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Report ID: ICT0006
Pages: 170
Base Year: 2023
Format: PDF
Historical Date: 2019-2022
MARKET SCOPE:
The global 3C Smart Robot market is projected to grow significantly, registering a CAGR of 7.1% during the forecast period (2024 – 2032).
A smart robot refers to a robotic system equipped with advanced technologies, including artificial intelligence (AI), machine learning, sensors, and connectivity, that enable it to perform tasks autonomously and adapt to changing environments. These robots have the ability to perceive their surroundings, make decisions based on data analysis, and execute tasks without constant human intervention. The term “smart” implies a higher level of intelligence, flexibility, and responsiveness compared to traditional robots In industrial settings, smart robots are used for tasks such as assembly, welding, and material handling to increase efficiency and precision. Smart robots play a crucial role in automating material handling processes in warehouses and distribution centers, improving order fulfillment. In healthcare, smart robots are employed in surgery assistance, rehabilitation, and patient care to enhance precision and provide support to medical professionals.
MARKET OVERVIEW:
Driver: Rising E-commerce and logistics trend is driving the market growth.
The growth of e-commerce and changes in consumer buying behavior drive the need for efficient logistics solutions. Smart robots equipped with navigation and communication capabilities can optimize warehouse operations and last-mile delivery. The growth of e-commerce and shifts in consumer buying behavior have significantly influenced the logistics landscape, leading to an increased demand for efficient and innovative solutions. Smart robots, equipped with advanced navigation and communication capabilities, play a crucial role in optimizing various aspects of e-commerce and logistics operations.
Opportunities: Advancements in AI and connectivity is anticipated for the market growth in the upcoming years.
AI algorithms enable robots to perceive and interpret their surroundings more effectively. This includes image recognition, object detection, and understanding spatial relationships, allowing robots to navigate complex environments. Machine learning algorithms, a subset of AI, empower robots to learn from experience. This adaptability allows robots to improve their performance over time, refine their actions based on feedback, and handle a wider range of tasks without explicit programming. AI-driven decision-making enables robots to make complex choices in real-time. Whether it’s navigating through obstacles, optimizing paths, or responding to dynamic changes in the environment, AI enhances a robot’s ability to make informed decisions. AI-driven automation allows robots to autonomously perform tasks without constant human intervention. This is particularly valuable in industrial settings, where robots can execute repetitive and precise tasks with efficiency.
COVID IMPACT:
The robotics industry, like many others, experienced disruptions in the supply chain due to factory closures, restrictions on movement, and logistics challenges. This affected the production and availability of robotic components and systems. The demand for certain types of robots, especially those used in industries heavily impacted by the pandemic (e.g., manufacturing, logistics), may have experienced fluctuations. On the other hand, there could be increased interest in robots used for tasks such as cleaning, disinfection, and automation in healthcare. Some robots found new applications in responding to the challenges posed by the pandemic. For instance, robots were deployed for tasks like disinfection in public spaces, delivering medical supplies, and supporting healthcare professionals. The need for social distancing and reducing human contact in certain industries accelerated the adoption of automation and robotics. This trend was particularly notable in manufacturing and logistics to ensure continuity amid workforce challenges. Research and development activities in robotics may have faced delays or adjustments due to restrictions on physical workspaces and the reprioritization of projects.
SEGMENTATION ANALYSIS:
Handling Robot segment is anticipated to grow significantly during the forecast period
A handling robot, often referred to as an industrial or material handling robot, is a type of robot designed for tasks related to material handling and manipulation within an industrial setting. In some cases, a robot can exhibit characteristics of both handling and smart robots. For example, an industrial robot in a smart manufacturing environment might incorporate AI for adaptive control, connectivity for remote monitoring, and precise handling capabilities for assembly tasks. The integration of smart technologies into handling robots enhances their capabilities, making them more adaptable to changing conditions and providing opportunities for advanced applications in the era of Industry 4.0 and smart manufacturing.
Computer segment is anticipated to grow significantly during the forecast period
The computer serves as the central processing unit (CPU) for the smart robot. It processes information received from sensors, makes decisions based on programmed algorithms or artificial intelligence (AI), and sends commands to the robot’s actuators for motion and task execution. Smart robots are equipped with various sensors, such as cameras, lidar, ultrasonic sensors, and more. These sensors gather data about the robot’s surroundings. The computer processes this sensory information to create a real-time understanding of the environment. The computer can be equipped with AI and machine learning capabilities to enable the smart robot to learn from its experiences, adapt to new situations, and improve its performance over time. This is particularly valuable in applications where the robot needs to navigate complex environments or learn specific tasks. The computer is responsible for task planning and coordination. It determines how the robot should move and interact with its environment to achieve predefined objectives. This includes path planning, obstacle avoidance, and manipulation tasks.
REGIONAL ANALYSIS:
The Asia Pacific region is set to witness significant growth during the forecast period.
The Asia Pacific region is known for being a hub of technological innovation, manufacturing, and adoption. Countries such as China, Japan, South Korea, and Taiwan play significant roles in the development and deployment of robotics and smart technologies. China has emerged as a global leader in technology and innovation. The country is a major player in manufacturing and is home to some of the world’s largest technology companies. Chinese companies are at the forefront of developments in areas like artificial intelligence, 5G technology, robotics, and e-commerce. Japan has a long history of technological innovation and is known for its advancements in robotics, electronics, and automotive industries. Japanese companies are pioneers in industrial robotics, and the country continues to invest in research and development in emerging technologies. South Korea is renowned for its contributions to the electronics and semiconductor industries. Companies like Samsung and LG are global leaders in the production of smartphones, televisions, and other consumer electronics. South Korea is also actively involved in the development of robotics and automation technologies.
COMPETITIVE ANALYSIS
The global 3C Smart Robot market is reasonably competitive with mergers, acquisitions, and Type launches. See some of the major key players in the market.
In 2023, Sustainable Innovation is Driven by Yamakawa India at CII’s Green Cementech 2023. YASKAWA India Private Limited demonstrated its steadfast dedication to promoting World-Class Energy Efficiency measures within the cement sector at Green Cementech 2023, an event hosted by the Confederation of Indian sector (CII) in Hyderabad this May. The occasion provided a crucial stage for highlighting YASKAWA’s contribution to encouraging sectors to become more sustainable, cutting energy use, and helping to reach NET zero targets.
In 2023, ABB introduces the IRB 930 SCARA robot to revolutionize assembly and pick-and-place processes. Designed to meet growth opportunities in key markets including electronics, automotive and renewable energy production
Scope of the Report
** In – depth qualitative analysis will be provided in the final report subject to market
Primary and Secondary Research
In order to understand the market in detail we conduct primary and secondary research. We collect as much information as we can from the market experts through primary research. We contact the experts from both demand and supply side and conduct interviews to understand the actual market scenario. In secondary research, we study and gather the data from various secondary sources such as company annual reports, press releases, whitepapers, paid databases, journals, and many other online sources. With the help of the primary interviews, we validate the data collected from secondary sources and get a deep understanding on the subject matter. Post this our team uses statistical tools to analyses the data to arrive at a conclusion and draft it in presentable manner.
Market Size Estimations
Understanding and presenting the data collected is a crucial task. Market sizing is a critical part of the data analysis and this task is performed by using Top-down and bottom-up approaches. In this process, we place different data points, market information and industry trends at a suitable space. This placement helps us presume the estimated & forecast values for coming few years. We use several mathematical and statistical models to estimate the market sizes of different countries and segments. Each of this is further added up to outline the total market. These approaches are individually done on regional/country and segment level.
Data Triangulation
As we arrive at the total market sizes, the market is again broken down into segments and subsegments. This process is called as data triangulation and is implementable wherever applicable. This step not only helps us conclude the overall market engineering process, but also gives an assurance on accuracy of the data generated. The data is triangulated based on studying the market trends, various growth factors, and aspects of both demand and supply side.