The following video presents The Future of Factory Automation:
Since the 1970 factories have become ever more automated. In this episode Allison and Vince look at current trends in factory automation and show how networked facilities are changing the landscape of manufacturing.
According to the Robotic Industries Association (RIA), robot orders and shipments in North America increased in 2014 due to various socioecononic reasons.
Manufacturers are adopting more automation than ever before. For many, it’s no longer a question of whether to automate, only when and to what extent.
Robot Orders and Shipments in North America
- A total of 27,685 robots valued at $1.6 billion were ordered from North American companies during 2014, an increase of 28% in units and 19% in dollars over 2013.
- 25,425 robots valued at $1.5 billion were shipped to North American customers in 2014. Shipments grew 13% in units and six percent in dollars over 2013.
- The automotive industry was the primary driver of growth in 2014, with robot orders increasing 45% year over year.
- Non-automotive industries grew seven percent in total over 2013. The standout non-automotive industries in 2014 in terms of order growth were Plastics and Rubber (25%), Semiconductor and Electronics (21%), and Metals (16%).
- The fastest growing applications for robot orders in North America in 2014 were Arc Welding (+58%), Spot Welding (+57%), Assembly (+16%), and Material Handling (+11%).
- RIA estimates that some 230,000 robots are now at use in United States factories, placing the US second only to Japan in robot use.
Some Socioeconomic Reasons For Increasing Robot Sales in Manufacturing
- Wages offshore rising.
- Robot prices down and performance up.
- An aging workforce moves closer to retirement.
- Misconceptions of manufacturing as crude and demoralizing persist.
- The skills gap is growing.
Canon is working hard in creating “eyes for intelligent robots” or Super Machine Vision.
Canon is currently hard at work in the pursuit of Super Machine Vision (SMV), a next-generation vision system that surpasses the abilities of the human vision system, by leveraging its autofocus (AF) technologies cultivated through the development of cameras and business machines while also taking advantage of the image-recognition and data-processing capabilities employed in face-detection and character-recognition technologies.
SMV development is proceeding in two fields—Industrial Machine Vision and Monitoring Machine Vision—with the aim of realizing intelligent robotic vision capable of not only operating on command, but also detecting, assessing and learning as people do, based on a recorded history (experience) in accordance with changes in the environment and circumstances.
For various products, using Industrial Machine Vision, Canon aims to develop vision systems for automatic production robots to be used during the assembly and inspection processes as follows.
Conceptual Overview of Identification Functionality of the 3-D Machine Vision Heads or Systems. (Left) Performing the same function as the human vision system, the illumination and capture unit employed in these systems incorporates some of Canon’s most advanced imaging and optical technologies. (Right) Meanwhile, the processing unit, which serves as the brain of the system, is equipped with various recognition and image-processing technologies developed by Canon: Image Courtesy of Canon
Additionally, to provide intelligent learning capabilities, the unit contains algorithms developed based on statistical machine learning, which makes possible estimation and learning through the analysis of statistical data.
Because many of the parts used in cameras and other products are achromatic—many being either black or white in appearance—or made of glossy or transparent material, identifying individual parts from within a large pile proved challenging. With Industrial Machine Vision SMV, however, development focuses on the realization of visual capabilities that enable the high-speed and high-precision supply and assembly of such parts.
http://www.canon.com/technology/approach/special/smv.html
Recently, Canon launched the 3-D Machine Vision Systems, models RV300, RV500 and RV1100.
- To be used with industrial robots, these systems or heads are capable of high-speed, high-accuracy three-dimensional recognition of objects.
- Therefore, these heads in combination with a robotic arm can help increase production efficiencies in factories by facilitating the automatic high-speed supply of parts to production lines.
The Canon 3-D Machine Vision Systems, models RV300, RV500, and RV1100 are expected to be available on Oct 1, 2015.
PRESS RELEASE
Canon Enters 3-D Machine Vision Market In The US
MELVILLE, N.Y., JULY 16, 2015 – Canon U.S.A., Inc., a leader in digital imaging solutions, today announced the entry into the growing machine vision market in the U.S., with the launch of 3-D Machine Vision Systems, models RV300, RV500 and RV1100. Designed for use with industrial robots, these systems are capable of high-speed, high-accuracy three-dimensional recognition of objects. The systems in combination with a robotic arm can help increase production efficiencies in factories by facilitating the automatic high-speed supply of parts to production lines.
Canon RV1100 3-D Machine Vision Head or System
Enabling a robotic arm to accurately and successively recognize and pickup individual items from a randomly assembled pile of parts requires a system capable of the three-dimensional recognition of the shapes of the parts. All three models of Canon’s Machine Vision system feature a 3-D machine vision head, which encompasses the system sensor and 3-D machine vision recognition software for recognition processing. The highest level of performance in speed and accuracy for three-dimensional object recognition capabilities of the Canon’s Machine Vision system were made possible by applying innovative image-recognition and information-processing technologies cultivated through Canon’s research and development of cameras and business machines.
Canon’s 3-D Machine Vision systems can accurately recognize a diverse range of objects, including parts with curved features, parts with few distinguishing characteristics and intricately structured parts. The RV300, RV500, RV1100 enable the 3-D recognition of randomly piled parts as small as approximately 10 mm2, 20 mm2, and 45 mm2, respectivelyi.
Contributing to improved production-line efficiency, all three models deliver high-speed performance, taking only approximately 1.8 seconds to recognize randomly arranged small-scale parts in 3-D. This data is then sent to a robotic controller unit attached to the robotic arm.
The new systems feature high-performance 3-D recognition with a high level of accuracy; the RV300, RV500, and RV1100 achieve exceedingly small error tolerances of less than 0.1 mm2, 0.15 mm2, 0.5mm2, respectively.
Users can easily register data for parts to be picked up by inputting CAD data and by capturing images of the parts randomly assembled in a pile. The 3-D machine vision systems can use computer-generated images to automatically learn how to visually identify the parts. Since no complicated programming is necessary, users can easily re-register parts in accordance with changes in type and shape of parts to be supplied in production.
The Canon 3-D Machine Vision System is capable of instantaneously measuring the location and orientation of designated parts in three dimensions and helps eliminate the need for separate 2-D vision sensors to determine the positioning of parts or a table on which to temporarily place parts during the parts-supply process. Accordingly, the system allows the construction of production lines to be simplified for parts provision while achieving higher efficiency in feeding parts to the production line.
In 2014, global sales of 2-D and 3-D machine vision systems for use with industrial robots totaled approximately $22 millionii. The market for 3-D machine vision systems is expected to grow significantly in the future, driven by strong demand for the further automation of production lines used by manufacturers in a variety of industries, including automotive and automotive component manufacturers.
The Canon 3-D Machine Vision Systems, models RV300, RV500, and RV1100 are expected to be available on Oct 1, 2015.
About Canon U.S.A., Inc.
Canon U.S.A., Inc., is a leading provider of consumer, business-to-business, and industrial digital imaging solutions to the United States and to Latin America and the Caribbean (excluding Mexico) markets. With approximately $31 billion in global revenue, its parent company, Canon Inc. (NYSE:CAJ), ranks third overall in U.S. patents granted in 2014† and is one of Fortune Magazine’s World’s Most Admired Companies in 2015. In 2014, Canon U.S.A. has received the PCMag.com Readers’ Choice Award for Service and Reliability in the digital camera and printer categories for the 11th consecutive year. Canon U.S.A. is committed to the highest level of customer satisfaction and loyalty, providing 100 percent U.S.-based consumer service and support for all of the products it distributes. Canon U.S.A. is dedicated to its Kyosei philosophy of social and environmental responsibility. In 2014, the Canon Americas Headquarters secured LEED® Gold certification, a recognition for the design, construction, operations and maintenance of high-performance green buildings. To keep apprised of the latest news from Canon U.S.A., sign up for the Company’s RSS news feed by visiting www.usa.canon.com/rss and follow us on Twitter @CanonUSA. For media inquiries, please contact pr@cusa.canon.com.
† Based on weekly patent counts issued by United States Patent and Trademark Office.
i As a condition when measuring, the RV300, RV500, RV1100 require minimum pattern areas projected from the machine vision head of 100 mm2, 400mm2, 2,025mm2.
ii Market data based on Canon’s own research.
All specifications and availability dates are subject to change without notice.
The following video presents Answers for the future of manufacturing:
Making things right. Answers for the future of manufacturing.
In the future machines will learn to communicate independently, to optimize production stages and to fill in for each other where necessary.
