
- 아시아태평양
- 중동 및 아프리카
- 남미
제13장 경쟁 구도
- 기업 점유율 분석
- 경쟁 벤치마킹
- 공개 기업 주식 개요
- 비교 분석 : 주요 기업의 재무 동향
- 주요 전개 및 성장 전략
제14장 기업 개요
- NVIDIA CORPORATION
- IBM CORPORATION
- SIEMENS
- GENERAL ELECTRIC
- INTEL
- MICROSOFT CORPORATION
- ROBERT BOSCH
- AMAZON WEB SERVICES(AMAZON INC.)
- CISCO SYSTEMS, INC.
- ROCKWELL AUTOMATION
LSH
Global AI in Manufacturing Market Research Report Information By Type (Hardware, Software, Services) By Technology (Machine Learning (ML), Computer Vision, Natural Language Processing (NLP), Context-Aware Computing, Machine Reasoning, Deep Learning) By Deployment (On-Cloud and On-Premise) By Organization Size (SMEs and Large Enterprises) By Application Area (Predictive Maintenance and Machinery Inspection, Quality Control and Inspection, Production Planning and Management, Inventory Management Forecast Till 2032
Overview of the Market
In 2023, the manufacturing AI market was estimated to be worth USD 3,544.6 million. With a compound annual growth rate (CAGR) of 29.7% from 2024 to 2032, the AI in Manufacturing market industry is expected to increase from USD 4,384.1 million in 2024 to USD 28,343.6 million by 2032.
The term "AI in Manufacturing" describes how artificial intelligence technologies are incorporated into production procedures to improve output, effectiveness, and quality. To automate processes, forecast maintenance requirements, streamline supply chains, guarantee quality control, and enhance decision-making, machine learning, computer vision, robots, and data analytics are used. Manufacturers may cut expenses, limit downtime, and establish more adaptable and responsive production environments by utilizing AI.
Perspectives on Market Segments
The AI in Manufacturing market is divided into three segments based on type: hardware, software, and services.
Machine Learning (ML), Computer Vision, Natural Language Processing (NLP), Context-Aware Computing, Machine Reasoning, and Deep Learning are the technological segments that make up the market.
The market has been divided into two segments based on deployment: on-premises and on-cloud.
The AI in Manufacturing market is divided into two segments based on the size of the organization: SMEs and large enterprises.
The market for AI in manufacturing has been divided into several segments based on the end-use industry, including automotive, electronics and semiconductors, pharmaceuticals and chemicals, food and beverages, heavy metals and machinery, energy and utilities, textiles and apparel, aerospace and defense, consumer goods, and others. The market has also been divided into application areas, such as predictive maintenance and machinery inspection, quality control and inspection, production planning and management, inventory management, predictive analytics, robotics and automation, energy management, supply chain optimization, and others.
Regional Perspectives
With a 31.2% market share in 2023, Asia-Pacific leads the region in the AI in Manufacturing market. The market was valued at USD 1,327.0 million in 2023 and is expected to rise at a compound annual growth rate (CAGR) of 31.2% to reach USD 11,639.5 million in 2032.
In 2023, North America held a sizable portion of the market. Predictive maintenance and intelligent automation are made possible by the integration of artificial intelligence into precision manufacturing in the United States. In addition to making the nation more competitive in the global manufacturing market, this technology is also propelling significant advancements in the sector.
France, Germany, Italy, the United Kingdom, Russia, and the rest of Europe make up the subsegments of the European AI in Manufacturing market. Because of the government's expanded commitment to build smart factories throughout Europe, the European market is expected to rise steadily throughout the projection period.
The manufacturing sectors in the Middle East and Africa have been expanding significantly. Countries in the Middle East and Africa, including Saudi Arabia, Egypt, and the United Arab Emirates, have been making significant economic investments. This is one of the main elements supporting the region's manufacturing industry.
Additionally, businesses in the Middle East and Africa increase productivity, efficiency, cost savings, and product quality by implementing technology in the manufacturing sector, making them competitive on the global market.
Key Players
NVIDIA, Intel, Siemens, IBM, GE, Microsoft Corporation, Robert Bosch, Amazon Web Services, Cisco Systems Inc., and Rockwell Automation are the market leaders for artificial intelligence in manufacturing.
TABLE OF CONTENTS
1 EXECUTIVE SUMMARY
2 MARKET INTRODUCTION
- 2.1 DEFINITION
- 2.2 SCOPE OF THE STUDY
- 2.3 RESEARCH OBJECTIVE
- 2.4 MARKET STRUCTURE
3 RESEARCH METHODOLOGY
- 3.1 OVERVIEW
- 3.2 DATA FLOW
- 3.2.1 DATA MINING PROCESS
- 3.3 PURCHASED DATABASE:
- 3.4 SECONDARY SOURCES:
- 3.4.1 SECONDARY RESEARCH DATA FLOW:
- 3.5 PRIMARY RESEARCH:
- 3.5.1 PRIMARY RESEARCH DATA FLOW:
- 3.5.2 PRIMARY RESEARCH: NUMBER OF INTERVIEWS CONDUCTED
- 3.6 APPROACHES FOR MARKET SIZE ESTIMATION:
- 3.6.1 CONSUMPTION & NET TRADE APPROACH
- 3.6.2 REVENUE ANALYSIS APPROACH
- 3.7 DATA FORECASTING
- 3.7.1 DATA FORECASTING TYPE
- 3.8 DATA MODELING
- 3.8.1 MICROECONOMIC FACTOR ANALYSIS:
- 3.8.2 DATA MODELING:
4 MARKET DYNAMICS
- 4.1 INTRODUCTION
- 4.2 MARKET TRENDS AND GROWTH AFFECTING FACTORS
- 4.2.1 USING AI/ML/DEEP LEARNING TO BOOST PREDICTION PRECISION
- 4.2.2 ARTIFICIAL INTELLIGENCE IS BEING USED TO AUTOMATE MANUFACTURING PROCESSES
- 4.2.3 GROWTH AFFECTING FACTORS
- 4.3 GROWTH PARAMETERS MAPPED - DRIVERS
- 4.3.1 THE INCREASING ADOPTION OF AI TECHNOLOGIES IN MANUFACTURING
- 4.3.2 THE ADVANCEMENT OF AI ALGORITHMS
- 4.3.3 ENHANCING PRODUCT QUALITY
- 4.4 GROWTH INHIBITORS MAPPED - RESTRAINTS
- 4.4.1 THE HIGH COST OF AI TECHNOLOGY
- 4.4.2 THE LACK OF DATA
- 4.5 OPPORTUNITY
- 4.5.1 DEVELOPING NEW AI-POWERED PRODUCTS AND SERVICES
- 4.5.2 IMPROVING THE EFFICIENCY AND PRODUCTIVITY OF MANUFACTURING PROCESSES
- 4.5.3 CREATING NEW BUSINESS MODELS BASED ON AI
- 4.6 COVID-19 IMPACT ANALYSIS
- 4.6.1 IMPACT ON OVERALL ICT
- 4.6.2 IMPACT ON AI IN MANUFACTURING MARKET
- 4.6.3 IMPACT ON DEMAND OF AI IN MANUFACTURING MARKET
- 4.6.4 IMPACT ON PRICING OF AI IN MANUFACTURING MARKET
5 MARKET FACTOR ANALYSIS
- 5.1 VALUE CHAIN ANALYSIS
- 5.1.1 HARDWARE/SOFTWARE PROVIDER
- 5.1.2 AI IN MANUFACTURING PROVIDERS
- 5.1.3 SELECT THE RIGHT VENDOR OR TOOL
- 5.1.4 END USERS
- 5.2 PORTER'S FIVE FORCES MODEL
- 5.2.1 THREAT OF NEW ENTRANTS
- 5.2.2 BARGAINING POWER OF SUPPLIERS
- 5.2.3 THREAT OF SUBSTITUTES
- 5.2.4 BARGAINING POWER OF BUYERS
- 5.2.5 INTENSITY OF RIVALRY
6 GLOBAL AI IN MANUFACTURING, BY COMPONENT
- 6.1 OVERVIEW
- 6.2 HARDWARE
- 6.3 SOFTWARE
- 6.4 SERVICES
7 GLOBAL AI IN MANUFACTURING, BY TECHNOLOGY
- 7.1 INTRODUCTION
- 7.2 MACHINE LEARNING (ML)
- 7.3 COMPUTER VISION
- 7.4 NATURAL LANGUAGE PROCESSING (NLP)
- 7.5 CONTEXT AWARE COMPUTING
- 7.6 MACHINE REASONING
- 7.7 DEEP LEARNING
8 GLOBAL AI IN MANUFACTURING, BY DEPLOYMENT TYPE
- 8.1 OVERVIEW
- 8.2 ON PREMISES
- 8.3 CLOUD BASED
9 GLOBAL AI IN MANUFACTURING, BY ORGANIZATION SIZE
- 9.1 OVERVIEW
- 9.2 SMES
- 9.3 LARGE ENTERPRISES
10 GLOBAL AI IN MANUFACTURING, APPLICATION AREA
- 10.1 OVERVIEW
- 10.2 PREDICTIVE MAINTENANCE AND MACHINERY INSPECTION
- 10.3 QUALITY CONTROL AND INSPECTION
- 10.4 PRODUCTION PLANNING AND MANAGEMENT
- 10.5 INVENTORY MANAGEMENT
- 10.6 PREDICTIVE ANALYTICS
- 10.7 ROBOTICS AND AUTOMATION
- 10.8 ENERGY MANAGEMENT
- 10.9 SUPPLY CHAIN OPTIMIZATION
11 GLOBAL AI IN MANUFACTURING, BY END USE INDUSTRY
- 11.1 OVERVIEW
- 11.2 AUTOMOTIVE
- 11.3 ELECTRONICS AND SEMICONDUCTORS
- 11.4 PHARMACEUTICALS AND CHEMICALS
- 11.5 FOOD AND BEVERAGES
- 11.6 HEAVY METALS AND MACHINERY
- 11.7 ENERGY AND UTILITIES
- 11.8 TEXTILES AND APPAREL
- 11.9 AEROSPACE AND DEFENSE
- 11.10 CONSUMER GOODS
- 11.11 OTHERS
12 GLOBAL AI IN MANUFACTURING, BY REGION
- 12.1 OVERVIEW
- 12.2 NORTH AMERICA
- 12.2.1 US
- 12.2.2 CANADA
- 12.2.3 MEXICO
- 12.3 EUROPE
- 12.3.1 GERMANY
- 12.3.2 ITALY
- 12.3.3 FRANCE
- 12.3.4 SPAIN
- 12.3.5 UK
- 12.3.6 REST OF EUROPE
- 12.4 ASIA-PACIFIC
- 12.4.1 CHINA
- 12.4.2 JAPAN
- 12.4.3 INDIA
- 12.4.4 SOUTH KOREA
- 12.4.5 REST OF ASIA PACIFIC
- 12.5 MIDDLE EAST & AFRICA
- 12.5.1 GCC COUNTRIES
- 12.5.2 SOUTH AFRICA
- 12.5.3 REST OF MEA
- 12.6 SOUTH AMERICA
- 12.6.1 BRAZIL
- 12.6.2 ARGENTINA
- 12.6.3 REST OF SOUTH AMERICA
13 COMPETITIVE LANDSCAPE
- 13.1 INTRODUCTION
- 13.2 COMPANY MARKET SHARE ANALYSIS, 2023 (% SHARE)
- 13.3 COMPETITIVE BENCHMARKING
- 13.4 PUBLIC PLAYERS STOCK SUMMARY
- 13.5 COMPARATIVE ANALYSIS: KEY PLAYERS FINANICAL
- 13.6 KEY DEVELOPMENTS & GROWTH STRATEGIES
- 13.6.1 NEW PRODUCT DEVELOPMENT
- 13.6.2 MERGER AND ACQUISTION
- 13.6.3 PARTNERSHIPS/ COLLABORATION/OTHERS
14 COMPANY PROFILES
- 14.1 NVIDIA CORPORATION
- 14.1.1 COMPANY OVERVIEW
- 14.1.2 FINANCIAL OVERVIEW
- 14.1.3 PRODUCTS OFFERED
- 14.1.4 KEY DEVELOPMENTS
- 14.1.5 SWOT ANALYSIS
- 14.1.6 KEY STRATEGIES
- 14.2 IBM CORPORATION
- 14.2.1 COMPANY OVERVIEW
- 14.2.2 FINANCIAL OVERVIEW
- 14.2.3 PRODUCTS OFFERED
- 14.2.4 KEY DEVELOPMENTS
- 14.2.5 SWOT ANALYSIS
- 14.2.6 KEY STRATEGIES
- 14.3 SIEMENS
- 14.3.1 COMPANY OVERVIEW
- 14.3.2 FINANCIAL OVERVIEW
- 14.3.3 PRODUCTS OFFERED
- 14.3.4 KEY DEVELOPMENTS
- 14.3.5 SWOT ANALYSIS
- 14.3.6 KEY STRATEGIES
- 14.4 GENERAL ELECTRIC
- 14.4.1 COMPANY OVERVIEW
- 14.4.2 FINANCIAL OVERVIEW
- 14.4.3 PRODUCTS OFFERED
- 14.4.4 KEY DEVELOPMENTS
- 14.4.5 SWOT ANALYSIS
- 14.4.6 KEY STRATEGIES
- 14.5 INTEL
- 14.5.1 COMPANY OVERVIEW
- 14.5.2 FINANCIAL OVERVIEW
- 14.5.3 PRODUCTS OFFERED
- 14.5.4 KEY DEVELOPMENTS
- 14.5.5 SWOT ANALYSIS
- 14.5.6 KEY STRATEGIES
- 14.6 MICROSOFT CORPORATION
- 14.6.1 COMPANY OVERVIEW
- 14.6.2 FINANCIAL OVERVIEW
- 14.6.3 PRODUCTS OFFERED
- 14.6.4 KEY DEVELOPMENTS
- 14.6.5 SWOT ANALYSIS
- 14.6.6 KEY STRATEGIES
- 14.7 ROBERT BOSCH
- 14.7.1 COMPANY OVERVIEW
- 14.7.2 FINANCIAL OVERVIEW
- 14.7.3 PRODUCTS OFFERED
- 14.7.4 KEY DEVELOPMENTS
- 14.7.5 SWOT ANALYSIS
- 14.7.6 KEY STRATEGIES
- 14.8 AMAZON WEB SERVICES (AMAZON INC.)
- 14.8.1 COMPANY OVERVIEW
- 14.8.2 FINANCIAL OVERVIEW
- 14.8.3 PRODUCTS OFFERED
- 14.8.4 KEY DEVELOPMENTS
- 14.8.5 SWOT ANALYSIS
- 14.8.6 KEY STRATEGIES
- 14.9 CISCO SYSTEMS, INC.
- 14.9.1 COMPANY OVERVIEW
- 14.9.2 FINANCIAL OVERVIEW
- 14.9.3 PRODUCTS OFFERED
- 14.9.4 KEY DEVELOPMENTS
- 14.9.5 SWOT ANALYSIS
- 14.9.6 KEY STRATEGIES
- 14.10 ROCKWELL AUTOMATION
- 14.10.1 COMPANY OVERVIEW
- 14.10.2 FINANCIAL OVERVIEW
- 14.10.3 PRODUCTS OFFERED
- 14.10.4 KEY DEVELOPMENTS
- 14.10.5 SWOT ANALYSIS
- 14.10.6 KEY STRATEGIES
