Abstract
Summary
The artificial intelligence in manufacturing market is expected to reach USD 20.8 billion by 2028 from USD 3.2 billion in 2023, at a CAGR of 45.6% from 2023–2028. The growth of this market is attributed to the Rising need to handle increasingly large and complex dataset and emerging industrial IoT and automation technologies.
“Machine learning technology segment to dominate the artificial intelligence in manufacrturing market in 2023”
Machine Learning includes various technologies, such as deep learning, supervised learning, unsupervised learning, and reinforcement learning. Machine learning enables systems to improve their performance automatically with experience. Machine Learning helps develop a computer program/algorithm that can access data and use it to train itself without human intervention. The ability of Machine Learning to collect and handle big data and its increasing applications in predictive analytics and machinery inspection, quality control, and cybersecurity are expected to drive the growth of the artificial intelligence in manufacturing market for Machine Learning technology.
“Quality control segment is projected to grow at a highest CAGR during the forecast period.”
AI-driven quality control systems empower plant operators to identify deviations in product properties during the manufacturing process. These quality control applications depend on gathering both three-dimensional (3D) and two-dimensional (2D) data through laser-based aggregate scanning systems, which subsequently transform this data into digital images. The core technologies applied in these quality control applications within manufacturing plants encompass machine learning, computer vision, and context-aware computing. This robust quality control framework aids plant operators in validating the product quality, and it finds extensive application in industries such as pharmaceuticals, food and beverages, as well as semiconductors.“Software segment hold the largest market share during the forecast period”
A computer system needs highly effective and efficient hardware and software to exhibit intelligent capabilities like the human brain. The growing adoption of AI solutions and platforms in various industries and the widening application scope of AI in the manufacturing sector are the prime factors driving the growth of the artificial intelligence in manufacturing market for the software segment.
“China is to dominate the artificial intelligence in manufacrturing market of Asia Pacific in 2023”
Asia Pacific consists of some of the fastest-growing economies—such as China, Japan, and South Korea. China is a key manufacturing hub in the Asia Pacific region. The country is a major force of artificial intelligence development in Asia Pacific, with strengths in data accessibility and policy support. The manufacturing sector in China is growing rapidly, resulting in the introduction of new robotics and big data technologies. All these factors, coupled with the presence of a large number of manufacturing plants in China, are expected to increase the manufacturing data volume. Moreover, the government of China is undertaking initiatives to encourage the adoption of AI technologies in manufacturing
The break-up of the profiles of primary participants:
• By Company Type – Tier 1 – 55%, Tier 2 – 25%, and Tier 3 – 20%
• By Designation – C-level Executives – 60%, Directors – 20%, and Others – 20%
• By Region – North America - 40%, Europe – 30%, Asia Pacific – 20%, and Rest of the World – 10%
Major players in the artificial intelligence in manufacturing market include Siemens, IBM, Intel Corporation, NVIDIA Corporation, and General Electric and others.
Research Coverage
The report segments the artificial intelligence in manufacturing market by Offering, Technology, Application, Industry, and Region. The report also comprehensively reviews drivers, restraints, opportunities, and challenges influencing market growth. The report also covers qualitative aspects in addition to the quantitative aspects of the market.
Reasons to buy the report:
The report will help the market leaders/new entrants with information on the closest approximate revenues for the overall artificial intelligence in manufacturing market and related segments. This report will help stakeholders understand the competitive landscape and gain more insights to strengthen their position in the market and plan suitable go-to-market strategies. The report also helps stakeholders understand the market pulse and provides information on key market drivers, restraints, opportunities, and challenges.
The report provides insights on the following pointers:
• Analysis of critical drivers (Rising need to handle increasingly large and complex dataset, emerging industrial IoT and automation technology, surging adoption of AI fuiling growth of semiconductor chipset manufacturing, growing investment propelling growth of start-ups in manufacturing AI space), restraints (Reluctance among manufacturers to adopt AI-based technologies), opportunities (enhance manufacturing efficiency through AI-powered predictive analytics and production planning, application of AI-driven machine learning and NLP for intelligent enterprise processes), and challenges (lack of skilled workforce, especially in developing countries and concerns regarding data privacy and cybersecurity regulations) influencing the growth of the artificial intelligence in manufacturing market.
• Product Development/Innovation: Detailed insights on upcoming technologies, research and development activities, and new product launches in the artificial intelligence in manufacturing market.
• Market Development: Comprehensive information about lucrative markets – the report analyses the artificial intelligence in manufacturing market across various regions.
• Market Diversification: Exhaustive information about new products, untapped geographies, recent developments, and investments in the artificial intelligence in manufacturing market.
• Competitive Assessment: In-depth assessment of market shares, growth strategies, and product offerings of leading players like Siemens (Germany), IBM (US), Intel Corporation (US), NVIDIA Corporation (US), and General Electric Company (US).
Table of Contents
1 INTRODUCTION 36
1.1 STUDY OBJECTIVES 36
1.2 MARKET DEFINITION 36
1.2.1 INCLUSIONS AND EXCLUSIONS 37
1.3 STUDY SCOPE 37
1.3.1 MARKETS COVERED 37
1.3.2 REGIONAL SCOPE 38
1.3.3 YEARS CONSIDERED 38
1.4 CURRENCY CONSIDERED 39
1.5 STAKEHOLDERS 39
1.6 SUMMARY OF CHANGES… 40
1.6.1 RECESSION IMPACT ANALYSIS 40
2 RESEARCH METHODOLOGY 41
2.1 RESEARCH DATA 41
2.1.1 SECONDARY DATA 42
- 2.1.1.1 List of major secondary sources 42
- 2.1.1.2 Key data from secondary sources 43
2.1.2 PRIMARY DATA 43
- 2.1.2.1 Primary interviews with experts 44
- 2.1.2.2 Breakdown of primaries 44
- 2.1.2.3 Key data from primary sources 45
2.1.3 SECONDARY AND PRIMARY RESEARCH 46
- 2.1.3.1 Key industry insights 47
2.2 MARKET SIZE ESTIMATION 47
2.2.1 BOTTOM-UP APPROACH 47
- 2.2.1.1 Approach to derive market size using bottom-up analysis 47
2.2.2 TOP-DOWN APPROACH 48
- 2.2.2.1 Approach to derive market size using bottom-up analysis 49
2.3 MARKET BREAKDOWN AND DATA TRIANGULATION 50
2.4 RESEARCH ASSUMPTIONS 51
2.5 PARAMETERS CONSIDERED TO ANALYZE IMPACT OF RECESSION ON ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET 51
2.6 RESEARCH LIMITATIONS 52
2.7 RISK ASSESSMENT 52
3 EXECUTIVE SUMMARY 53
4 PREMIUM INSIGHTS 59
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET 59
4.2 ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY OFFERING 60
4.3 ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY TECHNOLOGY 60
4.4 ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY APPLICATION 61
4.5 ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY INDUSTRY 62
4.6 ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY COUNTRY 63
5 MARKET OVERVIEW 64
5.1 INTRODUCTION 64
5.2 MARKET DYNAMICS 65
5.2.1 DRIVERS 65
- 5.2.1.1 Pressing need to handle large and complex datasets effectively 65
- 5.2.1.2 Rising adoption of IIoT and automation technologies by manufacturing firms 66
- 5.2.1.3 Thriving semiconductor chipset industry due to increasing adoption of AI technology 66
- 5.2.1.4 Growing venture capital and seed funding opportunities for startups entering in AI-driven manufacturing 67
5.2.2 RESTRAINTS 68
- 5.2.2.1 Reluctance among manufacturers to adopt AI-based technologies 68
5.2.3 OPPORTUNITIES 68
- 5.2.3.1 Utilization of AI-powered predictive analytics and production planning apps to enhance manufacturing efficiency 68
- 5.2.3.2 Execution of ML and NLP to automate and upgrade business processes 69
5.2.4 CHALLENGES 69
- 5.2.4.1 Shortage of skilled workforce, especially in developing countries 69
- 5.2.4.2 Concerns regarding data privacy and stringent data security regulations 70
5.3 VALUE CHAIN ANALYSIS 70
5.4 ECOSYSTEM MAPPING 72
5.5 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 74
5.6 PORTER’S FIVE FORCES ANALYSIS 74
5.6.1 BARGAINING POWER OF SUPPLIERS 76
5.6.2 BARGAINING POWER OF BUYERS 76
5.6.3 THREAT OF NEW ENTRANTS 76
5.6.4 THREAT OF SUBSTITUTES 76
5.6.5 INTENSITY OF COMPETITIVE RIVALRY 76
5.7 CASE STUDY ANALYSIS 76
5.8 TECHNOLOGY ANALYSIS 78
5.9 PRICING ANALYSIS 78
5.9.1 AVERAGE SELLING PRICE OF PROCESSORS OFFERED BY KEY PLAYERS 78
5.9.2 AVERAGE SELLING PRICE TREND OF PROCESSORS, BY TYPE 79
5.10 TRADE ANALYSIS 81
5.10.1 IMPORT SCENARIO 81
5.10.2 EXPORT SCENARIO 82
5.11 PATENT ANALYSIS 83
5.12 KEY STAKEHOLDERS AND BUYING CRITERIA 88
5.12.1 KEY STAKEHOLDERS IN BUYING PROCESS 88
5.12.2 BUYING CRITERIA 89
5.13 KEY CONFERENCES AND EVENTS, 2023-2025 90
5.14 REGULATORY LANDSCAPE 91
5.14.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 91
5.14.2 STANDARDS IN ITS/C-ITS 93
6 ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY OFFERING 94
6.1 INTRODUCTION 95
6.2 HARDWARE 97
6.2.1 PROCESSORS 98
- 6.2.1.1 Robust parallel processing capabilities of processors to foster adoption in AI applications 98
- 6.2.1.1.1 Microprocessor units (MPUs) 99
- 6.2.1.1.2 Graphics processing units (GPUs) 99
- 6.2.1.1.3 Field programmable gate array (FPGA) 99
- 6.2.1.1.4 Application-specific integrated circuits (ASICs) 99
- 6.2.1.1 Robust parallel processing capabilities of processors to foster adoption in AI applications 98
6.2.2 MEMORY DEVICES 100
- 6.2.2.1 High demand for high-bandwidth memory devices to drive market 100
6.2.3 NETWORK DEVICES 100
- 6.2.3.1 Increased implementation of Ethernet adaptors and interconnects to create opportunities for network device providers 100
6.3 SOFTWARE 101
6.3.1 AI SOLUTIONS 102
- 6.3.1.1 Rising use of nonprocedural languages to develop AI solutions to boost segmental growth 102
- 6.3.1.2 On-premises 102
- 6.3.1.2.1 Greater flexibility and control offered by on-premises AI solutions to fuel segmental growth 102
- 6.3.1.3 Cloud 103
- 6.3.1.3.1 Reduced operational costs, hassle-free deployment, and high scalability provided by cloud deployment model to drive segmental growth 103
6.3.2 AI PLATFORMS 103
- 6.3.2.1 Increasing adoption of AI platforms to develop learning algorithms and intelligent applications to support segmental growth 103
- 6.3.2.2 Machine learning framework 104
- 6.3.2.3 Application program interface (API) 105
6.4 SERVICES 105
6.4.1 DEPLOYMENT & INTEGRATION 106
- 6.4.1.1 Growing demand for deployment and integration services while configuring AI systems in manufacturing sector to drive market 106
6.4.2 SUPPORT & MAINTENANCE 106
- 6.4.2.1 Increasing demand for support & maintenance services to keep systems at acceptable standards to fuel market growth 106
7 ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY TECHNOLOGY 107
7.1 INTRODUCTION 108
7.2 MACHINE LEARNING 109
7.2.1 ADVANCEMENTS IN DEEP LEARNING, SUPERVISED LEARNING, AND REINFORCEMENT LEARNING TECHNOLOGIES TO DRIVE MARKET 109
7.2.2 DEEP LEARNING 112
- 7.2.2.1 Growing penetration of IoT, automation, and machine vision technologies in manufacturing plants to drive market 112
7.2.3 SUPERVISED LEARNING 113
- 7.2.3.1 Image recognition, facial recognition, and predictive analytics to contribute to market growth 113
7.2.4 REINFORCEMENT LEARNING 113
- 7.2.4.1 Potential to automatically determine context-specific ideal behavior to maximize performance to drive market 113
7.2.5 UNSUPERVISED LEARNING 113
- 7.2.5.1 Use of algorithms to find hidden data patterns or groupings in large datasets to boost adoption of unsupervised learning technology 113
7.2.6 OTHER TECHNOLOGY TYPES 114
7.3 NATURAL LANGUAGE PROCESSING 114
7.3.1 RISING USE OF NLP-DRIVEN TOOLS TO AUTOMATE COMPLEX BUSINESS PROCESSES TO DRIVE MARKET 114
7.4 CONTEXT-AWARE COMPUTING 116
7.4.1 INCREASING FOCUS ON MAKING REAL-TIME DECISIONS TO ENHANCE QUALITY, SAFETY, AND PRODUCTIVITY TO BOOST DEMAND IN MANUFACTURING SECTOR 116
7.5 COMPUTER VISION 118
7.5.1 INTEGRATION OF COMPUTER VISION TECHNOLOGY TO ANALYZE 3D OBJECTS AND MINIMIZE MATERIAL WASTE TO DRIVE MARKET 118
8 ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY APPLICATION 120
8.1 INTRODUCTION 121
8.2 INVENTORY OPTIMIZATION 123
8.2.1 GROWING IMPLEMENTATION OF AI IN MANUFACTURING SECTOR TO ACHIEVE COST-EFFICIENCY AND ENSURE TIMELY PRODUCT DELIVERY TO DRIVE MARKET 123
8.3 PREDICTIVE MAINTENANCE & MACHINERY INSPECTION 125
8.3.1 INCREASING ADOPTION OF LEARNING TECHNOLOGY TO PREVENT UNEXPECTED DOWNTIME DUE TO MACHINE FAILURE TO FUEL MARKET GROWTH 125
8.4 PRODUCTION PLANNING 128
8.4.1 RISING USE OF BIG DATA ANALYTICS IN PRODUCTION PLANNING TO FOSTER MARKET GROWTH 128
8.5 FIELD SERVICES 130
8.5.1 SURGING USE OF AI-POWERED SOLUTIONS IN FIELD SERVICES OFFERED TO OIL & GAS AND ENERGY & POWER INDUSTRY PLAYERS TO SUPPORT MARKET GROWTH 130
8.6 RECLAMATION 131
8.6.1 ELEVATING DEMAND FOR COMPUTER VISION TECHNOLOGY TO IDENTIFY AND SORT RECYCLABLE MATERIALS TO DRIVE MARKET 131
8.7 QUALITY CONTROL 133
8.7.1 GROWING USE OF AI-POWERED QUALITY CONTROL SYSTEMS BY PHARMACEUTICAL AND FOOD & BEVERAGE COMPANIES TO ACCELERATE MARKET GROWTH 133
8.8 CYBERSECURITY 135
8.8.1 HIGH EMPHASIS OF AUTOMATED PLANTS ON AVOIDING DATA BREACHES TO BOOST DEMAND FOR AI-DRIVEN CYBERSECURITY SOLUTIONS 135
8.9 INDUSTRIAL ROBOTS 138
8.9.1 SEAMLESS INTEGRATION OF AI INTO INDUSTRIAL ROBOTS TO IMPROVE PRODUCTION AND EFFICIENCY TO DRIVE MARKET 138
9 ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY INDUSTRY 140
9.1 INTRODUCTION 141
9.2 AUTOMOTIVE 143
9.2.1 INCREASING ADOPTION OF ML AND COMPUTER VISION TECHNOLOGIES TO ENSURE FLAWLESS PRODUCTION OF VEHICLE PARTS TO DRIVE MARKET 143
9.3 ENERGY & POWER 144
9.3.1 GROWING IMPLEMENTATION OF AI TO MINIMIZE ENERGY WASTE AND REDUCE ENERGY COSTS TO BOOST SEGMENTAL GROWTH 144
9.4 PHARMACEUTICALS 146
9.4.1 RISING USE OF AI IN QUALITY CONTROL AND PRODUCTION PLANNING APPLICATIONS TO STIMULATE MARKET GROWTH 146
9.5 METALS & HEAVY MACHINERY 147
9.5.1 INCREASED USE OF ROBOTICS IN METALS & HEAVY MACHINERY INDUSTRY TO AVOID UNPLANNED DOWNTIME AND WASTAGE TO DRIVE MARKET 147
9.6 SEMICONDUCTOR & ELECTRONICS 149
9.6.1 SURGING FOCUS ON DEVELOPING MINIATURE SEMICONDUCTOR AND ELECTRONICS EQUIPMENT TO BOOST ADOPTION OF AI-BASED INDUSTRIAL ROBOTS 149
9.7 FOOD & BEVERAGES 150
9.7.1 GROWING ADOPTION OF AUTOMATION TO MAINTAIN HYGIENIC FOOD PROCESSING SOLUTIONS TO FUEL MARKET GROWTH 150
9.8 OTHER INDUSTRIES 152
10 ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET, BY REGION 154
10.1 INTRODUCTION 155
10.2 NORTH AMERICA 157
10.2.1 NORTH AMERICA: RECESSION IMPACT 157
10.2.2 US 161
- 10.2.2.1 Rising adoption of industrial robots due to shortage of skilled workforce to drive market 161
10.2.3 CANADA 161
- 10.2.3.1 Increasing investments by SMEs in IoT to boost demand for AI-based solutions 161
10.2.4 MEXICO 162
- 10.2.4.1 Surging foreign direct investments in AI and robotics to support market growth 162
10.3 EUROPE 162
10.3.1 EUROPE: RECESSION IMPACT 162
10.3.2 GERMANY 166
- 10.3.2.1 High adoption of computer vision systems to get real-time manufacturing data to fuel market growth 166
10.3.3 UK 167
- 10.3.3.1 Increasing investment by government in robotics and AI technologies to foster market growth 167
10.3.4 FRANCE 167
- 10.3.4.1 Rising adoption of AI by manufacturing firms to fuel market growth 167
10.3.5 REST OF EUROPE 168
10.4 ASIA PACIFIC 169
10.4.1 CHINA 173
- 10.4.1.1 Strategic planning to achieve Next Generation AI goal by 2030 to boost demand for AI technology by manufacturing firms 173
10.4.2 JAPAN 173
- 10.4.2.1 Strong presence of top-tier IT, machinery, and automobile manufacturing firms to support market growth 173
10.4.3 SOUTH KOREA 174
- 10.4.3.1 Presence of massive computing data centers for AI research to contribute to market growth 174
10.4.4 REST OF ASIA PACIFIC 174
10.5 ROW 175
10.5.1 SOUTH AMERICA 177
- 10.5.1.1 Increased investments in IT infrastructure development to fuel market growth 177
10.5.2 MIDDLE EAST & AFRICA 177
- 10.5.2.1 Increasing deployment of cloud-based cognitive computing in manufacturing sector to drive market 177
11 COMPETITIVE LANDSCAPE 178
11.1 INTRODUCTION 178
11.2 MAJOR STRATEGIES ADOPTED BY KEY PLAYERS 178
11.3 REVENUE ANALYSIS OF TOP 5 PLAYERS 179
11.4 MARKET SHARE ANALYSIS 180
11.5 COMPANY EVALUATION MATRIX, 2022 182
11.5.1 STARS 182
11.5.2 PERVASIVE PLAYERS 182
11.5.3 EMERGING LEADERS 182
11.5.4 PARTICIPANTS 182
11.6 ARTIFICIAL INTELLIGENCE IN MANUFACTURING MARKET: COMPANY FOOTPRINT 184
11.6.1 COMPANY FOOTPRINT OF TOP PLAYERS 184
11.7 SMALL AND MEDIUM-SIZED ENTERPRISES (SMES) EVALUATION MATRIX, 2022 188
11.7.1 PROGRESSIVE COMPANIES 188
11.7.2 RESPONSIVE COMPANIES 188
11.7.3 DYNAMIC COMPANIES 188
11.7.4 STARTING BLOCKS 188
11.8 COMPETITIVE BENCHMARKING 190
11.9 COMPETITIVE SITUATIONS AND TRENDS 193
12 COMPANY PROFILES 203
12.1 KEY PLAYERS 203
12.1.1 NVIDIA CORPORATION 203
12.1.2 IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) 209
12.1.3 INTEL CORPORATION 215
12.1.4 SIEMENS 220
12.1.5 GENERAL ELECTRIC 226
12.1.6 GOOGLE LLC 231
12.1.7 MICROSOFT 235
12.1.8 MICRON TECHNOLOGY, INC 240
12.1.9 AMAZON WEB SERVICES, INC. (AWS) 246
12.1.10 SIGHT MACHINE 249
12.2 OTHER PLAYERS 252
12.2.1 PROGRESS SOFTWARE CORPORATION (DATARPM) 252
12.2.2 AIBRAIN INC 253
12.2.3 GENERAL VISION INC 254
12.2.4 ROCKWELL AUTOMATION 255
12.2.5 CISCO SYSTEMS, INC 256
12.2.6 MITSUBISHI ELECTRIC CORPORATION 257
12.2.7 ORACLE 258
12.2.8 SAP 259
12.2.9 VICARIOUS 260
12.2.10 UBTECH ROBOTICS CORP LTD 260
12.2.11 AQUANT 261
12.2.12 BRIGHT MACHINES, INC 261
12.2.13 RETHINK ROBOTICS GMBH 262
12.2.14 SPARKCOGNITION 262
12.2.15 FLUTURA 263
13 ADJACENT MARKET 264
13.1 SMART FACTORY MARKET 264
13.2 INTRODUCTION 264
13.3 INDUSTRIAL SENSORS 266
13.3.1 LEVEL SENSORS 268
- 13.3.1.1 Rising demand for level sensors to detect and measure levels of liquids, bulk solids, and other fluids to drive market 268
13.3.2 TEMPERATURE SENSORS 269
- 13.3.2.1 Increasing use of temperature sensors in chemicals, energy & power, and oil & gas vertical to support market growth 269
13.3.3 FLOW SENSORS 269
- 13.3.3.1 Rising adoption of flow sensors to measure rate of fluid flow either directly or inferentially to fuel market growth 269
13.3.4 POSITION SENSORS 269
- 13.3.4.1 Increasing application areas of position sensors increasing with technological advancements to drive market 269
13.3.5 PRESSURE SENSORS 269
- 13.3.5.1 Growing adoption of pressure sensors in semiconductor processing, robotics, and test & measurement in industrial applications to contribute to market growth 269
13.3.6 FORCE SENSORS 270
- 13.3.6.1 Rising use of force sensors to ensure safe robot and human interaction to drive market 270
13.3.7 HUMIDITY & MOISTURE SENSORS 270
- 13.3.7.1 Extensive use of humidity and moisture sensors in chemicals, pharmaceuticals, oil & gas, and food & beverages verticals to drive market 270
13.3.8 IMAGE SENSORS 270
- 13.3.8.1 Increasing adoption of image sensors to convert optical images into electronic signals to support market growth 270
13.3.9 GAS SENSORS 271
- 13.3.9.1 Surging adoption of gas sensors to measure concentration of different gases in air to contribute to market growth 271
13.4 INDUSTRIAL ROBOTS 271
13.4.1 TRADITIONAL INDUSTRIAL ROBOTS 273
- 13.4.1.1 Articulated robots 273
- 13.4.1.1.1 Growing use of articulated robots in assembly and welding to drive segmental growth 273
- 13.4.1.2 Cartesian robots 273
- 13.4.1.2.1 Potential to carry heavy loads to boost demand for cartesian robots in industrial applications 273
- 13.4.1.3 Selective compliance assembly robot arm (SCARA) robots 274
- 13.4.1.3.1 Growing utilization of SCARA robots in welding and spray-painting operations to fuel market growth 274
- 13.4.1.4 Cylindrical robots 274
- 13.4.1.4.1 Suitability of cylindrical robots for pick and place operations to drive market 274
- 13.4.1.5 Other robots 274
- 13.4.1.1 Articulated robots 273
13.4.2 COLLABORATIVE ROBOTS 274
- 13.4.2.1 Highest adoption rate of collaborative robots in industrial applications to drive market 274
13.5 INDUSTRIAL 3D PRINTERS 275
13.5.1 RISING ADOPTION OF INDUSTRIAL PRINTERS TO CONSTRUCT THREE-DIMENSIONAL SOLID OBJECTS TO DRIVE MARKET 275
13.6 MACHINE VISION SYSTEMS 278
13.6.1 CAMERAS 280
- 13.6.1.1 Rising need for high-quality images to boost demand for smart cameras 280
13.6.2 FRAME GRABBERS, OPTICS, AND LED LIGHTING 280
- 13.6.2.1 Influence of position and quality of other key components, such as LEDs and frame grabbers, on image quality to lead to high demand 280
13.6.3 PROCESSORS AND SOFTWARE 281
- 13.6.3.1 Growing integration of processors and software in machine vision systems to drive market 281
14 APPENDIX 282
14.1 INSIGHTS FROM INDUSTRY EXPERTS 282
14.2 DISCUSSION GUIDE 283
14.3 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 286
14.4 CUSTOMIZATION OPTIONS 288
14.5 RELATED REPORTS 288
14.6 AUTHOR DETAILS 289