Industries such as personal electronics, where there is a need for customization and a high expectation for quality, are driving major changes in the manufacturing industry, and integrated robotic applications are helping. Production is shifting from mass production of the same product to production of smaller lots of different products as companies look to achieve a shorter time to market and a shorter total business cycle. This means more products can be customized, manufactured locally, and produced.
Traditional robots adapt to new production models
The traditional production model won't disappear any time soon because it is ideal for mass production. In these traditional plants, industrial robots are fixed in place and programmed to execute specific tasks. These traditional industrial robots are highly efficient, accurate, and reliable. However, these traditional industrial robots cannot see their surroundings, feel objects, or interact with humans.
To keep pace with the changing global manufacturing model, future robots will need to offer the flexibility and agility to remain productive and improve quality while adapting to meet increasingly diverse consumer needs.
The characteristics of a future intelligent robot include the ability to deploy in various applications, such as manufacturing plants or the home. They also need connectivity to a network that shares information with other smart devices and the ability to learn with the support of artificial intelligence algorithms, the Cloud, and Big Data. They also need an easy, safe, and friendly human-machine interface (HMI) and the ability to move.
More intelligent robotics
Many technology giants are currently working to make more intelligent robots. For example, Google is training its 6-axis robots to pick up objects of varying shapes and materials. These robots are not pre-programmed for a specific object so their failure rate is high when encountering a new object, but they can learn from every failure and try to find the right strategy to pick up the object next time. The robot can learn from its unsuccessful and successful trials and share the experiences with other robots via the Cloud.
Fanuc is doing similar research with deep-learning algorithms that use trial and error to learn how to pick up randomly positioned objections with 90% accuracy. Fanuc is partnering with Nvidia, which provides GPU chipsets, to offer artificial intelligence services to predict downtime and improve existing robots' operational efficiency. Potential applications for deep machine learning are extensive, such as minimizing downtime by pre-scheduling maintenance and optimizing robot movements by analyzing vision system and sensor data.
Collaborative robots, human-robot interaction
While collaborative robots are not as efficient or accurate when compared to their traditional industrial robots counterpart, they have the advantages of being safe, mobile, flexible, space saving, easy to install, deploy, and program. IHS Markit forecasts the market for collaborative robots will grow from $108 million in 2015 to $570 million in 2020.
Collaborative robots are designed to understand their environment and interact with people, which is unlike a traditional robot that works on the assembly line. These technologies are intended to develop the natural interfaces that allow for the operation of complex robotic systems with less training and expended energy.
Collaborative robots are a popular topic around the world, and many industrial robot vendors are showcasing their collaborative robots including: YuMi from ABB; UR3, UR5, and UR10 from Universal Robots; Sawyer and Baxter from Rethink; and CR-35iA from Fanuc.
Professional service robots
According to the IHS Markit Service Robots & Drones Report–2016, the market for professional service robots was estimated at $2.6 billion in 2015 with revenues forecast to increase to $12.8 billion in 2020. After 2020, the global market for professional service robot markets is forecast to grow even faster and reach $80.6 billion in 2030 with more robots moving from prototype to commercialization in various applications.
The demands on the professional service applications are a multi-billion dollar opportunity for the professional service robot market. Industries such as agriculture, logistics, medical and healthcare, and domestic help are among the early adopters of professional service robots.
The automated agricultural machinery is gradually replacing the work handled by farmers as demand for service robots has increased. They're being used for processes such as seeding, planting, harvesting, pruning, weeding, picking, sorting, spraying, and materials handling.
The medical and healthcare industries also are making great progress in service robot deployment. With surgical robot prices falling, and their use in medical operation tasks growing, the medical industry will continue to be one of the fastest growth sectors for robots. As the global population ages—especially in developed nations like Japan and Germany—the demand for domestic help robots also will grow as the technology develops.
Robotic autonomous navigation, mobility
Mobility is one of the critical differences between service robots and traditional industrial robots. Robot form factors can be classified into four types based on the environment, mobility, and portability: Land-based, air-based/space/drones, water-based, and wearable/exoskeleton.
A robot's form factor is linked with the environment in which the robots need to perform and the mobility of the robotic system. Wheeled or tracked robots can adapt well within a structured and predictable environment (as automatic guided vehicles do in plants or cleaning robots working at home), while legged robots are suitable for unstructured and unpredictable environments.
The largest and earliest applications of mobile service robots are the warehouse-based systems and intra-logistics operations within factories and the retail environment. The increase in business-to-customer trade has changed commissioning tasks from large-scale pallet and crate picking to unit picking operations. This has driven autonomous navigation and mobility technologies as a result.
Wilmer Zhou, senior analyst, IHS Markit. IHS Markit is a CFE Media content partner. Edited by Chris Vavra, production editor, Control Engineering, CFE Media, firstname.lastname@example.org.
What other industries do you see taking advantage of the industrial robots market and why?
About the author
Wilmer Zhou is a senior analyst at IHS Markit with expertise in the APAC automation market. In the automation field, his focus is on robotics, motors, and drives, including low voltage ac motors, medium voltage motors, low voltage motor drives, medium voltage drives, stepper systems, integrated motors, servo motors, servo drives, and generators. Zhou holds a BS in Mechatronic Engineering from the University of Electronic Science & Technology of China and MBA master degree from Shanghai JiaoTong University. Zhou is based in the company's Shanghai, China Office.