ROBOT TEACH PENDANT MARKET ANALYSIS

The teach pendant is a device that is used to control the industrial or non-industrial robot remotely. Teach pendant device provides a various settings which helps to control robots and also helps to design and develop new capabilities and features

The increasing R&D investment for the development of next generation robots become one of the key factor for the growth of robotic tech pendant market, globally. According to Coherent Market Insight analysis there was US$ 91.5 billion spending in robotic industry in 2016, up from US$ 71 billion and is forecasted to reach up to US$ 188 billion in 2020. Various R&D activities are trying to improve the technology in the robotics such as mechatronics, perception manipulation, navigation, gripping, and motion control. The second generation robots holds the technical capability of sensors and 3D- vision system which works with the integration of control system and intelligent algorithms with teach pendants which helps to identify the machine and human presence. For the next generation robotics the vendors are highly focused to improve the cognitive skills of robots with the help of control systems, sensors, high-power processors which helps robots to analyses the gathered information in real time entity and change its behavior accordingly. In addition to this, the increasing demand of non-automotive application and advancement of technology are also some of the major driving factors which increase the market of robot teach pendant globally.   

The alternative programming method become one of the major threat which hinders the growth of the global robotic teach pendant market. The robotic programming method is done by three approaches - online programming method, simulation or offline programming method and lead through programming method. The online programming method adopts teach pendant is a time consuming method. So simulation or offline programming method is adopted by the end users.

Robot teach pendant Market Taxonomy

On the basis of deployment model, the global robot teach pendant market is classified into:

• On–premises model
• Cloud based model

On the basis of end users, the global robot teach pendant market is classified into:

• Healthcare
• Defense and security
• Aerospace
• Automotive
• Electronics
• Domestic
• Others

On the basis of application, the global robot teach pendant market is classified into:

• Material handling
• Welding application
• Painting application

On the basis of regions, the global robot teach pendant market is classified into:

• North America
• Europe
• Asia Pacific
• Latin America
• Middle East
• Africa             

Material handling application holds the dominant position in the global robot teach pendant market and is projected to retain its dominance throughout the forecast period. This application is majorly influenced by increasing demand from various end users industries such as automotive, electronics and many more installing the automating process in there manufacturing units. The increasing demand to advanced product development and availability of less skilled labor majorly in developing countries such as China, India have increased the demand for 6robots as they have the capability to perform multiple tasks.      

Global Robot Teach Pendant Market – Regional Outlook

On the basis of geography, global robot teach pendant market is classified into North America, Europe, Asia Pacific, Latin America, Middle East, and Africa. Asia Pacific holds the dominant position in the global robot teach pendant market and is projected to retain its dominance throughout the forecast period. The increasing automotive industry in India and China provides a major opportunity for the robot teach pendant market in this region. According to “Organisation Internationale des Constructeurs d'Automobiles” in 2016, China sold 28 million units of vehicles up from 24.7 million units in 2015.  

Global Robotic Teach Pendant Market – Key Players

ABB Ltd, Fanuc Corporation, KUKA AG, Omron Adept Technologies, Inc., Yaskawa Motoman, COMAU S.p.A., DENSO Robotics, Epson America, Inc., Festo, Intelitek, Mitsubishi Electric Corporation, Nachi Robotic Systems Inc, Stäubli International, Yamaha Robotics Inc. are some of major companies in the global robotic teach pendant market. 

Global Robotic Teach Pendant Market: Key Developments

• In June 2018, ABB Ltd launched OmniCore, a digital robot control to increase flexibility, reliability and performance. It offers broadest motion control options, more tailored solutions for the connected solutions.
• In April 2019, FANUC Corporation (FANUC), in collaboration with Preferred Networks, Inc. (PFN), developed a new AI function called AI Servo Monitor which collects control data of feed axes and spindle axes of machines with high-speed sampling. It applies deep learning to the collected data and shows the anomaly score based on the current state of the machine components.
• In May 2018, KUKA AG partnered with Hyundai Heavy Industries aims at joint efforts on marketing and related comprehensive support. In furtherance of the partnership, a Strategic Sales Framework Agreement between Hyundai Heavy Industries Holdings’ robotics business division (Hyundai Robotics) and KUKA Robotics Korea Co. Ltd., KUKA’s local subsidiary, was also established. Through such partnership, Hyundai Robotics intended to broaden its product portfolio, regarding new technologies and products, small robotics, human-robotic collaboration, mobility, etc., as well as to expand its business with existing and newly acquired Korean customers.
• In September 2018, Yaskawa America, Inc introduced Smart Pendant, tablet-based interface that offers a simple learning experience compared to the standard pendant and is ideal for novice robot programmers. Smart Pendant features automatic programming feedback which can reduce programmer errors, and its quick error recovery can reduce costly downtime.
• In July 2017, DENSO Robotics introduced a new RC8A robot controller, with the additional advanced performance feature of DENSO Safety Motion which allows creation of virtual fences around the robot.