|
Forecast
Period
|
2024-2028
|
|
Market
Size (2022)
|
USD
12.84 Billion
|
|
CAGR
(2023-2028)
|
14.20%
|
|
Fastest
Growing Segment
|
Automotive
|
|
Largest
Market
|
North
America
|
Market Overview
Global 2D & 3D Machine Vision Systems Market
has valued at USD 12.84 Billion in 2022 and is anticipated to project robust
growth in the forecast period with a CAGR of 14.20% through 2028. Machine
vision provides machines with a gift of sight, complementing or replacing
manual inspection tasks, using cameras and image processing. Machine vision
applications range from basic tasks, like presence detection, to real-time
inspection and grading tasks in harsh environments.
Manufacturing firms worldwide realize the benefits
of machine vision systems, particularly in areas where redundant tasks, like
inspection, should be performed with precision. They are playing an essential
role in high-speed production lines and hazardous environments. Some of the
significant benefits offered by these systems include increased productivity,
reduced machine downtime, and tighter process control.
Key Market Drivers
Automation and Industry 4.0
Automation and Industry 4.0 are two powerful forces
that are driving the rapid growth of the 2D and 3D machine vision systems
market. These transformative trends are reshaping industries across the globe,
and machine vision systems play a pivotal role in enabling the vision of a
highly automated and interconnected future. Industry 4.0, often referred to as
the fourth industrial revolution, is characterized by the integration of
digital technologies, data analytics, and automation into manufacturing and industrial
processes. It represents a shift towards more intelligent, connected, and
efficient production systems. As industries embrace Industry 4.0 principles,
the demand for advanced machine vision systems is soaring.
One of the primary drivers of the market is the
need for enhanced automation. Manufacturers are increasingly adopting robotic
systems to carry out tasks that were once performed by humans. Machine vision
systems are the eyes of these robots, allowing them to "see" and
understand their environment. This enables robots to work safely alongside
humans, handle complex tasks with precision, and adapt to changing conditions.
Whether it's in automotive assembly lines, logistics warehouses, or
pharmaceutical manufacturing, machine vision is a cornerstone of automation.
Moreover, Industry 4.0 emphasizes data-driven decision-making. Machine vision
systems are not just about automation but also about gathering critical data
from visual inputs. These systems can collect vast amounts of data in
real-time, enabling predictive maintenance, process optimization, and quality
control. This data-driven approach is vital for achieving efficiency, reducing
downtime, and ensuring consistent product quality.
Another aspect of Industry 4.0 is the
interconnectedness of machines and systems through the Industrial Internet of
Things (IIoT). Machine vision systems are often integrated with IIoT platforms,
enabling remote monitoring and control of manufacturing processes. This
connectivity enhances the agility and responsiveness of industries to changing
market demands. In conclusion, the symbiotic relationship between automation
and Industry 4.0 is propelling the 2D and 3D machine vision systems market to
new heights. As industries strive for greater efficiency, productivity, and
data-driven insights, machine vision technology is emerging as an indispensable
tool to achieve these goals. The future of manufacturing and industrial
processes is increasingly reliant on the vision systems that enable machines to
perceive and act in the world, making them a cornerstone of the fourth
industrial revolution.
Increased Demand for Robotics
The increased demand for robotics is a significant
driver propelling the growth of the 2D and 3D machine vision systems market.
Robotics, across various industries, is undergoing a remarkable transformation,
with machines increasingly taking on tasks that require vision and perception
capabilities. Machine vision systems are at the core of this transformation,
playing a pivotal role in enhancing the functionality and efficiency of robots.
Robotic systems are becoming increasingly versatile and intelligent, thanks to
advancements in machine vision technology. These systems are now capable of
"seeing" and understanding their surroundings, which is crucial for
tasks like object recognition, navigation, and interaction with humans and
objects. Whether it's in manufacturing, logistics, healthcare, or agriculture,
robots equipped with machine vision are becoming indispensable.
In manufacturing, robots are used for tasks such as
pick-and-place, assembly, and quality control. Machine vision systems enable
robots to precisely identify and manipulate objects on the assembly line,
ensuring accuracy and consistency. They can also inspect products for defects,
leading to improved quality control and reduced waste. As manufacturers embrace
automation, the demand for machine vision systems to enhance robotic
capabilities is on the rise. The logistics and e-commerce sectors are witnessing
a surge in demand for automation to handle order fulfillment and warehouse
operations efficiently. Autonomous mobile robots (AMRs) equipped with machine
vision sensors can navigate through complex environments, avoid obstacles, and
pick items from shelves accurately. This not only increases productivity but
also reduces labor costs.
In healthcare, robots are used in surgery,
diagnostics, and patient care. Machine vision systems help these robots perform
delicate procedures with precision and safety. They can also assist in tasks
like medication dispensing and patient monitoring. Agriculture is another
sector experiencing a robotics revolution. Autonomous agricultural robots
equipped with machine vision can perform tasks like planting, harvesting, and
weed control with greater precision, reducing the need for manual labor and
increasing crop yields. Overall, the increased demand for robotics is driving
the adoption of 2D and 3D machine vision systems. These systems empower robots
with the ability to perceive their environment, make decisions, and perform
tasks accurately and efficiently. As industries continue to recognize the value
of automation and robotics in improving productivity and reducing costs, the
market for machine vision systems is poised for significant growth in the
coming years.
Rapid
Technological Advancements
Rapid technological advancements are serving as a
powerful catalyst for the growth and evolution of the 2D and 3D machine vision
systems market. These advancements are transforming the landscape of machine
vision, making these systems more capable, versatile, and accessible across a
wide range of industries and applications. One of the key drivers of
technological advancement in machine vision is the continuous improvement in
sensors and cameras. The development of high-resolution, low-noise sensors and
cameras enables machine vision systems to capture and process clearer and more
detailed images. This enhancement is particularly crucial for applications that
require precise measurement, defect detection, and quality control.
Image processing algorithms are another area where
rapid progress is occurring. Advanced algorithms, often based on artificial
intelligence (AI) and deep learning techniques, allow machine vision systems to
interpret and analyze images more intelligently. This results in greater
accuracy and the ability to recognize and categorize objects and defects with
unprecedented speed and precision. 3D machine vision technology, in particular,
has benefited significantly from technological advancements. The introduction
of 3D sensors, such as time-of-flight and structured light cameras, has enabled
machines to perceive depth and shape, making them invaluable for tasks like bin
picking, robotic navigation, and volumetric measurements.
Furthermore, the integration of machine vision with
other emerging technologies like augmented reality (AR) and virtual reality
(VR) is expanding the scope of applications. These combinations create
immersive environments where machine vision systems can provide real-time
information and enhance human-machine interaction. Miniaturization and cost
reduction have also been key drivers. Smaller, more affordable components make
it possible to deploy machine vision systems in a wider range of settings,
including mobile devices, wearable technology, and consumer electronics. This
accessibility is fostering innovation in areas such as autonomous vehicles,
augmented reality glasses, and smart appliances.
Additionally, the rapid growth of edge computing
capabilities is allowing machine vision systems to process data locally,
reducing latency and enabling real-time decision-making in applications like
autonomous vehicles and industrial automation. In conclusion, rapid
technological advancements are revolutionizing the 2D and 3D machine vision
systems market. These innovations are increasing the capabilities,
affordability, and adaptability of machine vision technology, which, in turn,
is driving its adoption across numerous industries. As industries continue to
harness the power of machine vision for automation, quality control, and
data-driven decision-making, the market for these systems is poised for
continued growth and innovation.
Download Free Sample Report
Key Market Challenges
Cost of Implementation
The cost of implementation is a significant
challenge that can potentially hamper the growth of the global 2D and 3D
machine vision systems market. While these systems offer a wide range of
benefits, the initial investment required to deploy them can be a barrier,
particularly for small and medium-sized enterprises (SMEs) and businesses with
limited budgets. High Initial Capital Investment: Acquiring the hardware and
software components necessary for 2D and 3D machine vision systems can be
expensive. This includes the cost of cameras, sensors, lighting equipment,
processing units, and specialized software. The total cost can vary widely
depending on the complexity and scale of the application.
Integration Costs: In addition to the hardware and
software costs, integrating machine vision systems into existing production
lines can incur additional expenses. This may involve retrofitting or modifying
machinery to accommodate the new technology, as well as hiring or training
personnel with expertise in machine vision. Customization Costs: Many
applications require customized machine vision solutions to meet specific
requirements. Developing and implementing these custom solutions can add to the
overall cost, as they often involve tailored software development and system
calibration. Maintenance and Support Costs: Machine vision systems require
ongoing maintenance to ensure they operate at peak performance. Regular
calibration, software updates, and hardware maintenance can contribute to the
total cost of ownership over time. Businesses also need to budget for technical
support and training to keep their staff proficient in operating the systems.
Economies of Scale: Larger enterprises with higher
production volumes can often justify the investment in machine vision
technology more easily than smaller businesses. They can spread the cost over a
larger number of units or products, making the return on investment (ROI) more
attractive. ROI Uncertainty: Demonstrating a clear and timely return on
investment can be challenging, especially for businesses that are new to
machine vision technology. Calculating ROI depends on factors like increased
productivity, reduced defects, and cost savings, which may not be immediately
evident.
Competitive Pricing Pressure: In some industries,
there may be competitive pressures to keep product prices low. This can limit a
company's ability to invest in costly machine vision systems, even if they
would improve product quality and efficiency in the long run. Despite these
challenges, it's important to note that the cost landscape of machine vision
technology is evolving. Advances in hardware miniaturization, increased
competition among technology providers, and economies of scale are gradually reducing
the cost of implementation. Moreover, as the technology matures and becomes
more widely adopted, the benefits of improved quality control, automation, and
data analytics often outweigh the initial investment, making machine vision
systems a strategic choice for many businesses seeking to remain competitive in
the modern industrial landscape.
Lack of Skilled Workforce
The lack of a skilled workforce poses a significant
challenge that could potentially hamper the growth of the global 2D and 3D
machine vision systems market. Machine vision technology is becoming
increasingly sophisticated, and its successful implementation and operation
require individuals with specific skills and knowledge. The shortage of
qualified personnel can impede the adoption and utilization of these systems in
various industries and applications. Complexity of Machine Vision Technology:
Machine vision systems involve intricate components such as cameras, sensors,
image processing software, and often require calibration and programming.
Skilled technicians and engineers are needed to design, set up, and maintain
these systems effectively.
Shortage of Machine Vision Experts: There is a
notable scarcity of professionals with expertise in machine vision technology,
as it requires a unique blend of skills in computer vision, image processing,
programming, and hardware integration. Finding and hiring such individuals can
be challenging for companies looking to implement these systems. High Demand
for Skilled Personnel: The increasing demand for skilled machine vision experts
is driven by the growing adoption of automation and Industry 4.0 practices
across various industries. This heightened competition for qualified talent can
result in higher labor costs. Training and Retention: Companies that do invest
in training their workforce in machine vision technology may face challenges in
retaining these skilled employees. Highly trained personnel are often sought
after by other organizations, which can lead to talent turnover.
Diverse Applications: Machine vision is used across
a wide range of industries, including manufacturing, healthcare, automotive,
agriculture, and more. Each application may require specialized knowledge and
experience, further complicating the recruitment process. Rapid Technological
Advancements: The rapid pace of technological change in the field of machine
vision means that skilled workers need to continually update their knowledge
and skills to stay current. This ongoing learning curve adds to the challenges
of finding and retaining qualified personnel.
Global Competition: The global nature of the
machine vision market means that companies may need to compete on a global scale
to attract skilled talent. This can drive up labor costs and make it even more
challenging for smaller companies to access the necessary expertise. Addressing
the lack of a skilled workforce in the machine vision industry requires a
multi-pronged approach. This includes investing in education and training
programs, fostering partnerships between educational institutions and
businesses, and promoting the development of machine vision-related courses and
certifications. Additionally, companies may need to offer competitive
compensation packages and opportunities for career growth to attract and retain
skilled professionals. Overcoming this workforce challenge is essential to
unlock the full potential of 2D and 3D machine vision systems in various sectors,
enabling businesses to enhance automation, quality control, and data-driven
decision-making.
Key Market Trends
Integration of AI and Deep Learning
The integration of artificial intelligence (AI) and
deep learning is a driving force behind the growth of the global 2D and 3D
machine vision systems market. This integration is revolutionizing machine
vision technology, making systems smarter, more adaptable, and capable of
addressing complex real-world challenges. AI and deep learning algorithms
empower machine vision systems to process and interpret visual data with
remarkable accuracy and speed. Here's how they are driving the market, Advanced
Image Recognition: AI and deep learning algorithms excel at recognizing
patterns and objects within images. They enable machine vision systems to
identify and classify objects, defects, and anomalies with a level of precision
that was previously challenging to achieve.
Enhanced Decision-Making: These technologies enable
machine vision systems to make real-time decisions based on the visual data
they capture. This is invaluable in applications like autonomous vehicles,
where AI-powered machine vision systems can identify obstacles, pedestrians,
and road signs, enabling safe navigation. Object Tracking: AI and deep learning
models can track objects' movements and predict their trajectories. This
capability is vital in surveillance, robotics, and logistics, where tracking moving
objects is essential for safety and efficiency. Improved Quality Control: In
manufacturing, AI-driven machine vision systems can detect even subtle defects
in products, leading to enhanced quality control and reduced production errors.
Flexible Adaptation: Deep learning models can adapt
to changing conditions and environments. This adaptability is particularly
valuable in robotics and automation, where machines need to handle diverse and
unpredictable situations. Reduced False Alarms: By learning from historical
data, machine vision systems equipped with AI can reduce false alarms and
identify real issues more accurately, minimizing disruptions and improving
overall efficiency.
Customization and Versatility: AI-driven machine
vision solutions can be customized for specific applications and industries,
making them versatile tools for a wide range of use cases. In conclusion, the
integration of AI and deep learning is propelling the 2D and 3D machine vision
systems market forward. These technologies are unlocking new possibilities for
automation, quality control, and data-driven decision-making across industries,
making machine vision systems indispensable in the era of Industry 4.0 and
beyond. As AI and deep learning continue to advance, we can expect even more
sophisticated and capable machine vision systems to drive innovation and growth
in various sectors.
3D Vision Technology Advancements
3D vision technology advancements are poised to be
a driving force behind the global 2D and 3D machine vision systems market.
These advancements represent a transformative leap in the capabilities and
applications of machine vision, offering a depth and precision that was
previously unattainable with traditional 2D systems. One of the key advantages
of 3D vision technology is its ability to provide accurate depth perception.
Recent innovations in 3D sensors, such as time-of-flight and structured light cameras,
have enabled machine vision systems to create detailed and reliable 3D
reconstructions of objects and environments. This depth perception is
invaluable in applications such as robotics, where machines need to interact
with their surroundings in a highly precise manner.
Moreover, 3D vision technology enhances object
recognition capabilities, allowing machines to not only identify objects but
also assess their shape, size, and orientation in three dimensions. This
capability has broad implications across industries, from manufacturing and
automotive quality control to logistics and healthcare. Additionally, 3D vision
advancements are driving improvements in robotics, enabling robots to navigate
complex and dynamic environments more effectively. This is particularly relevant
in applications like autonomous vehicles, where 3D vision is fundamental for
obstacle detection and avoidance. As 3D vision technology continues to evolve
and become more accessible, it is set to revolutionize industries, enhance
automation, and open up new opportunities for innovation, making it a key
driver in the global machine vision systems market's growth and development.
Segmental Insights
End-user Industry Insights
Food and Beverages segment
dominated in the market. The food and beverage sector is one of the most
significant markets for machine vision systems owing to growing safety culture
and stringent government regulations forcing companies to adopt advance inspection
procedures as a part of automation.
The uniform and systematic
application of machine vision in the food industry over the past decade is
mainly attributed to continual developments in constituent methodologies, such
as image processing and pattern recognition. Moreover, technological advancements
have permitted feasible implementation of these machines at lower cost.
Inspection of food (concerned predominantly with defects or contaminants),
quality control, and in some cases, assembly control of more complex foods
(pizzas and layer cakes) during the processing of food are some of the major
areas of scope where the machine vision systems find applications.
Download Free Sample Report
Regional Insights
North America is expected to dominate the market
during the forecast period. North America is a developed region with a
well-established infrastructure, North
America is a substantial market for vendors offering solutions for machine
vision. The regional market is expected to grow significantly over the forecast
period, owing to the early adoption of automation in the manufacturing and
healthcare industries.
In North America, the sales of machine vision
components and systems that provide vision intelligence to robots and other
machines increased significantly in 2018, according to AIA, the industry trade
group, and part of the Association for Advancing Automation (A3).
In July 2019, Microchip Technology Corporation
introduced its Smart Embedded Vision Initiative. The new ecosystem utilizes
Microchip’s low-power PolarFireFPGAs with a series of high-speed imaging
interfaces, intellectual property for image processing, and an enhanced
ecosystem of outside partnerships. This initiative is designed to bolster
machine vision advances for applications such as industrial, medical devices,
automotive, and aerospace.
Recent Developments
- April 2020 - Cognex Corporation introduced the
In-Sight D900 embedded vision system. A first-of-its kind solution, the
In-Sight D900 features Cognex’s ViDideep learning software inside an In-Sight
industrial-grade smart camera. The self-contained system is designed to solve a
broad range of complex in-line inspection applications including optical
character recognition (OCR), assembly verification, and defect detection.
- August 2019 - IDS planned to expand its USB3 vision
camera range by more than 100 models. This means it will integrate the entire
range of sony sensors which are already available with GigE Vision. The new
cameras can be used with IDS peak, IDS brand-new, hardware-independent SDK..
Key Market Players
- Cognex Corporation
- Keyence
Corporation
- Omron
Corporation
- ISRA
Vision AG
- IDS
Imaging Development Systems GmbH
- National
Instruments Corporation
- MVTec
Software GmbH
- Sony
Corporation
- Teledyne
DALSA
- Toshiba
Corporation
|
By Component
|
By Product
|
By End user Industry
|
By Region
|
|
|
- PC-based
- Smart Camera-based
|
- Food and Beverage
- Medical Devices
- Pharmaceutical
- Automotive
- Electronics and Semiconductors
- Other
|
- North America
- Europe
- South America
- Middle East & Africa
- Asia Pacific
|
|
Report Scope:
In this report, the Global 2D & 3D Machine
Vision Systems Market has been segmented into the following categories, in
addition to the industry trends which have also been detailed below:
- Global 2D & 3D Machine Vision Systems
Market, By
Component:
o
Hardware
o
Software
- Global
2D & 3D Machine Vision Systems Market, By
Product:
o PC-based
o Smart Camera-based
- Global 2D & 3D Machine Vision Systems
Market, By End user Industry:
o Food and Beverage
o Medical Devices
o Pharmaceutical
o Automotive
o Electronics and Semiconductors
o Other
- Global 2D & 3D Machine Vision Systems
Market, By Region:
o North America
§ United States
§ Canada
§ Mexico
o Asia-Pacific
§ China
§ India
§ Japan
§ South Korea
§ Indonesia
o Europe
§ Germany
§ United Kingdom
§ France
§ Russia
§ Spain
o South America
§ Brazil
§ Argentina
o Middle East & Africa
§ Saudi Arabia
§ South Africa
§ Egypt
§ UAE
§ Israel
Competitive Landscape
Company Profiles: Detailed analysis of the major companies presents in the Global 2D
& 3D Machine Vision Systems Market.
Available Customizations:
Global 2D & 3D Machine Vision Systems Market
report with the given market data, Tech Sci Research offers customizations
according to a company's specific needs. The following customization options
are available for the report:
Company Information
- Detailed analysis and profiling of additional
market players (up to five).
Global 2D & 3D Machine Vision Systems Market is
an upcoming report to be released soon. If you wish an early delivery of this
report or want to confirm the date of release, please contact us at [email protected]