到2045年,协作机器人的市场规模将达到700亿美元左右

2025年-2045年协作机器人:技术、参与者和市场

协作机器人(cobots)、移动作业机器人、末端效应器、传感器、抓手、汽车制造、拣选和放置、码垛、包装、食品和饮料、电子、电动汽车锂离子电池


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得益于低资本投入门槛、编程便捷性以及日益增强的人机协同能力,协作机器人正变得流行起来。本报告全面讨论了协作机器人在多个终端行业中的关键应用,涉及汽车制造、半导体生产、电动汽车电池回收、食品与饮料加工、电子制造、医疗保健服务、酒店业、半导体等领域以及拣选与放置、机器维护、货物码垛、产品包装、质量检测以及物料搬运等一系列终端任务。
该报告提供以下信息:技术趋势与协作机器人参与者分析:
  • 市场领导者和小型新兴初创企业
  • 领先协作机器人制造商的详细概述
  • 详细的价格、负载和范围比较。
  • 不同商用协作机器人的基准研究。
  • 终端行业和任务中协作机器人的使用概述。
  • 汽车制造业的详细区域SWOT分析以及协作机器人如何帮助他们克服挑战。
  • 法规分析(如工业5.0、中国制造2025、智能工厂2025等)以及领先汽车制造公司的提案,这些将如何加速协作机器人的采用。
  • 食品和饮料行业中协作机器人的详细分析。分析高混合低批量模型以及协作机器人如何用于包装、码垛等。
  • 电子行业中协作机器人的前景,涵盖多个案例研究和大型电子供应商的投资分析。
  • 酒店和医疗保健行业中协作机器人的分析。
  • 电动汽车锂离子电池回收行业中协作机器人的分析,包括案例研究和典型协作机器人在电池拆解中的步骤。
  • 光伏行业中协作机器人的分析。
  • 拣选与放置、材料处理、质量检查等任务中协作机器人的分析,以及投资回报期和ROI的基准。
  • 协作机器人采用障碍及其潜在解决方案的分析。
  • 向移动协作机器人发展的趋势及当前技术障碍,以及协作机器人制造商与移动机器人制造商之间的合作趋势。
  • 末端执行器(如夹持器、传感器、打磨工具等)的分析,以及多个领先末端执行器供应商的简介。
  • 协作机器人中的感应系统分析及增强安全水平的新兴传感器。
  • 协作机器人中的人工智能分析,如计算机视觉、自然语言处理(语音识别)等。
  • 提供协作机器人组件供应商概况及两大控制器供应商NVIDIA和AMD的分析。
  • 来自关键公司简介的主要信息。
市场预测与分析:
  • 协作机器人销量和收入的20年市场预测。
  • 不同地区市场(亚太地区、北美、欧洲及其他地区)的20年市场预测。
  • 协作机器人末端执行器的20年预测。
  • 汽车制造业中协作机器人销售量的20年预测。
  • 按12个任务在不同行业中的体积销售和收入的20年详细分析。
  • 芯片质量检测用协作机器人销售量的20年市场预测
  • 汽车装配和表面处理用协作机器人销售量的20年市场预测。
 
报告涵盖的主要内容:
执行摘要
引言
工业5.0
 
协作机器人参与者与基准测试
  • ABB
  • Airskin
  • AMD Xilinx
  • Bruker Alicona
  • Denso
  • Dobot
  • F&P Personal Robotics
  • Franka Emika
  • JAKA
  • Kawasaki
  • Neura Robotics
  • NVIDIA
  • Omron
  • OnRobot
  • Robotiq
  • Robotnik
  • Schmalz
  • Tacterion
  • Techman Robot
  • Universal Robot
  • Vikaso
  • Yaskawa
 
按行业划分的协作机器人
  • 汽车行业,分为装配(如焊接、仪表板组件装配等)、螺丝拧紧和表面处理
  • 食品与饮料行业,分为包装与码垛
  • 电子行业,分为手机芯片检测、手机组装、PCB组装、AR/VR检测及可穿戴设备组装
  • 酒店业
  • 锂离子电池行业制造与回收
  • 光伏行业
  • 半导体行业
  • 区域SWOT分析
  • 中小企业在多个行业中的挑战
 
按任务划分的协作机器人
  • 拣选与放置
  • 包装与码垛
  • 机器看护
  • 材料处理
  • 半导体行业质量检查
 
关键新兴技术
  • 夹持器(刚性夹持器、软性夹持器、真空夹持器、磁力夹持器等)
  • 驱动技术(电动、气动、液压等)
  • 表面加工工具
  • 传感器,包括扭矩传感器、触觉传感器、摄像头等
  • 压阻式、压电式、电容式传感器
  • 控制器
  • 协作机器人中的AI,包括Nvidia和AMD的芯片
 
OEM厂商与组件供应商列表
  • Robotiq
  • OnRobot
  • Schmalz
  • NVIDIA
  • AMD
 
移动协作机器人/移动操控器
  • 当前障碍——精度不匹配
  • 随着移动性的增加,显著潜力
 
预测
  • 按行业和任务划分的20年体积和市场规模预测(12个任务在各个行业)
  • 按地区划分的20年体积和市场规模预测(亚太地区、欧洲、北美及其他地区)
  • 市场趋势,差异化分析及机会
简介
 
Collaborative robots, a type of lightweight and slow-moving robot designed to work next to human operators without a physical fence, has gained significant momentum thanks to their flexibility and the initiatives of bringing humans back to factories, industry 5.0, made in China 2025, and many announcements from leading companies of reducing carbon footprint.
 
Collaborative robots (cobots) are ideal options for small and medium sized enterprises (SMEs) thanks to their low costs, small footprint, ease of programming, flexibility, and low power consumption. As the large companies aim to bring people back to their factories, cobots are expected to be increasingly adopted. Further, the advancement of AI, such as machine vision and voice recognition, enable additional functions and remote software updates of cobots. Traditional industries such as the automotive industry where cobots can be used for assembling dashboard components, polishing surfaces, welding, and screwing, have been the primary cobot applications. Cobots can also be used for other industries and tasks such as food and beverage, semiconductor and battery quality inspection, packaging and palletizing, and machine tending. IDTechEx's report on "Collaborative Robots 2025-2045: Technologies, Players, and Markets", takes a deep dive into the applications and industries including car assembly, surface polishing, screwing, injection molding, PC processor inspection, phone chip inspection, phone assembly, wearable device assembly, PCB assembly, packaging, and Li-ion battery industry. The report also conducts an in-depth analysis of the key enabling technologies, players, and markets with granular market size and volume forecast over the next 20 years.
 
A granular analysis of the commercially available 6 degrees of freedom cobots based on their payloads, reaches, and repeatability. Source: IDTechEx
 
Cobots have found usage across many industries. The technology and market readiness levels of cobots in these industries differ, and IDTechEx has summarized the level of maturity of cobots across different industries and tasks.
 
The automotive industry is the most prominent application of cobots. Cobots can be used for multiple tasks including car assembly (e.g., welding, assembling dashboards, etc.), surface polishing, and screwing. With the increasing popularity of electric vehicles, many existing car product lines need retrofitting or reconstruction. One of the pain points of automotive OEMs is that if one industrial robot malfunctions, the entire production line risks of getting shut down to ensure human operators can safely enter the robot working zone for inspection. This process leads to a significant downtime cost. For instance, it takes around 90 minutes to produce a Tesla model 3 at the Fremont factory, so if the production line is down for a few hours, then it will lead to a huge loss. To mitigate these potential issues, cobots can be the ideal solution as they can work closely and flexibly with human operators despite that they cannot fully replace industrial robots for heavy-duty tasks. Meanwhile, large automotive manufacturers (e.g., Audi, Volkswagen, etc.) have proposed "intelligent factories" plans where they aim to enhance the flexibility of their production by improving human-robot interaction. IDTechEx forecasts that the market size of cobots in the automotive industry will grow at a CAGR of 22% over the next 20 years.
 
Analysis of cobots market penetration by different tasks and industries. Source: IDTechEx
 
Further to the automotive industry, cobots also pose potential in other industries such as food and beverage where cobots are used for high-mix low-volume production for improved flexibility. At this stage in 2024, most of the packaging is still done manually. Although the food and beverage industry has historically not been the primary target industry for cobots, IDTechEx noticed that more cobot makers would start to use a long-tail strategy and make increasing efforts in the food and beverage industry for the next 20 years. Despite the significant market potential, IDTechEx has seen challenges such as limited budget from companies in these industries, limited technical capabilities and lack of understanding of the payback time. To mitigate this challenge, some cobot OEMs have proposed a cobot-as-a-service model where users can try first and buy later. More details are included in the "Collaborative Robots 2025-2045: Technologies, Players, and Markets" report.
 
The report also covers many other industries, including a few emerging ones such as the semiconductor industry and the Li-ion battery recycling industries. These industries have experienced significant growth over the past few years. Despite some successful examples of using cobots in semiconductor cleanrooms, such as KUKA's cobot in Infineon's cleanroom, IDTechEx has noted a few hurdles. For instance, it can be challenging to ensure that cobots meet stringent cleanliness requirements for semiconductor manufacturing environments. Current cobots may also struggle with ultra-precise tasks required in semiconductor production, necessitating further technological advancements. More challenges and future trends on cobots in the semiconductor industry can be found in the "Collaborative Robots 2025-2045: Technologies, Players, and Markets" report. Li-ion battery recycling industry, in contrast, has also seen potential of using cobots despite the low adoption rate at this stage. End-of-life battery recycling has been a significant market and is expected to grow substantially due to the increasing number of batteries being produced. However, cobots only has limited usage in this industry as of today because of the lack of standardization in battery disassembly process.
 
Further to the applications, the fundamentals of cobots lie in the technologies, such as sensors and software. Sensors are one of the most important enabling technologies for collaborative robots. The most typical sensors used in cobots for safety are torque sensors, where a range of sensor values are pre-set, and if a collision occurs, the values will exceed the range, which triggers the robot's emergency stop. However, IDTechEx has noticed a number of emerging sensors (e.g., tactile, proximity, etc.) to provide safety, but they have not been widely adopted in the markets so far.
 
End-effectors, also known as end-of-the-arm-tooling, are designed to enable robots to interact with their tasks. End-effectors can be classified as mechanical or electromechanical components depending on actuation principles. Typical end-effectors include grippers, process tools, and sensors. IDTechEx believes that the end-effector market will increase with the increasing adoption of cobots. However, since different cobots can share end-effectors, we think the end-effector market will saturate earlier than the cobot market.
 
Historic cobots market size. Source: IDTechEx
Key Aspects
 
Technology trends & cobot players analysis:
  • Market leaders and small emerging start-ups
  • Detailed overview of leading cobot manufacturers
  • Detailed price, payload, and reach comparisons.
  • Benchmarking studies between different commercially available cobots.
  • Overview of the use of cobots by end industries and tasks.
  • Detailed regional SWOT analysis of the automotive manufacturing industry and how cobots are expected to help them overcome the challenges.
  • Analysis of regulations (e.g., Industry 5.0, Made in China 2025, Smart Factory 2025, etc.) and leading car-making companies' proposals and how these will accelerate the adoption of cobots.
  • Detailed analysis of cobots in the food and beverage industry. Analysis of high mix low volume model and how cobots are used for packaging, palletizing, etc.
  • Outlook of cobots in the electronics industry covering several case studies and investment analysis of large electronics suppliers.
  • Analysis of cobots in the hospitality and healthcare industry.
  • Analysis of cobots in the EV Li-ion battery recycling industry covering case studies and steps of a typical cobot in battery disassembly.
  • Analysis of cobots in the photovoltaics industry.
  • Analysis of cobots for picking and placing, material handling, quality inspection, and the benchmark for payback time and ROI.
  • Analysis of cobot adoption barriers and potential solutions to these barriers.
  • Progression toward mobile cobots, current technological hurdles, and the trend of partnerships between cobot makers and mobile robot makers.
  • Analysis of end-effectors (e.g., grippers, sensors, sanding tools, etc.), along with several profiles of leading end-effector suppliers.
  • Analysis of sensory systems in cobots and the emerging sensors that can enhance safety levels.
  • Analysis of AI in the cobots, such as computer vision, natural language processing (voice recognition), etc.
  • Provide an overview of cobot component suppliers and an analysis of two leading cobot controller suppliers, NVIDIA and AMD.
  • Primary information from key profiled companies.
 
Market Forecasts & Analysis:
  • 20-year market forecasts for collaborative robots in volume sales and revenue.
  • 20-year market forecasts for collaborative robots in different regional markets (APAC, North America, Europe, and the Rest of the World).
  • 20-year forecast for cobot end-effectors.
  • 20-year forecast of cobot sale volume in the automotive manufacturing industry.
  • 20-year granular analysis of volume sales and revenue of collaborative robots by 12 tasks in different industries.
  • 20-year market forecast for cobot sales volume for chip quality inspection
  • 20-year market forecast for cobot sales volume for the automotive assembly and automotive surface finishing.
Report MetricsDetails
Historic Data2019 - 2024
CAGRThe global market of cobots is expected to grow by a CAGR of 22.8% over the next 20 years
Forecast Period2025 - 2045
Forecast UnitsUS$, Unit (thousands)
Regions CoveredAll Asia-Pacific, Europe, North America (USA + Canada)
Segments CoveredMobile cobots, cobots in automotive, semiconductor, EV Li-ion battery, photovoltaics, food and beverage, electronics, hospitality and healthcare, picking and placing, palletizing, packaging, material handling, and quality inspection. End-effectors, sensors, and AI software for collaborative robots.
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Table of Contents
1.EXECUTIVE SUMMARY
1.1.Collaborative robots (Cobots)
1.2.Three phases of cobot adoption
1.3.6 stages of human-robot interaction (HRI)
1.4.Traditional industrial robots vs. collaborative robots
1.5.Benefits of industrial robots vs. collaborative robots
1.6.Benefits of cobots - key takeaways
1.7.Drawbacks of cobots - key takeaways
1.8.Safety requirement for cobots - five main types
1.9.Cobot market size forecast by 12 end-user industries: 2025-2045
1.10.Cobot market size forecast tables by 12 industries and tasks: 2025-2045
1.11.Cobot volume forecast by end-user tasks and industries: 2025-2045
1.12.Cobot volume forecast tables by end-user industry and task: 2025-2045
1.13.Cobot volume forecast by task: 2025-2045
1.14.Cobot volume forecast table by task: 2025-2045
1.15.Overview of commercialized cobots
1.16.Overview of cobots by weight and payload
1.17.Payload Summary of Cobots
1.18.Cobot Cost Analysis
1.19.Industry 5.0 - transformative vision for EU
1.20.Robotics evolution
1.21.Collaborative robots drive industry 5.0 - future factory
1.22.Low-carbon society commitment from big robot manufacturers
1.23.Cobot historic market size: 2019-2024
1.24.Mobile cobot market size forecast: 2025-2045
1.25.Cobot volume forecast by region: 2025-2045
1.26.Cobot volume forecast table by region: 2025-2045
1.27.Categorization of end-effectors
1.28.Overview of end-effectors
1.29.Cobot end-effectors market size forecast: 2025-2045
1.30.Overview of the market - lack of differentiation and market opportunities
1.31.Roadmap of Cobots
1.32.Roadmap and Maturity Analysis of Cobots by Industry
1.33.Overview of market drivers
1.34.Overview of the OEMs and suppliers
1.35.Global competitive landscape
1.36.Differentiations of cobots
2.INTRODUCTION
2.1.Definitions of the key terms
2.2.Definitions of the key terms
2.3.Leading cobot manufacturers and recent collaboration
2.4.Typical performance and cost characteristics of collaborative robotic arms
2.5.The rise of 'collaborative' robotic arms: filling a market gap
2.6.Spacing sharing & safeguarding: traditional vs collaborative
2.7.Type of assembly operation
2.8.Six stages of human-robot collaboration
2.9.Stage One - what is not a collaborative robot?
2.10.Stage Two - what is not a collaborative robot?
2.11.Stage Three - laser scanner separation
2.12.Stage Four - shared workspace no virtual guarding
2.13.Stage Five - operators and robots working together
2.14.Stage Six - Autonomous mobile collaborative robots
2.15.Degrees of collaboration: spatial and/or temporal separation
2.16.Single or dual arms?
2.17.Safety requirement for cobots - five main types
2.18.Safety requirement - understanding biomechanical limit criteria
2.19.Safety requirement for cobots - Power and force limiting
2.20.Safety requirement for cobots - Speed and separation monitoring and safety monitored stop
2.21.Safety requirement for cobots - hand guiding
2.22.Safety requirement for cobots - soft impact design
2.23.Robot safety standards of different regions
2.24.Robot safety standards of different regions
3.COBOT PLAYERS AND BENCHMARKING
3.1.Benchmarking
3.1.1.Key terms and performances expected from cobots
3.1.2.Benchmarking of robots based on DoF, payload, weight, repeatability, reach, price, payload to weight ratio and ease of programming
3.1.3.Benchmarking of robots based on DoF, payload, weight, repeatability, reach, price, payload to weight ratio and ease of programming
3.1.4.Benchmarking of robots based on DoF, payload, weight, repeatability, reach, price, payload to weight ratio and ease of programming
3.1.5.Benchmarking of robots based on DoF, payload, weight, repeatability, reach, price, payload to weight ratio and ease of programming
3.1.6.Benchmarking of cobots - Degree of Freedom (DoF) = 6
3.1.7.Benchmarking of cobots - Degree of Freedom (DoF) = 7
3.1.8.Comparison of cobots - DoF = 6
3.1.9.Average price per cobot by company - low-cost cobots
3.1.10.Average price per cobot by company - medium-cost cobots
3.1.11.Average price per cobot by company - high-cost cobots
3.1.12.Porter's Five Force Analysis
3.2.Differentiation Analysis of Cobots
3.2.1.Lack of Differentiation Across Cobots
3.2.2.Cobot Comparison
3.2.3.How to assess the performance of cobots
3.3.Cobot Players Analysis
3.3.1.An overview of the value chain
3.3.2.Major players - Switzerland
3.3.3.Major players - Germany
3.3.4.Major players - Japan
3.3.5.Major players - USA
3.3.6.Major players - Canada
3.3.7.Major players - China
3.3.8.Major players - China
3.3.9.Major players - Others
3.3.10.ABB - YuMi
3.3.11.ABB - YuMi
3.3.12.ABB - GoFa
3.3.13.ABB - SWIFTI CRB 1100-4/0.475 and CRB 1100-4/0.58
3.3.14.KUKA - LBR iiwa series
3.3.15.KUKA - LBR iisy and iiQKA Ecosystem
3.3.16.Fanuc
3.3.17.Fanuc - CR (collaborative robots) series - CR-4iA, CR-7iA, and CR-7iA/L
3.3.18.Fanuc - CR (collaborative robots) series - CR-14iA/L, CR-15iA, CR-35iA, CRX-10iA and CRX-10iA/L
3.3.19.Aubo Robotics - i series
3.3.20.i-series - i16 and i20
3.3.21.i-series - i3, i5, and i10
3.3.22.DOBOT - CR series
3.3.23.CR3, CR5, and CR10
3.3.24.CR16 and M1 Pro
3.3.25.End-effectors and other accessories - DOBOT
3.3.26.Stäubli - TX2touch series
3.3.27.TX2touch-60 series
3.3.28.TX2touch-90 series
3.3.29.Yuanda Robotics - Yuanda robot
3.3.30.Yuanda robot - Yu
3.3.31.Universal Robots
3.3.32.Universal Robots - UR(x)e series
3.3.33.Universal Robots - UR3e
3.3.34.Universal Robots - UR5e
3.3.35.Universal Robots - UR10e
3.3.36.Universal Robots - UR16e
3.3.37.Universal Robots - UR20
3.3.38.Universal Robots - UR30
3.3.39.Universal Robots - system specifications
3.3.40.Techman Robot
3.3.41.SWOT - Techman Robot
3.3.42.Omron
3.3.43.Omron - TM5-700 and TM5X-700
3.3.44.Omron - TM5-900 and TM5X-900
3.3.45.Omron - TM12 and TM12X
3.3.46.Omron - TM14 and TM14X
3.3.47.F&P Personal Robotics
3.3.48.SWOT - F&P Personal Robotics
3.3.49.F&P Personal Robotics - P-Rob
3.3.50.F&P Personal Robotics - Lio
3.3.51.Kawasaki Heavy Industries
3.3.52.duAro series
3.3.53.Neura Robotics - Cognitive Cobots
4.COBOTS BY INDUSTRIES
4.1.Market Landscape Overview
4.1.1.Roadmap of Cobots
4.1.2.Overview of Drivers
4.1.3.Roadmap and Maturity Analysis of Cobots by Industry
4.1.4.Cobot - Technical Pain Point - Not Just a Robot but the Integration of an Entire System
4.1.5.System Integration of Cobots
4.2.Automotive Industry
4.2.1.Opportunities for collaborative robots in the automotive manufacturing industry
4.2.2.Five challenges for SMEs
4.2.3.Five challenges for SMEs
4.2.4.Challenges of automotive manufacturing
4.2.5.The trend for Audi and Volkswagen digitization
4.2.6.Fast increase of cobots usage in the upcoming decade because of policy and company strategy
4.2.7.Fast increase of cobots usage - China
4.2.8.COVID highlights the supply chain fragility and accelerate the cobot usage
4.2.9.SWOT analysis of cobots in the APAC automotive industry
4.2.10.SWOT analysis of cobots in the North American automotive industry
4.2.11.More details of applications scenarios in the automotive manufacturing industry
4.2.12.Case study: OPEL's engine assembly line with the aid of UR-cobots
4.2.13.Case study: PSA's smart factory
4.2.14.Case study: Ford - seam sealant injection
4.2.15.Case study: Zippertubing
4.2.16.Summary for automotive manufacturing
4.2.17.Robotic Charging
4.2.18.Cobot sales volume forecast in automotive industry
4.2.19.Unit sales forecast of cobots for the automotive industry
4.3.Food and Beverage Industry
4.3.1.Challenges and requirements of 21st food and Fast-Moving Consumer Goods (FMCG) industry
4.3.2.Challenges and requirements of 21st food and (FMCG) industry - key takeaways
4.3.3.SWOT analysis of cobots in the food and beverage industry - Europe
4.3.4.SWOT analysis of cobots in the food and beverage industry - Asia
4.3.5.SWOT analysis of cobots in the food and beverage industry - North America
4.3.6.Cobots for food and beverage industry are used for different purposes and tasks
4.3.7.Case study: Nortura - palletizing
4.3.8.Case study: Atria Scandinavia - packaging
4.3.9.Forecast of cobots in the food and beverage industry
4.3.10.Conclusion and outlook for cobots in the food and beverage industry
4.3.11.Conclusion and outlook for cobots in the food and beverage industry
4.4.Electronics
4.4.1.Challenges of 3C manufacturing in electronics
4.4.2.Case study - Melecs EWS
4.4.3.Main market is in China, and main tasks include picking and placing, palletizing, and quality inspection
4.4.4.Cobots volume forecast in the electronics industry: 2025-2045
4.4.5.Cobots volume forecast table in the electronics industry: 2025-2045
4.4.6.Summary for 3C manufacturing
4.5.Hospitality and healthcare
4.5.1.Challenges on the hospitality and healthcare industry
4.5.2.Cobots in the medical field
4.5.3.Cobots in the healthcare industry - key takeaways
4.6.Cobots in the Li-ion Industry
4.6.1.Overview of cobots in the Li-ion manufacturing
4.6.2.Benefits of cobots in the Li-ion manufacturing
4.6.3.TOPSIS Analysis
4.6.4.TOPSIS Analysis for Cobot Selection
4.6.5.Use Cases - Fanuc America
4.6.6.Integrating AI into cobots for better EV battery inspection
4.6.7.Li-ion battery defects detection - Nissan Leaf 2011
4.6.8.Comparison of robot and cobot capabilities for battery module inspection
4.6.9.Time Reduction Enabled by Cobots
4.6.10.Overview of cobots in the end-of-life Li-ion recycling for Nissan Leaf 2011
4.6.11.EV battery disassembly process
4.6.12.Challenges in computer vision for dismantling during disassembly
4.6.13.Technical Pain Points of Cobots in Li-ion Battery Industry
4.6.14.Commercial Pain Points of Cobots in Li-ion Battery Industry
4.6.15.Yearly Volume Forecasts of Cobots in EV Li-ion Battery: 2024-2044
4.6.16.Yearly Revenue Forecasts of Cobots in EV Li-ion Battery: 2024-2044
4.7.Cobots in the photovoltaic Industry
4.7.1.Overview of Cobots in the Photovoltaic Industry
4.7.2.Use Case - Robotic Assembly of Photovoltaic Arrays (1)
4.7.3.Use Case - Robotic Assembly of Photovoltaic Arrays (2)
4.7.4.Use Case: Cobotic welding tool for improved quality
4.7.5.Barriers and solutions of cobots in the photovoltaic industry
4.8.Cobots in the semiconductor industry
4.8.1.Emerging sector: cobots in semiconductor industry
4.8.2.Photomask Processing - Use Case
4.8.3.Cobots in cleanroom - technical requirements and barriers
4.8.4.Requirements of cobots used in cleanroom
4.8.5.Future Trends of cobots in the semiconductor industry
5.COBOTS BY TASKS
5.1.Picking and Placing
5.1.1.Picking and placing
5.1.2.Machine tending
5.1.3.Benefits and ROI for machine tending
5.1.4.Packaging and palletizing
5.1.5.Cobots volume forecast in packaging and palletizing: 2025-2045
5.1.6.Cobots market size forecast in packaging and palletizing: 2025-2045
5.2.Material Handling
5.2.1.Processing tasks
5.2.2.Finishing tasks
5.2.3.Forecast of cobots market size and volume for surface processing: 2025-2045
5.2.4.Forecast table of cobots for surface processing: 2025-2045
5.3.Quality inspection
5.3.1.Quality inspection
5.3.2.Cobots market size forecast in chip quality inspection: 2025-2045
5.4.Summary of different tasks
5.4.1.Roadmap and Maturity Analysis of Cobots by Industry
5.4.2.Payback time/ROI by tasks
5.4.3.Pain points and solutions for cobot adoption
5.4.4.Barriers for cobot adoption
6.KEY TECHNOLOGIES AND COMPONENTS IN COBOTS
6.1.Overview
6.1.1.Sensor-based control
6.1.2.Typical sensors used for collaborative robots
6.1.3.Flexible force/pressure sensors used for robotic soft grippers
6.1.4.Brief introduction of technologies for tactile sensors in soft grippers
6.1.5.Piezoresistive vs. Piezoelectric vs. Capacitive technologies
6.1.6.What are printed piezoresistive sensors?
6.1.7.What is piezoresistance?
6.1.8.SWOT: Piezoresistive sensors
6.1.9.Capacitive sensors
6.1.10.Tactile sensors
6.1.11.Capacitive proximity and tactile sensors - AIDIN Robotics
6.1.12.Time-of-flight (ToF) sensors
6.1.13.Challenges with traditional force sensors
6.1.14.Force sensing - FRANKA EMIKA
6.1.15.Robotic visual and force sensing
6.1.16.Torque sensors
6.1.17.Vision systems for cobots
6.1.18.Vision systems in robots
6.1.19.AIRSKIN
6.1.20.AIRSKIN - further details
6.1.21.SWOT - AIRSKIN
6.1.22.AIDIN Robotics
6.1.23.SWOT - AIDIN Robotics
6.1.24.Tacterion
6.1.25.SWOT - Tacterion
6.1.26.Bruker Alicona
6.1.27.SWOT - Bruker Alicona
6.1.28.FRANKA EMIKA
6.2.End-Effectors
6.2.1.What are end-effectors and how are they used in different applications?
6.2.2.Examples of the applications of end-effectors
6.2.3.How to categorize end-effectors?
6.2.4.How to categorize end-effectors?
6.2.5.How do end-effectors change the robot and cobot industry?
6.2.6.How do end-effectors change the robot and cobot industry?
6.2.7.ROBOTIQ
6.2.8.OnRobot
6.2.9.SWOT - OnRobot
6.2.10.Schmalz
6.3.Grippers
6.3.1.Grippers - categorization based on actuation types
6.3.2.Grippers with rigid fingers
6.3.3.Soft grippers
6.3.4.Actuation technologies for soft grippers
6.3.5.Comparison of rigid and soft grippers
6.3.6.Vacuum grippers
6.3.7.Vacuum grippers - suction cup selection
6.3.8.Magnetic grippers
6.3.9.Emerging technologies: tactile sensors
6.3.10.End-Effector - Suction Cups
6.4.Surface Processing Tools
6.4.1.Surface finishing
6.4.2.Surface finishing with cobots could be ideal for SMEs
6.4.3.Case study - ROBOTIQ surface finishing kit
6.5.Computing platforms
6.5.1.NVIDIA Isaac
6.5.2.AMD - SOM
6.5.3.Software and AI features - Universal Robots
6.5.4.SWOT - AMD - SOM
6.6.OEMs and Component Suppliers
6.6.1.Key components and accessories
6.6.2.Overview of the OEMs and suppliers
6.6.3.List of OEMs and suppliers
6.6.4.List of OEMs and suppliers
6.6.5.List of OEMs and suppliers
6.6.6.List of OEMs and suppliers
6.6.7.End-effectors by OEM
6.6.8.Price of end-effectors by type
6.7.Emergence of mobile cobots
6.7.1.What are mobile cobots?
6.7.2.Mobile collaborative robots - benefits
6.7.3.Mobile collaborative robots - overview of limitations
6.7.4.Applications of mobile cobots
6.7.5.Mobile cobots - gaps and mismatches in accuracy
6.7.6.Robotnik
6.7.7.Other challenges of mobile cobots
6.7.8.Collaboration of mobile robot suppliers and cobot suppliers
6.7.9.Mobile collaborative robots market size forecast: 2025-2045
6.8.Integration of AI in Cobots
6.8.1.Overview of AI-Driven Cobots
6.8.2.Cognitive Cobots - Neurac Robotics
7.TECHNICAL AND COMMERCIAL BARRIERS AND SOLUTIONS
7.1.Commercial Barrier - Metrics to Consider
7.2.Technical Barriers - Metrics to Consider
8.FORECASTS
8.1.Methodology and assumptions for forecasts
8.2.Illustration of S-curve
8.3.Historic cobot market size: 2019-2024 (what are the COVID impacts)?
8.4.Cobot market size forecast: 2025-2045
8.5.Cobot volume sales forecast: 2025-2045
8.6.Market share of cobots (volume) by regions: 2019-2043
8.7.Market share of cobots (revenue) by regions: 2025-2045
8.8.Regional Cobot Volume Forecast: 2025-2045
8.9.Cobots Volume Forecast for APAC: 2025-2045
8.10.Cobots Volume Forecast for Europe: 2025-2045
8.11.Cobots Volume Forecast for North America: 2025-2045
8.12.Cobot revenue forecast by regions: 2025-2045
8.13.Mobile collaborative robots market size forecast: 2025-2045
8.14.Cobot end-effectors market size forecast: 2025-2045
8.15.Cobot volume forecast in automotive industry: 2025-2045
8.16.Cobot volume forecast in the automotive industry: 2025-2045
8.17.Cobots in chip quality inspection
8.18.Cobots volume forecast for chip quality inspection: 2025-2045
8.19.Market size forecast of cobots by 12 applications: 2025-2045
8.20.Cobot market forecast (US$ millions) tables by end-user industry: 2025-2045
8.21.Cobot volume forecast (thousands) by end-user industry: 2025-2045
8.22.Cobot market forecast tables by end-user industry - Volume (thousands)
8.23.Volume forecast of cobots by tasks: 2025-2045
8.24.Cobot volume forecast table by tasks: 2025-2045
9.PROFILES
9.1.ABB
9.2.AIRSKIN
9.3.AMD Xilinx — KR260 Starter Kit for Various Robotic Applications
9.4.Bruker Alicona
9.5.Denso — New Market Player in the Cobot Industry
9.6.F&P Personal Robotics
9.7.Franka Emika
9.8.Kassow Robots
9.9.Kawasaki — Industrial Robots and Tactile Skin on Cobots
9.10.KUKA — Solutions to Cobots, Digitalisation, and Sustainability
9.11.Neura Robotics
9.12.Omron — Cobot with an End-Camera
9.13.OnRobot A/S
9.14.Robotnik
9.15.Stäubli — Demonstrating a Full Solution for Future Factories
9.16.Tacterion
9.17.Techman Robot — A Major Cobot Player
9.18.Universal Robots — The Largest Cobot Player
9.19.Vikaso Robotics
9.20.Yaskawa — Leading Player of Industrial and Collaborative Robots
 

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幻灯片 360
Companies 20
预测 2045
已发表 Nov 2024
ISBN 9781835700747
 

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