Dedicating a small portion of U.S. national resources to manufacturing will result in a very high price/performance ratio, and the efficient production of resources will benefit U.S. consumers and support millions of employees in this important economic field in the United States. This can ensure that the United States can maintain its economic growth even if the proportion of workers who can reach retirement age is decreasing year by year. Manufacturing research and development will also benefit health care, agriculture, and transportation, and strengthen US resources, defense, and energy security. In the next 50 years, the resulting series of research activities will greatly improve the quality of "Made in the United States" and increase productivity. This strategy has been embodied in the United States government-led Advanced Manufacturing Partnership (AMP) and the National Manufacturing Innovation Network (NNMI) program.
Robotics is a revolutionary technology that can revolutionize manufacturing. Workers in the United States no longer want to work at the lower end of the factory. At the same time, due to the increase in social security and medical insurance costs, the labor costs of American workers also began to increase. Even if we can afford the labor costs of workers, small, complex industrial robots with shorter life cycles still need to expand their adaptability, accuracy, reliability, and other skills that surpass human workers. Advanced robots and production automation can:
1) Maintain domestic intellectual property and material wealth, otherwise it will choose offshore production;
2) Make manufacturing companies more competitive;
3) Can provide related positions for development, production, maintenance and training of robots;
4) Allowing factories to use robot teams to take advantage of the different skills of humans and robots (human intelligence and dexterity, accuracy, strength and repeatability of robots);
5) Can improve working conditions while reducing expensive medical expenses;
6) Reduce the manufacturing time of finished products, so that manufacturers can better match the changes in retailer demand.
Effective and effective use of robots will increase employment opportunities for the American people, improve the quality of related work, and increase the US’s global competitiveness. Based on the above advantages, NCR, Cisco, Apple, Lenovo, Tesla and other companies have set up their new factories in the United States. They expect to use robotics and automation to support their company's continued growth.
The above summarizes the importance of robotics and automation technology in the U.S. manufacturing industry and in the U.S. economy. It describes where robots and automation technologies will greatly increase productivity, and presents a visionary research and development roadmap. U.S. national investment can play a role in promoting these key research areas.
This article summarizes the related activities and conclusions of the workshop on manufacturing and automated robotics. The "Robotics-VO" organization supported by the National Science Foundation sponsored the seminar. The seminar is one of five workshops to update the "U.S. Robot Roadmap: From the Web to Robotics." The content of this seminar is to constantly update the road map based on the development of the robot field in the past four to five years. The research plan proposed in the report will significantly enhance the manufacturing economy of the United States. It will help form a well-trained and highly technical production line, create new job opportunities, and will play an important role in the re-emergence of the U.S. economy. effect.
Here, "automation" and "robot" have specific meanings. According to the definition of the Robotics and Automation Institute of the Institute of Electronics and Electrical Engineering, robotics mainly refers to systems equipped with sensors and actuators that can cooperate with humans either automatically or semi-automatically. The research of robots emphasizes the intelligence and adaptability to deal with unstructured environments, and the automation research focuses on the efficiency, productivity, quality, and reliability of automated systems that work long hours in organized, well-structured environments.
Our goals are twofold: first, to reveal the strategic importance of robotics and automation technology in U.S. manufacturing; and second, to present cases that can use robotics and automation to increase productivity.
Economic driving force
The basis of economic development in the last century came from industrialization, and the core lies in manufacturing. The manufacturing sector provides 12% of U.S. GDP and 9% of total employment. 70% of U.S. total exports are also due to manufacturing. Therefore, the manufacturing industry represents an important part of the country's overall health economy. In the manufacturing industry, the total value of the robotic industry reached 8 billion U.S. dollars and steadily increased by 9% every year. This core robotic industry has received strong support from the manufacturing industry, such as the provision of instruments, ancillary automation facilities, and system integration. It has contributed a total of US$30 billion worth of industrial value.
In the past 30 years, the manufacturing economy in the United States has undergone profound changes. In addition to the significant trade deficit with Canada, China, Mexico and Japan, manufacturing is still a major part of the U.S. economy. Manufacturing encompasses the manufacture of all goods, from consumer electronics to industrial equipment, which contributes 12% of US GDP and 9% of employment. The manufacturing productivity of the United States exceeds its major competitors. In all countries, the United States is at the top of the list, regardless of the average productivity of employees per unit of time and unit. The average productivity of the Americans has continued to increase, and the productivity has doubled over the past three decades. In fact, it is the ever-increasing productivity that has caused U.S. manufacturing to remain competitive during the recession and recover in the face of other rapidly growing economies such as China and India. The growth and efficiency of productivity are mainly attributed to technological innovation and its application in product design and production processes. At present, China is considered to be the leader in manufacturing, but it is expected that in 2020, US manufacturing will surpass China in terms of output value and productivity.
However, this relationship will always change. Potential foreign competitors are carrying out basic research and education to improve the manufacturing process. On the other hand, the results of U.S. manufacturing are also being used for scientific research and have maintained steady progress over the past decade. During this period of time, there has been little change in the funds used for investment and development in the U.S. manufacturing industry. Under a global perspective, the total U.S. funding for research and development has dropped to only 30%. Sometimes, our foreign competitors use the same innovative technology, but with little labor cost to weaken the dominance of the United States, so the US manufacturing industry is facing increasing pressure. The balance of trade in industrial products in the United States has declined by 50 billion U.S. dollars per decade. In addition, as the population ages, the number of workers is also drastically reduced. It is optimistic to estimate that by 2050, every two workers will have to support a retired worker. Therefore, robot workers must meet the demand for increasing the industrial productivity while reducing the number of human workers. Finally, the tremendous advances in robotics and automation technology will be the key to the next generation of high value-added products. Nano-scale embedded computer industry relying on advanced sensors and microelectronics is no longer a labor-intensive industry capable.
In contrast, China, South Korea, Japan and India are investing heavily in higher education and research institutions. Both India and China are systematically recalling the scientists and engineers they cultivated in the United States. U.S. competitors have also begun to shake the dominance of the United States in specific areas related to robotics and manufacturing. South Korea invests 100 million U.S. dollars a year and invests for 10 consecutive years (2002-2012) in robotics research and education-related projects. The European Union has invested more than US$600 million in research and development of robotics and its cognitive systems, and has also allocated an additional US$900 million to the Horizon Plan related to manufacturing robotics. Japan will also invest 350 million U.S. dollars in human-robot and service robot research and development within the next decade, and announced that it will invest 1 billion U.S. dollars in the next five years to make Japan a global leader in industrial robotics. Compared with the above countries' investment quotas, the federal government's investment funds are very inadequate.
Storage robot kiva
And robotics is also important for automated logistics. Amazon spent $700 million in 2012 to acquire Kiva Systems, enabling it to use the best technology for database automation. In addition, Apple and Lenovo did not use Asia as their first choice to reduce production costs after using the robot system. In the past decade, wages for Chinese workers have increased by 340%, while American workers' wages have grown much lower. In addition, Tesla opened a factory in California to manufacture alternative fuel vehicles. It uses a high degree of automation, which allows it to continue to survive in the United States.
Economic growth
The U.S. Department of Commerce and the American Competitiveness Commission analyzed a large number of companies and their comprehensive annual growth rates. The breakdown of major industry industries is shown in the table below.
The current growth areas in manufacturing include logistics, material handling and robotics. Given the importance of manufacturing, it is necessary to consider how to use robots and other technologies to enhance US manufacturing.
Consumerization of robotics
Many advanced technologies have proven that once technology is introduced into the vast consumer market, it will certainly lead to increased innovation and reduced costs. The most notable example is the emergence of personal computers and mobile communications. Both of these technologies were initially developed for the needs of the company. Once these technologies are introduced into the consumer market, the amount of R&D invested by companies will increase exponentially, resulting in the rapid development of technology and a significant reduction in costs. At the same time, it also stimulated the establishment of a large number of emerging industries and companies. At present, these industries and companies have contributed a large proportion of GDP and are now dominated by the US stock market.
iRobot Roomba 760
This will also have a similar impact on the cultivation of robots and robot-related technology markets. A simple example is Microsoft's Kinect interface for the home computer gaming market. It has advantages in speech and gesture interactions, making it extremely attractive in a large number of commercial applications. Another benefit of "consumerization" of robotics is that workers are more familiar with robots. When people are accustomed to interacting with robots in their lives, they can be more comfortable working with robots without seeing them as threats. For example, two-thirds of consumers who own iRobot's automatic vacuum cleaners name their vacuum cleaners, and one-third of consumers admit that they will bring vacuum cleaners to visit friends.
The future of manufacturing
Today's US manufacturing industry is like the database technology of the 1960s. It is a patchwork solution that lacks strict methodological guidance and cannot be scientifically innovative. In 1970, IBM mathematician Ted Codd invented relational algebra, an advanced mathematical database model. This technology was funded by the U.S. federal government and eventually grew into a $14 billion database industry today. If you can develop a similar model, manufacturing will greatly benefit. Just as the method of adding two numbers does not depend on the pencil you use, the abstract model of manufacturing should also be completely independent of whether the product is being manufactured solely or assembled by a production line.
Another example is the Turing Machine, an advanced abstract model invented by Alan Turing in the 1930s, thereby establishing the mathematical and scientific foundation of today's high-tech industry. Analogous to the Turing machine, the abstract model of manufacturing will also bring huge returns to design, automation and manufacturing. At present, the development of computer science and information science has made it possible to model the physical manufacturing process and to enable researchers to bring Turing machines into manufacturing. The end result will be the same as the database and computer, so that the United States manufacturing products have higher quality, better reliability, lower cost and faster delivery.
By improving robotics and cultivating highly qualified staff, robotics can be applied more efficiently, which will increase employment and global competitiveness in the United States. Traditional assembly line workers are now at the age of retirement. They have not yet received training in using robotics technology, and their insurance and medical costs have also increased year by year. Even with affordable labor costs, the adaptability, precision, and reliability required to produce the next generation of small, complex industrial products are beyond the capabilities of workers. The extensive introduction of advanced robotics and automation technologies in the manufacturing industry will:
1) Master intellectual property and wealth;
2) Make the company more competitive;
3) Create jobs in the areas of robot R&D, manufacturing, maintenance and training;
4) The factory can employ a human-robot hybrid team to make full use of each other's skills and strengths (for example, human beings are good at dealing with emergencies to ensure the operation of the production line, while robots are more likely to perform precise and repetitive tasks and can lift heavy loads. Object)
5) Reduce expensive medical problems (such as carpal tunnel syndrome, back injuries, burns, and inhalation of toxic gases and vapors);
6) Shorten the delivery time of manufactured products and make the system more adaptable to changes in the needs of retailers.
Investing in manufacturing can revitalize US manufacturing. Putting a small part of the country’s resources into an economically efficient, resource-efficient manufacturing industry can benefit US consumers and support the millions of workers who work in this important economic area. The above investment can also benefit health care, agriculture, and transportation, and at the same time it can strengthen the nation’s resources in defense, energy, and security. In the next 50 years, a series of favorable results from the research will greatly improve the quality of "Made in the United States" and make the U.S. manufacturing industry thriving.
Roadmap research process
The U.S. manufacturing technology roadmap describes the prospects for the development of key capabilities in the manufacturing industry through the development of a series of basic technologies in the field of robotics. Each key capability has evolved from one or more areas that are widely used in manufacturing, and both point to some of the main technical areas of basic R&D (see below). It is very important to integrate the content of the roadmap into a coherent plan.
The influence of robotics on manufacturing
Now we use hypothetical examples to introduce some influential robotic technology applications and key capabilities that have a great positive effect on applications. These hypothetical scenarios help explain the changes in the manufacturing model and are examples of the convergence of capabilities and technologies. This roadmap clarifies the key nodes of each capability in 5 years, 10 years, and 15 years.
Case 1: Pipeline Assistant Robot
Automakers face a surge in orders for their new type of electric vehicles and need to quickly integrate the production capabilities of other early-model automobile production lines that have already been produced. The pipeline quickly redistributed the task to accommodate the new car model. The factory purchased a group of assembly-assisted robots that were quickly set up and began to complete new tasks with human workers. The first job in the assembly line was to fine tune the robot parameters to optimize its sensor system and machine learning algorithms. The second job was to double the factory's production in four days of execution. Immediately thereafter, a key supplier requested changes to the assembly sequence to accommodate the tolerance of the battery pack during assembly. Then the engineer used the calculation tool to quickly modify the assembly program, print it to the worker, and upload the new assembly program to the assembly-assisted robot. This flexible manufacturing industry is gradually entering our lives. For example, in August 2012, Rethink Robotics announced that its $22,000 robot Baxter can be programmed directly from demonstrations without training or training. The reduction in installation and operating costs will change the application of future automation technologies in business cases.
Case 2: Unique Discrete Parts Manufacturing and Assembly
A professional physician came to a small workshop with only 5 employees who mainly accepted orders from medical device companies. He wanted to create a head control input device for a quadriplegic patient in a wheelchair. Today, this special equipment is very expensive because it will take a lot of time and labor to set up the machine to manufacture and assemble it. The owner of this small workshop has a robot that accepts voice and gesture commands and can instruct robots when they do not know how to handle them. This robot can place the processing material on a milling machine or lathe and start the machine, and can set necessary mechanical and electronic components and request assistance when the instruction is ambiguous and inoperable. During movement between different working positions, the robot can clean up coolant leaks and provide safety tips to workers working in tight spaces. The robot can respond to a quick request at work and will not be rejected because the request may delay its main job. Finally, the robot assembles the components and loads the product in the afternoon. Such sudden work only caused minor interruptions to the daily work of the workshop.
Case 3: Fast, Integrated, Model-Based Supply Chain Design
The packaging for infant formula supplied by major foreign suppliers was found to have serious quality control issues. Lead engineers in the United States can use a comprehensive multiscale modular integration supply chain model to introduce new suppliers, reuse the reusable parts of the supply chain, and influence the transformation of the entire supply chain: including production, distribution, packaging, and supply And distribution. The most important part of the entire transition is the 20 robots used for rapid production to redesign the bags.
These examples may seem far away today, but we already have a technical foundation, a large number of professionals, educational infrastructure, and appropriate investments in key technology areas. These foundations will enable us to achieve these goals within 15 years.
Key manufacturing capabilities
In this section, we will briefly discuss the key capabilities of manufacturing, and give the technical nodes that may be reached in 5, 10, and 15 years. In the follow-up content, we will discuss some promising research directions that can enable us to reach the above technical nodes.
Adaptable and reconfigurable production line
Today, the time interval between the conceptual design of a new product and its manufacture on the production line is unacceptably large. For a new car, this time interval can be as long as two years. When faced with a new product and production line subsystem that can be produced, we hope to be able to reconfigure the subsystems and set up workstations to produce new products. Therefore, in the next 15 years, the roadmap with adaptive and reconfigurable production lines includes the following three goals:
Autonomous navigation
Autonomous navigation is a basic capability that will affect the automation of mining and construction equipment, the efficient transportation of raw materials to finished products, the handling of raw materials for loading and unloading on assembly lines, and the automation of guided vehicles that bring finished products to checkpoints, and similar Operation of logistic support for inventory storage and deployment. Enabling robots to autonomously navigate in unstructured environments, including stationary obstacles, vehicles, pedestrians, and animals, requires a critical investment in the component technology. The autonomous navigation roadmap contains the following technical nodes:
Green manufacturing
American architect William McDonough said: "Pollution is a sign of design (and manufacturing) failure." At present, from the components to the system, the manufacturing industry that satisfies the top-down needs needs to be fully re-conceived. Most of the solutions to the reduction of waste in the manufacturing industry are directed at the waste generated during the production process, the waste that can be used, and the waste generated during the shutdown and maintenance. Our roadmap for green manufacturing looks at the recycling of all components and systems throughout the production process, from the extraction and processing of raw materials to the manufacture and distribution of products to the recycling of final materials. In order to be able to achieve gradual changes, we must introduce new manufacturing technologies and the design of new products must also follow the goal of green manufacturing. For example, the transition to additive manufacturing will greatly reduce the waste generated in the production of products or parts. The new logistics system also needs extensive recovery capabilities. At present, it is difficult for a logistics system to recover materials that cannot be recycled by manufacturing companies or that can be recycled but not recycled. We are very concerned about the reuse of manufacturing infrastructure, the recycling of raw materials, the minimization of energy use in each manufacturing process, and the reconfiguration of subsystems for the production of new products.
Human-like dexterous operation technique
Robotic arm and palm flexibility will eventually surpass humans. In terms of speed and strength, this is already a reality. However, compared to robotic opponents, human hands still have advantages in completing tasks that require high dexterity. This difference is due to machine-aware, reliable high-fidelity sensors, and key technologies such as planning and control. The robot's smart operation technology roadmap contains the following technical nodes:
Model-based supply chain integration and design
At present, the development of the computer field and information science makes it possible to model the physical manufacturing process and make it possible for researchers to bring the Turing machine into the manufacturing industry. If this technology is completed, the manufacturing industry will thrive like databases and computers, allowing interoperability of systems and components, higher product quality, better reliability, lower costs, and faster delivery. Therefore, the model-based supply chain integration and design roadmap has the following technical nodes:
Nano-scale manufacturing
Classical CMOS-based integrated circuits and computing models are being surpassed by new nano-scale manufacturing and computing technologies. We have seen the growth and development of non-silicon microsystems technology and new methods built using synthetic technologies observed in nature. The development of micro-electromechanical systems (MEMS), low-power ultra-large-scale integrated circuits, and nanotechnology has made the emergence of submillimeter self-powered robots possible. New parallel or even random assembly technologies are expected to emerge. Traditional manufacturing methods will be replaced by new, nano-scale manufacturing methods currently only present in imagination. Therefore, nano-scale manufacturing and nano-robot technology must emphasize its basic R&D:
Unstructured environment awareness technology
In automated manufacturing, fixed automation equipment has been shown to be more easily mass-produced. In addition to some specific applications, the prospects of flexible automation technology and mass customization automation technology have not been noticed. One of the main reasons for this phenomenon is that fixed automation equipment has built a structured environment for itself to greatly simplify the challenges of “smart†manufacturing. Small batches of automated manufacturing require robots to be smarter, more flexible, and safe to operate in a low-structured environment that works with human workers. For example, at the product flow level, robots and other machinery and equipment need to work at various locations to complete the manufacturing of products (such as an airplane or a ship), and at the functional level, the products are Exercise between machines. The challenges of single component manufacturing exacerbated these difficulties. The sensory technology roadmap contains the following technology nodes:
Internal Security Robots Working with Humans: Robot Popularity
There is now a lot of discussion about guilty security robots. These discussions are not limited to the specific meaning of the term "security at home." "Intrinsically safe" equipment is defined as "under normal or abnormal conditions, in the case of a particular hazardous gas most likely to be ignited, it cannot release equipment or wiring sufficient to ignite electrical or thermal energy." In short, an "inner security" device cannot ignite flammable gas. The requirements for "inside security" obviously also need to be taken into account in robotic systems like other machines that are designed for manufacturing. Although it is obvious that "insecurity" will put more burden on the robot's behavior, it may be more related to the definition of the word "guilt" itself.
Guilt: A thing that belongs to its essence or structure; source and contained in an organism or part thereof. This is where the crux lies: we expect that robots must be safe from the inside and completely harmless to humans, regardless of the cost. This stems from a culture that fears that humans may create something that overrides humanity. Perhaps we have created a product that surpasses humanity.
For example, cars are dangerous. The first carriage without horses was a threat to other traditional carriages on the road, but we had already passed that era. On the freeway now, you can overtake at more than 120 kilometers. This does not mean that the car has "internal security," but that we have learned to accept the risks posed by the car. Over time, we gradually created a transportation system that relied on human beings for their ability, limitations, and the risks of driving on highways. We have popularized the automobile, made the automobile relevant to the public, and let the public need the car. The car has become a part of our society.
To popularize robots in the manufacturing industry, a similar risk and responsibility assessment model must be introduced. Like driving a car, the manufacturing environment itself has a certain degree of risk. Our goal is not to increase the risk when robots are added to the manufacturing industry. One acceptable measure of whether this goal is achieved is the number of days lost to work. If the number of days lost to work does not increase after the introduction of robots or automated equipment, then we are on the right path to the popularity of robots. After that we will continue to develop and refine security standards and find engineering system solutions for user-defined tasks.
In fact, we must securely develop and continue to encourage collaborative solutions that target our users' communication needs. This includes defining the capabilities, limitations, and associated risks of each robot. The diversity of innovation will drive the acceptance of robotic risk and responsibility assessment models. The society's understanding of humans and robots working in the factory and the large cultural environment will come along with the popularity of robots. The above social atmosphere will only slowly occur over time based on the expansion of the number of robot users. Advances in natural language programming, control learning, and materials technology are potential ways to accelerate this process.
The roadmap for robots working with humans is as follows:
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