Artificial Intelligence ...Within.Artificial Intelligence methods continue to provide upfront benefits in industrial and consumer arenas, although they're increasingly found working quietly in the background.By Frank J. Bartos. Control Engineering (September 1, 2003). "Perhaps we don't hear much about artificial intelligence (AI) methods used within today's technologies because it's slightly unnerving when computers emulate human thinking. Yet we, and computers themselves, continue to improve the way AI works quietly in the background to optimize, reduce process costs, and improve timing and product quality. For some tough, nonlinear applications, AI may be the only solution. ... Actually, AI consists of various technologies—expert systems, fuzzy logic, artificial neural networks, and genetic algorithms, among others." This article not only explains the technology, but also provides examples of many real world applications.

Mechanical Engineer Receives $400,000 to Improve Computer-Guided Engineering Design. UT Austin College of Engineering press release (March 29, 2005). "Developing a computer approach to graph designs for better suspension bridges, more efficient chemical processing plants or other systems is the focus of a $400,000 National Science Foundation Early Career Development award received by a mechanical engineer at The University of Texas at Austin. ... Assistant Professor Mathew Campbell will use advances in engineering, artificial intelligence and mathematical programs to improve the engineer’s design process."

• Visit the Automated Design Lab at the University of Texas at Austin and be sure to find out the answer to the question: "Why is a top your logo?"

Questions and Answers about the AI Microelectronics Laboratory at the University of Georgia. Here's where you'll find an answer to the question: "What does artificial intelligence have to do with microelectronics?"

Engineering Applications of Artificial Intelligence - The International Journal of Intelligent Real-Time Automation. Elsevier. "Artificial Intelligence (AI) techniques are now being used by the practising engineer to solve a whole range of hitherto intractable problems. This journal provides an international forum for rapid publication of work describing the practical application of AI methods in all branches of engineering." Free journal content, which can be accessed from the sidebar, includes tables of contents, abstracts, and a sample issue.

Major: Artificial Intelligence and Robotics. The Princeton Review. Do you like to take things apart to see how they work? Have you been fascinated with robots ever since you first saw R2D2 and C3PO steal the stage in Star Wars? If so, artificial intelligence and robotics could be the major for you. ... If you want to design the robot body, take classes in mechanical and electrical engineering. If you’re more interested in designing robot minds and behaviors, then you’ll need a background in both electrical engineering and computer science. Finally, if you’re interested in animal-inspired robotics...."

• Also see: Dancing to That Robotic Engineering Beat. By Chris Hedges. The New York Times (November 9, 2004). "'People hear the term mechanical engineering and they think we wear jumpsuits, carry wrenches and fix cars,' [Professor Naomi Ehrich Leonard] said."

ORNL engineers take page out of nature's playbook. Oak Ridge National Laboratory news release (May 10, 2006). "Designing complex systems such as nuclear reactors for space applications is a daunting task, but Oak Ridge National Laboratory researchers have made it less so by borrowing from nature.Using their genetic algorithm optimization tool, a takeoff of the natural selection process, Louis Qualls and colleagues can quickly perform searches of huge numbers of potential solutions to an engineering problem and identify the best options."

Evolutionary Design - Computers can provide design variations that no human would have imagined. A six minute video from the Technology Review Video Collection (September 2006). Guest: Eric Bonabeau.

Smart software makes sense of rough sketches. By Celeste Biever. New Scientist (September 12, 2003). "Intelligent software that brings rough sketches to life in a virtual world is promising to revolutionise the way children learn and to help engineers visualise their designs. ... The MIT software monitors the image as it is being drawn on to a computer screen and allocates probabilities to various interpretations of what it might represent. As the user adds more detail, the software adjusts these weightings. To do this, it uses a technique known as Bayesian analysis, which is normally used to compute the likelihood of specific causes, given certain effects. 'With our software, the 'causes' are what the user had in mind to draw, and the 'effects' are what was actually drawn,' says Randall Davis, who has developed the code with Christine Alvarado at MIT's Artificial Intelligence Laboratory."

• Visit the The Design Rationale Group: "Our approach to rationale capture is inspired by this set of observations and claims that a successful process must be less trouble than it is worth. The key in turn to making it less trouble is to provide natural interaction with design tools. We want designers to be able to sketch, gesture, and talk with the computer about their work in the same way they would with another designer. Our vision is a design environment with intelligence embedded in the environment, allowing designers to work in familiar ways in familiar media (e.g., whiteboards), yet give those media new and powerful capabilities (e.g., the ability to understand a sketch, ask intelligent questions about a design, etc.)."

Routine Design for Mechanical Engineering. By Axel Brinkop, Norbert Laudwein, and Rüdiger Maasen. AI Magazine 16(1): Spring 1995, 74-85. "COMIX (configuration of mixing machines) is a system that assists members of the EKATO Sales Department in designing a mixing machine that fulfills the requirements of a customer. It is used to help the engineer design the requested machine and prepare an offer that's to be submitted to the customer. comix integrates more traditional software techniques with explicit knowledge representation and constraint propagation. During the process of routine design, some design decisions have to be made with uncertainty. By including knowledge from process technology and company experience in the mechanical design, a sufficiently high degree of flexibility is achieved that the system can even assist in difficult design situations. The success of the system can be measured by the increase in the quantity and the quality of the submitted offers."

Breeding Race Cars to Win. By Michelle Delio. Wired News (June 18, 2004). "A technology that allows robots to rebuild themselves and computer programs to evolve and become better on their own is now being used to breed super-fast Formula One race cars. ... The breeding was done solely with computer-generated simulations using genetic algorithms -- programs that combine Mother Nature's laws and computer science to mimic the natural process of evolution. Using this sort of programmed procreation, the Digital Biology Interest Group [at University College London] has made self-healing battlefield surveillance robots -- gadgets that look like robotic snakes that can figure out how to wiggle home even when severely damaged, unlike less-evolved robots that typically just give up when one of their critical components goes out of commission."

Intelligent Computer-Aided Engineering. By Ken Forbus. AI Magazine 9(3): Fall 1988, 23-36. "The goal of intelligent computer-aided engineering (ICAE) is to construct computer programs that capture a significant fraction of an engineer’s knowledge. Today, ICAE systems are a goal, not a reality. This article attempts to refine that goal and suggest how to get there. We begin by examining several scenarios of what ICAE systems could be like. Next we describe why ICAE won’t evolve directly from current applications of expert system technology to engineering problems. I focus on qualitative physics as a critical area where progress is needed, both in terms of representations and styles of reasoning."

Humans beat AI in robot wars. By Andy McCue. CNETAsia (December 1, 2003). "Virtual robots created by computers have taken on human-designed opponents in an online experiment. Human innovation has fought off competition from robots created using artificial intelligence in an online experiment by boffins at a London university. The online Sodarace competition, created by the Queen Mary University of London, U.K. pitched virtual robots created by humans against those designed by artificial intelligence."

• For more info about Sodarace, the related web site below.

Virtual Vroom - Putting the pretend pedal to the make-believe metal in pursuit of expedited engine excellence. By Frank Markus. Car and Driver Magazine (May 2003). "Today, untold zillions of molecules of iron, aluminum, and plastic composites awoke at the flick of a human wrist on an ignition key. They were compressed or stretched by the forces of combustion, they transferred heat from cylinder walls to coolant, they transformed vibrations into noise, and they were lubricated against the forces of friction. But before these molecules were crafted into modern engines, virtual facsimiles of them were subjected to vivid, lifelike simulations of these actions, the whole shebang conjured by an artificial intelligence as sophisticated as anything conceived of in The Matrix. ... To get a closer look at this world of artificial abuse, we plugged into GM's engineering matrix, which is presided over by the GM Powertrain Synthesis & Analysis group in Pontiac, Michigan. This crew of 117, most of whose walls are papered with advanced-degree sheepskins, maintains and develops some 300 computerized tools and test procedures used throughout GM. ... Each tool strives to reduce the time, energy, and cost expended on physical testing and experimentation so that someday every part in a new car will be designed perfectly, so that no prototype (let alone production) part will ever fail."

VirtualManufacturing - This factory flickers on your monitor. By JosephOgando. Design News (October 11, 2004). "Want to see a factoryof the future? Well, turn on your computer. A New Jersey companycalled eMachineShop recently launched a new on-line factory thatlets engineers quickly design, price, and order machined metal andplastic parts. ... Once the geometry has been established, the software'smachining 'expert system' evaluates each design for manufacturability.'One of our major technology innovations involved incorporating ahuge amount of machining knowledge in the system,' says Lewis. Forexample, the system can currently flag issues related to milling,bending, part finish, and more. The bottom line, says Lewis, is thatthe system 'won't let users design any parts we can't make.'"

Collaboration is Key - But engineers must protect intellectual property. Interview with Attilio Rimoldi. Design News (May 17, 2004). "What's really new in CAD software? Functional modeling is the new evolution of CAD, where CAD is headed toward artificial intelligence. CAD systems were focused on the creation of geometry. But we as engineers think in terms of function, not geometry. We need to let the engineers think as engineers and not as CAD jockeys. Let the system create the supporting geometry to meet the functional needs. Functional modeling is also the basis for collaboration where we share only what is necessary. We don't share geometry, but instead share functions."

Immobots Take Control. By Wade Roush. Technology Review (December 2002/January 2003). "From photocopiers to space probes, machines injected with robotic self-awareness are reliable problem solvers. ... But Deep Space One had something Mars Polar Lander lacked: an onboard robot able to think autonomously and handle the unexpected. Using its engineering knowledge, the robot tried to repair the switch by toggling it on and off. When this failed, it devised a successful plan to complete the navigation maneuver, and the craft proceeded unharmed. The robot that saved Deep Space One was in the vanguard of a new breed of machines poised to have a big impact in space and here on Earth. Quite unlike the metallic contraptions that march stiffly through sci-fi movies or the mindless, stripped-down devices that heft parts on our assembly lines, the new robots have more brain than brawn. Each possesses a detailed picture of its own inner workings—encoded in software-based models—that gives it the ability to respond in novel ways to events its programmers might not have anticipated. Because many of these inward-focused, self-reconfiguring machines don’t move, some computer scientists call them immobile robots, or 'immobots.' ... A deep-space probe obviously requires much more autonomy than, say, a photocopier. But heavily used office machines must meet a similar demand for reliability and efficiency... 'This distinction between telling a system how to do its job and telling the system the end result you want is very fundamental,' says Robert Morris, director of IBM’s Almaden Research Center in San Jose, CA. IBM is working to build what it calls 'autonomic' characteristics -- model-based features, as well as others that employ classic heuristic programming -- into products such as Web servers and storage networks. These features will allow the products to reconfigure themselves for optimal performance, depending on what’s being asked of them."

Top Managers See It All With Products that Prowl For Performance Data. Company-wide view allows real-time analysis and action. By Tom Sawyer. McGraw-Hill Construction / Engineering News Record (December 8, 2003). "After years of concentrating on project management, scheduling and collaboration tools, an increasing number of software developers and Web services providers now are developing tools to enhance the enterprise-level view. They are developing products to either gather, integrate and analyze data generated by multiple tools, or they are offering single-database, across-the-board solutions for all business operations. 'Enterprise' and 'dashboard views' are buzzwords now. But some users say there is a lot more to it than just buzz and words as they put new systems in place. ... Cyntergy Technology, Tulsa, Okla., maker of a product called Thumbprint CPM, has even brought in an artificial intelligence twist. Thumbprint is a unified database, program management system. But instead of working from rigid templates for business activities created during implementation, it learns your business patterns and asks for explanations whenever you make changes. If, for instance, you start setting up a project in a new state that has different permitting requirements from states where you have set up other similar jobs, the system will query you about the changes. It also will define a new process to apply if you set up more work in that state again."

NASA Evolutionary Software Automatically Designs Antenna. Press release (June 15, 2004) available from SpaceRef. "NASA artificial intelligence (AI) software - working on a network of personal computers - has designed a satellite antenna scheduled to orbit Earth in 2005. The antenna, able to fit into a one-inch space (2.5 by 2.5 centimeters), can receive commands and send data to Earth from the Space Technology 5 (ST5) satellites. ... NASA scientists have spent two years developing the evolutionary AI software that designed the antenna. 'The AI software examined millions of potential antenna designs before settling on a final one,' said project lead Jason Lohn, a scientist at NASA's Ames Research Center, located in California's Silicon Valley. 'Through a process patterned after Darwin's 'survival of the fittest,' the strongest designs survive and the less capable do not.' The software started with random antenna designs and through the evolutionary process, refined them. The computer system took about 10 hours to complete the initial antenna design process. ... 'Not only can the software work fast, but it can adapt existing designs quickly to meet changing mission requirements,' he said. ... Scientists also can use the evolutionary AI software to invent and create new structures, computer chips and even machines, according to Lohn. ... 'The software also may invent designs that no human designer would ever think of,' Lohn asserted."

Unnatural Selection - Machines using genetic algorithms are better than humans at designing other machines. By Sam Williams. Technology Review (February 2005). "So why not automate trial and error? Antenna design, [Jason] Lohn believes, is one of many engineering problems that could best be solved by evolutionary algorithms, an emerging class of software that produces lots of different designs, rejecting the less fit in order to select the most functional."

"Berkeley Expert Systems Technology (BEST) lab is an Artificial Intelligence, Expert Systems and Information Technologies laboratory in the Department of Mechanical Engineering at University of California at Berkeley."

"CyclePad is the first articulate virtual laboratory the Qualitative Reasoning Group [at Northwestern University] has implemented. CyclePad enables students to construct and analyze a wide variety of thermodynamic cycles. A hypertext explanation facility provides the student with access to the chain of reasoning underlying the derivation of each value. CyclePad is currently being field-tested in undergraduate engineering classes at Northwestern University, The U.S. Naval Academy, and Oxford University."

• "Creating articulate virtual laboratories requires synthesizing advances involving several AI technologies. Qualitative physics ... Compositional modeling ... Truth-maintenance systems ... Symbolic algebra and constraint propagation ... Analogical processing techniques." - from the project page

European Group for Structural Engineering Applications of Artificial Intelligence. The focus of the EG-SEA-AI is the application of artificial intelligence research within the field of structural engineering. Structural engineering is defined as a field which encompasses design, fabrication, construction and maintenance of buildings, bridges, towers, dams and other similar structures. Primary goals are to improve contact between researchers and to promote the awareness of advanced computer applications in industry.

The 19th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE '06). Annecy, France; 27 - 30 June 2006.

• IEA/AIE Proceedings are available from the ACM Portal.

Smart Tools Lab @ Mechanical Engineering Department, Carnegie Mellon University. "In our LearnIT project, we are developing software that captures and preserves design procedures. LearnIT observes the designer's interaction with traditional CAD software, and from this infers reusable design procedures. In our RedesignIT project, we are developing tools that can predict the impact of proposed design changes. RedesignIT identifies the potential side-effects of proposed design changes and the possible means of repairing them. In our ExplainIT project, we are developing techniques for automatically constructing design documentation. ExplainIT examines the geometric model of a device and simulations of its operation in order to identify the purposes of the various parts."

#soda" id="soda"Sodarace [a joint venture between: soda and queen mary, university of london] is the online olympics pitting human creativity against machine learning in a competition to construct virtual racing robots. ... Sodarace is not just for fun. It is a shared competition for Artificial Intelligence researchers to test their learning algorithms while also being a play space in which to communicate the benefits of Artificial Intelligence research with a wide audience and promote a creative exploration of physics and engineering."

3D Simulations. "The purpose of this project is to develop 3D graphic simulations that enhance undergraduate and graduate engineering education. This project is run by The Robotics Research Group at the University of Texas." Free demo software of RoboWorks is available.

Related AI Topics Pages

• Architecture & Design
• Business & Manufacturing
• Qualitative Reasoning
• Robots

Other References Offline

AIEDAM. "Artificial Intelligence for Engineering Design, Analysis and Manufacturing is a journal intended to reach two audiences: engineers and designers who see AI technologies as powerful means for solving difficult engineering problems; and researchers in AI and Computer Science who are interested in applications of AI and in the theoretical issues that arise from such applications."

International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems. From the ACM Digital Library.

Journal of Computing in Civil Engineering. Published quarterly by ASCE, the American Society of Civil Engineers. "The Journal of Computing serves as a resource to researchers, practitioners, and students on advances and innovative ideas in computing as applicable to the engineering profession. Many such ideas emerge from recent developments in computer science, information science, computer engineering, knowledge engineering, and other technical fields. Some examples are innovations in artificial intelligence, parallel processing, distributed computing, graphics and imaging, and information technology. The journal publishes research, implementation, and applications in cross-disciplinary areas including software, such as new programming languages, database management systems, computer-aided design systems, and expert systems; hardware for robotics, bar coding, remote sensing, data mining and knowledge acquisition; and strategic issues such as the management of computing resources, implementation strategies, and organizational impacts."

Synthesis of Reinforcement Learning, Neural Networks, and PI Control Applied to a Simulated Heating Coil. C. Anderson, D. Hittle, A. Katz, R. Kretchmar. Journal of Artificial Intelligence in Engineering, Vol. 11, No. 4; pp. 423-431. This article and a condensed version are available from Chuck Anderson's Reinforcement Learning and Control page.

Review of Intelligent Systems for Engineering: A Knowledge-Based Approach. A book review by B. Chandrasekaran. AI Magazine 21(4): Winter, 2000, 123-124.

Artificial Intelligence in Chemical Engineering. Thomas E. Quantrill and Y. A. Liu. Academic Press, 1997.