Dublin, Feb. 22, 2019 (GLOBE NEWSWIRE) -- The "Artificial Intelligence in Manufacturing Market by Offering (Hardware, Software, and Services), Technology (Machine Learning, Computer Vision, Context-Aware Computing, and NLP), Application, Industry, and Geography - Global Forecast to 2025" report has been added to ResearchAndMarkets.com's offering.
The AI in manufacturing market is expected to be valued at USD 1.03 billion in 2018 and is likely to reach USD 17.22 billion by 2025, at a CAGR of 49.5% during the forecast period.
The manufacturing industry is witnessing a new wave of technological revolution, which is boosting the idea for implementation of AI in factories/plants. AI-based solutions are adopted in manufacturing facilities to improve productivity by maximizing asset utilization, minimizing downtime, and improving machine efficiency. Moreover, AI in manufacturing is expected to enhance productivity through quality control by detecting defects and help in the predictive maintenance of factory machinery. Extensive usage of big data, Industrial Internet of Things (IIoT), smart factory, and robotics are among the major factors driving the growth of this market.
The increase in the cost of labor and related supply-demand dynamics along with higher levels of output, better quality, and fewer errors are the major macro drivers for the growth of the AI in manufacturing market. Therefore, manufacturers and technology providers are spending heavily on research and development (R&D) to fulfill this market demand. The AI in manufacturing market marks a revolutionary convergence of different stakeholders such as hardware providers, software and technology companies, and manufacturers.
Major drivers for the market are increasing large and complex data set (often known as big data), evolving Industrial IoT and automation, improving computing power and declining hardware cost, and growing venture capital investments. The major restraint for the market is reluctance among manufacturers to adopt AI-based technologies. Critical challenges facing the AI in manufacturing market include limited skilled workforce and concerns regarding data privacy. Underlying opportunities in the AI in manufacturing market include improving the operational efficiency of manufacturing plants and application of AI for intelligent business process.
The competitive landscape chapter, in this report, provides the ranking of the key players in the AI in manufacturing market on the basis of their product portfolio, contribution to the manufacturing market, employee size, geographic reach, and growth after entry into the AI in manufacturing market.
Key Topics Covered:
1 Introduction
2 Research Methodology
3 Executive Summary
4 Premium Insights
4.1 Attractive Opportunities in AI in Manufacturing Market
4.2 AI in Manufacturing Market, By Offering
4.3 AI in Manufacturing Market, By Technology
4.4 APAC: AI in Manufacturing Market, By Industry and Country
4.5 AI in Manufacturing Market, By Country
5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Increasingly Large and Complex Data Set
5.2.1.2 Evolving Industrial IoT and Automation
5.2.1.3 Improving Computing Power and Declining Hardware Cost
5.2.1.4 Increasing Venture Capital Investments
5.2.2 Restraints
5.2.2.1 Reluctance Among Manufacturers to Adopt AI-Based Technologies
5.2.3 Opportunities
5.2.3.1 Growth in Operational Efficiency of Manufacturing Plants
5.2.3.2 Application of AI for Intelligent Business Process
5.2.4 Challenges
5.2.4.1 Limited Skilled Workforce
5.2.4.2 Concerns Regarding Data Privacy
5.3 Value Chain Analysis
5.4 Case Studies
5.4.1 Siemens Games Uses Fujitsu's AI Solution to Accelerate Inspection of Turbine Blades
5.4.2 Volvo Uses Machine Learning-Driven Data Analytics for Predicting Breakdown and Failures
5.4.3 Rolls-Royce Using Microsoft Cortana Intelligence for Predictive Maintenance
5.4.4 Paper Packaging Firm Used Sight Machines Enterprise Manufacturing Analytics to Improve Production
6 Artificial Intelligence in Manufacturing Market, By Offering
6.1 Introduction
6.2 Hardware
6.2.1 Processor
6.2.1.1 MPU
6.2.1.1.1 MPUs to Hold the Largest Share of AI in Manufacturing Market for Processors During the Forecast Period
6.2.1.2 GPU
6.2.1.2.1 GPUs to Grow at the Highest CAGR During the Forecast Period
6.2.1.3 FPGA
6.2.1.3.1 Low Power Consumption and Low Latency Expected to Drive the Market for FPGA
6.2.1.4 Asic
6.2.1.4.1 User-Specific Customized Solution Offered By Asic to Drive Its Market
6.2.2 Memory
6.2.2.1 High-Bandwidth Memory is Being Developed and Deployed for AI Applications, Independent of Its Computing Architecture
6.2.3 Network
6.2.3.1 Nvidia (US), Intel (US) and Mellanox Technologies (Israel) are the Key Providers of Network Interconnect Adapters for AI Applications
6.3 Software
6.3.1 AI Solutions
6.3.1.1 On-Premises
6.3.1.1.1 Data-Sensitive Enterprises Prefer On-Premise Advanced Nlp and Ml Tools to Be Used in AI Solutions
6.3.1.2 Cloud
6.3.1.2.1 AI Solution Providers are Focusing on the Development of Robust Cloud-Based Solutions for Their Clients
6.3.2 AI Platform
6.3.2.1 Machine Learning Framework
6.3.2.1.1 Major Tech Companies Such as Google, IBM, and Microsoft are Developing and Offering Their Own Ml Frameworks
6.3.2.2 Application Program Interface (API)
6.3.2.2.1 An API Provides A Platform for A Set of Routines and Tools for Building Software Applications
6.4 Services
6.4.1 Deployment & Integration
6.4.1.1 Deployment and Integration is A Key Service Required for Configuring AI Systems in Manufacturing
6.4.2 Support & Maintenance
6.4.2.1 The Ultimate Objective of Maintenance Services is to Keep the System at an Acceptable Standard
7 Artificial Intelligence in Manufacturing Market, By Technology
7.1 Introduction
7.2 Machine Learning
7.2.1 Deep Learning
7.2.1.1 Deep Learning Uses Artificial Neural Networks to Learn Multiple Levels of Data
7.2.2 Supervised Learning
7.2.2.1 Classification and Regression are Major Segmentation of Supervised Learning
7.2.3 Reinforcement Learning
7.2.3.1 Reinforcement Learning Allows Systems and Software to Determine Ideal Behavior for Maximizing Performance of the Systems
7.2.4 Unsupervised Learning
7.2.4.1 Unsupervised Learning Include Clustering Methods Consisting of Algorithms With Unlabeled Training Data
7.2.5 Others
7.3 Natural Language Processing
7.3.1 Nlp is Developed for Making Real-Time Translation and Developing Systems That Can Interact Through Dialogues
7.4 Context-Aware Computing
7.4.1 Development of More Sophisticated Hard and Soft Sensors has Accelerated the Growth of Context-Aware Computing
7.5 Computer Vision
7.5.1 Computer Vision Analyzes the Information of Different Geometric Shapes, Volumes, and Patterns
8 Artificial Intelligence in Manufacturing Market, By Application
8.1 Introduction
8.2 Predictive Maintenance and Machinery Inspection
8.2.1 Predictive Maintenance and Machinery Inspection Provide the Framework for All Planned Maintenance Activities
8.3 Material Movement
8.3.1 AI-Based Technology for Material Movement Will Ensure Streamlining of In-Plant Logistics
8.4 Production Planning
8.4.1 The Use of AI in Production Planning Leads to the Standardization of Product and Process Sequence
8.5 Field Services
8.5.1 Field Services are Extensively Used in Heavy Metals and Machine Manufacturing, Oil & Gas, and Energy and Power Industry
8.6 Quality Control
8.6.1 AI-Based Quality Control System is Widely Used in Pharmaceuticals, Food & Beverages, and Semiconductor Industries
8.7 Cybersecurity
8.7.1 Automation and Integrating Real-Time Systems in Manufacturing is Resulting in Adoption of Cybersecurity Systems
8.8 Industrial Robots
8.8.1 Industrial Robots Can Be Classified Into Traditional Industrial Robots and Collaborative Robots
8.9 Reclamation
8.9.1 in Reclamation, AI-Based Systems Detect Important Components From Waste Or Slags
9 Artificial Intelligence in Manufacturing Market, By Industry
9.1 Introduction
9.2 Automobile
9.2.1 Machine Learning and Computer Vision are the Major AI Technologies Deployed in Automobile Industry
9.3 Energy and Power
9.3.1 AI-Based Solutions Can Help Energy and Power Industry to Enhance Production Output and Reduced Downtime
9.4 Pharmaceuticals
9.4.1 Quality Control, Material Movement, and Production Planning are the Major Applications of AI in Pharmaceuticals
9.5 Heavy Metals and Machine Manufacturing
9.5.1 APAC is Considered to Have the Highest Number of Heavy Metals and Machine Manufacturing Plants in the World
9.6 Semiconductors and Electronics
9.6.1 AI is Likely to Assist in Optimizing the Production Cost, Technology Implementation, and Integration of Components
9.7 Food & Beverages
9.7.1 AI-Based Solutions Enhance the Quality of the Food Production Cost-Effectively
9.8 Others
10 Artificial Intelligence in Manufacturing Market, By Region
11 Competitive Landscape
11.1 Overview
11.2 Ranking of Players, 2017
11.3 Competitive Scenario
11.3.1 Product Launches and Developments
11.3.2 Collaborations, Partnerships, and Agreements
11.3.3 Acquisitions & Joint Ventures
12 Company Profiles
- Aibrain
- Alphabet Inc
- Amazon Web Services (AWS)
- Arimo Inc.
- Cisco Systems
- Citrine Informatics
- Clearpath Robotics Inc.
- CloudMinds Technologies
- DarkTrace
- DataRobot
- General Electric (GE) Company
- General Vision
- IBM
- Intel
- Kespry Inc.
- Micron Technology
- Microsoft
- Mitsubishi Electric
- Nvidia
- Omron Adept Technologies Inc.
- Oracle
- Preferred Networks Inc.
- Progress Software Corporation (Datarpm)
- Rockwell Automation
- SAP
- Siemens
- Sight Machine
- SkyMind, Inc.
- Tamr Inc.
- Ubtech Robotics
- Vicarious
For more information about this report visit https://www.researchandmarkets.com/research/2k8n5m/17_22_bn?w=12
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