Dublin, March 02, 2020 (GLOBE NEWSWIRE) -- The "Machine Vision Market by Deployment (General & Robotic cell), Component (Hardware and Software), Product (PC-based and Smart camera-based), Application, End-user Industry & Region - Forecast till 2025" report has been added to ResearchAndMarkets.com's offering.

The global machine vision market was valued at USD 9.9 billion in 2019 and is projected to reach USD 14.7 billion by 2025, growing at a CAGR of 6.5% between 2020 and 2025.

The major driving factors in the machine vision market is the increasing need for quality inspection and automation, growing demand for vision-guided robotic systems, increasing adoption of vision-guided robotic systems, and many more.

The major players in the machine vision market are Cognex Corporation (US), Basler AG (Germany), Omron Corporation (Japan), Keyence (Japan), National Instruments (US), Sony Corporation (Japan), Teledyne Technologies (US), Texas Instruments (US), Intel Corporation (US), ISRA Vision (Germany), Sick AG (Germany) and FLIR Systems (US).

Position & Guidance to Grow at the Fastest Rate in the Machine Vision Market During the Forecast Period

Position & guidance application enables manufacturers to build multiple products on the same production line and reduces the need for expensive hard tooling to maintain part position during inspection. Also, this application helps to improve the efficiency of production processes by instantaneously detecting the positional relationship between the target and machine tool or table and helps to control the system carefully.

Automotive Industry to Hold a Major Market Share in the Machine Vision Market During the Forecast Period

The automotive industry provides several opportunities for the machine vision market. The demand for machine vision systems is increasing in the automotive sector as it provides improved accuracy in critical activities such as bin picking and positioning of parts, such as doors and panels, for assembly. Due to the shortage of skilled laborers and the reducing manufacturing prices of automobiles, automobile companies are focusing more on automation in their production processes, ultimately boosting the growth of machine vision solutions in the automotive industry.

APAC held the Largest Market Share in the Machine Vision Market Between 2020 and 2025

The machine vision market in APAC is expected to hold a major market share during the forecast period as countries in APAC such as China, Japan, India, and South Korea have some of the largest manufacturing facilities wherein automation of manufacturing processes has been taken as the highest priority. Also, strong competition among consumer electronics companies in APAC is likely to boost the adoption of machine vision systems in the region.

Research Coverage

• This research report categorizes the global machine vision based on deployment, component, product, application, end-user industry, and geography.
• The report describes the major drivers, restraints, challenges, and opportunities pertaining to the machine vision market and forecasts the same until 2025.

Key Topics Covered

1 Introduction

2 Research Methodology

3 Executive Summary

4 Premium Insights
4.1 Machine Vision Market, 2017-2025 (USD Million)
4.2 Market, By Product
4.3 Market in APAC, By End-Use Industry and Country
4.4 Market, By Region
4.5 Market, By Application

5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Increasing Need for Quality Inspection and Automation
5.2.1.2 Growing Demand for Vision-Guided Robotic Systems
5.2.1.3 Increasing Adoption of 3D Machine Vision Systems
5.2.1.4 Increase in Manufacturing of Hybrid and Electric Cars
5.2.2 Restraints
5.2.2.1 Varying End-User Requirements
5.2.2.2 Lack of Flexible Machine Vision Solutions
5.2.3 Opportunities
5.2.3.1 Government Initiatives to Support Industrial Automation
5.2.3.2 Increasing Demand for AI in Machine Vision
5.2.3.2.1 Government Initiatives to Boost AI-Related Technologies
5.2.3.3 Growing Adoption of Industry 4.0
5.2.3.4 Need for Miniaturization of Cameras and Processors
5.2.3.5 Rising Need for Asics
5.2.4 Challenges
5.2.4.1 Complexity in Integrating Machine Vision Systems
5.2.4.2 Lack of User Awareness About Rapidly Changing Machine Vision Technology
5.3 Value Chain Analysis
5.3.1 R&D
5.3.2 Machine Vision Component Manufacturers
5.3.3 Original Equipment Manufacturers (OEMs)
5.3.4 System Integrators
5.3.5 Resellers and Distributors
5.3.6 End Users

6 Machine Vision, By Component
6.1 Introduction
6.2 Hardware
6.2.1 Cameras
6.2.1.1 Interface Standards
6.2.1.2 USB 2.0/USB 3.0
6.2.1.3 Camera Link
6.2.1.4 Gige
6.2.1.5 Coaxpress
6.2.1.6 Others (Emva-1288, Firewire, Genicam)
6.2.1.7 By Frame Rate
6.2.1.7.1 <25 FPS
6.2.1.7.2 25-125 FPS
6.2.1.7.3 More Than 125 FPS
6.2.1.8 By Format
6.2.1.8.1 Line Scan
6.2.1.8.2 Area Scan
6.2.1.9 By Sensor Type
6.2.1.9.1 Cmos
6.2.1.9.2 CCD
6.2.2 Frame Grabbers
6.2.2.1 Frame Grabber is A Part of the Computer Vision System Wherein Video Frames are Captured in A Digital Form
6.2.3 Optics
6.2.3.1 The Camera Lens Captures Images on A Photographic Film Or Other Media That are Capable of Storing an Image Chemically Or Electronically
6.2.4 LED Lighting
6.2.4.1 LED Lighting Conditions Determine the Quality of Images Captured By A Camera, the Images Can Be Enhanced in Such A Way That Some Features Can Get Negated, While Others Get Enriched
6.2.5 Processors
6.2.5.1 FPGA
6.2.5.1.1 An FPGA Consists of an Array of Programmable Logic Blocks, Which Can Be Configured to Design Desired Logic
6.2.5.2 DSP
6.2.5.2.1 DSPS have A Specially Designed Architecture, Which Helps in Fetching Multiple Data and Instructions at the Same Time
6.2.5.3 Microcontrollers and Microprocessors
6.2.5.3.1 Microcontrollers and Microprocessors are Specifically Designed for Real-Time Applications
6.2.5.4 VPU
6.2.5.4.1 VPU is A Type of AI Accelerator to Fulfill the Growing Need for Faster Processing Along With Compact Sizing for Data Generation in Vision-Related Applications
6.3 Software
6.3.1 Traditional Software
6.3.1.1 Traditional Software Provides A Framework to Develop and Deploy Machine Vision Applications
6.3.2 Deep Learning Software
6.3.2.1 Deep Learning Frameworks Offer Great Flexibility to Program Developers Owing to Their Ability to Design and Train Customized Deep Neural Networks

7 Machine Vision, By Product
7.1 Introduction
7.2 PC-Based Machine Vision Systems
7.2.1 PC-Based Machine Vision Systems have the Ability to Compensate for Unexpected Variations in Certain Tasks
7.3 Smart Camera-Based Vision Systems
7.3.1 Smart Camera-Based Vision Systems Consist of an Embedded Controller With an Integrated Vision Software That is Directly Connected to One Or More Cameras, Which May Differ in Image Resolution, Size, and Imaging Rates

8 Machine Vision, By Application
8.1 Introduction
8.2 Quality Assurance & Inspection
8.2.1 Manufacturers Use Machine Vision Systems for Visual Inspections That Require High Speed, High Magnification, Round-The-Clock Operation, and Repeatability of Measurements
8.3 Positioning & Guidance
8.3.1 Positioning Tools, Co-Ordinate Locators, Or Pattern Identifiers Recognize and Determine the Exact Position and Orientation of Parts and Objects
8.4 Measurement
8.4.1. Machine Vision Measurement Tools Combined With the Right Optics and Stable Lighting Provide Precision Repeatability to Ensure Manufacturing Accuracy.
8.5 Identification
8.5.1 in Identification, Vision Systems are Used to Read Various Codes and Alphanumeric Characters, Such as Text and Numbers
8.6 Predictive Maintenance
8.6.1 Predictive Maintenance Can Be Very Useful When There is Machine Downtime

9 Machine Vision, By End-Use Industry
9.1 Introduction
9.2 Automotive
9.2.1 Machine Vision Systems Offer High Accuracy in Critical Activities Such as Bin Picking and Positioning of Parts for Assembly
9.3 Electronics & Semiconductor
9.3.1 The Main Objectives of Deploying Machine Vision Systems are to Improve Product Quality and Increase Production Volume in A Short Period of Time
9.4 Consumer Electronics
9.4.1 2D and 3D Machine Vision Systems are Emerging as Powerful Technologies for Electronics Assembly Applications.
9.5 Glass
9.5.1 Modern Machine Vision Technology Improves Operational Efficiency, Traces Defects, Reduces Wastage, and Provides Detailed Statistical Information
9.6 Metals
9.6.1 The Machine Vision System Enhances Product Quality By 3D Inspection and Can Be Easily Incorporated Into Existing Manufacturing Systems to Enhance the Quality of the Overall Production Process
9.7 Wood & Paper
9.7.1 Machine Vision Systems Can Work Efficiently in Different Environmental Conditions, Such as Wood Dust, Heat, Smoke, Water, and Chemicals.
9.8 Pharmaceuticals
9.8.1 Machine Vision Systems are Used in Detecting Defects to Ensure Product Quality.
9.9 Food & Packaging
9.9.1 Food
9.9.1.1 The Machine Vision Systems are Pre-Trained With the Required Algorithms, Which Help Them Understand Characteristics Such as Size, Stage of Growth, and Variety
9.9.2 Packaging
9.9.2.1 Machine Vision Helps in the Inspection of Packaging Processes and Reduction of Errors By Carrying Out Multiple Inspections at A Single Time
9.10 Rubber & Plastics
9.10.1 The Machine Vision Systems are Designed to Examine and Evaluate Parts and Determine If the Parts are Good, Bad, Or Undefined.
9.11 Printing
9.11.1 Machine Vision Systems Used in Digital Printing Applications Check for Readable Texts and the Correct Number of Collated Pages Based on Individual Recipients as Well as to Ensure That the Right Pages are Used in the Right Envelopes
9.12 Machinery
9.12.1 Machine Vision Systems Help in Completing Processes Much Faster and Also Help in Detecting Defects and Validating Quality
9.13 Solar Panel Manufacturing
9.13.1 Industrial Machine Vision-Based Inspection is an Important Tool for Inspecting the Quality of Solar Panels.
9.14 Textiles
9.14.1 Machine Vision Systems Help Manufacturers Produce High-Quality Textiles While Minimizing the Costs and Maximizing the Profits

10 Geographic Analysis
10.1 Introduction
10.2 North America
10.3 Europe
10.4 Asia Pacific (APAC)
10.5 Rest of the World (RoW)

11 Competitive Landscape
11.1 Overview
11.2 Key Players in the Market
11.3 Competitive Leadership Mapping
11.3.1 Visionary Leaders
11.3.2 Dynamic Differentiators
11.3.3 Innovators
11.3.4 Emerging Companies
11.3.5 Competitive Leadership Mapping for Market (2018)
11.4 Competitive Benchmarking
11.4.1 Strength of Product Portfolio (25 Companies)
11.5.2 Business Strategy Excellence (25 Companies)
11.5 Competitive Scenario
11.5.1 Product Launches and Developments
11.5.2 Partnerships, Collaborations, and Agreements
11.5.3 Mergers & Acquisitions

12 Company Profile
12.1 Key Players
12.1.1 Cognex
12.1.1.1 Business Overview
12.1.1.2 Products Offered
12.1.1.3 Recent Developments
12.1.1.4 SWOT Analysis
12.1.2 Basler
12.1.3 Omron
12.1.4 Keyence
12.1.5 National Instruments
12.1.6 Sony
12.1.7 Teledyne Technologies
12.1.8 Texas Instruments
12.1.9 Intel
12.1.10 Baumer Optronic
12.1.11 Jai A/S
12.1.12 Mvtec Software
12.1.13 Tordivel A/S
12.1.14 ISRA Vision
12.1.15 Sick
12.1.16 FLIR Systems
12.2 Startup-Ecosystem
12.2.1 Ametek
12.2.2 Qualitas Technologies
12.2.3 Sualab
12.2.4 Algolux
12.2.5 Clarifai
12.2.6 Cadence Design Systems
12.2.7 Inuitive

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