AI is a filed of study that encompasses computational techniques for performing tasks that apparently require intelligence when performed by humans. Such problems include diagnosing problems in automobiles, computers and people, designing new computers writing stores and symphonies, finding mathematical theorems, assembling and inspecting products in factories.
It is a technology of information processing concerned with process of reasoning, learning and perception.
AI is both an art and a science. The activity of developing intelligent computer systems employs both proved mathematical principles, empirical results of studying previous systems.
The ability of systems to sense its environment, make decisions and control actions is known as intelligence. Intelligent action when carried out on a machine are known as artificial intelligence which can be formally defined as- “:It is a branch of computer science, which deals with a growing set of computer problem solving techniques being developed to imitated the human thought or decision making process on to produce the same results as those processes.”
INTRODUCTION:
AI in Design research is concerned with the use of AI techniques to study design. This is done by making hypotheses about designing and producing modes of design, knowledge and activity. Using these hypotheses and modes, computer programs (i.e., design systems) are built that can aid designers and carry out some portion of the design process. Thus hypotheses about design are tested and refined using design systems.Design, as a complex, goal-directed, problem-solving activity, has long been studied as a topic in AI. Apart from the intellectual challenge, it is also an important contributor to economic success, and is a fundamental precursor to manufacturing. AI techniques and components of an intelligent manufacturing system. Since its emergence in the 1950s AI has provided several techniques with applications in manufacturing. In the early years, knowledge-based systems, (KBS) attracted great attention. Recently neural networks (NN), case-based reasoning (CBR), genetic
algorithms (GAs) and fuzzy logic have attracted more attention and have been successfully employed in manufacturing.
This section contains a very brief and much simplified outline of the main. AI techniques and the components of simplified model of an intelligent. Manufacturing system.
AI TECHNIQUES:
2.1 KBs: The first attempt to be widely used to equip manufacturing systems with some degree of intelligence was the use of KBS. They seek to incorporate human knowledge about an application area, usually elicited from experts in the particular domain, so that the system can automatically replicate aspects of best practice. The human knowledge is represented using the IF- THEN production systems or more structured formats such as frames and semantic nets.
2.2 NNs: NNs are based on ideas about how the brain may work. Input stimuli (e.g. the parameter values have been widely used in many classification and optimization situations. History data are used to “train” the network, automatically determining the most appropriate configuration of the hidden network.
2.3 Fuzzy logic: Fuzzy logic allows the representation and processing of uncertain information such as linguistic statements, for example the customer desires a car, which is “fairly luxurious”. Judging the degree not is used in mathematical modeling or target setting.
2.4 GAs: GA use ideas from population genetics for solving complex global optimization problems. A pool of potential candidate solutions evolves through reproduction and mutation of the fittest and elimination of the least promising solutions of each generation are made “extinct”.
2.5 CBR: In CBR, the intelligent component of the system contains a history of past problems and the (successful) solutions, applied. Future problems can then be considered through analogy with these past cases to home in rapidly on the most promising type of solutions. A further step is incorporating machine learning though the updating of the ‘case-base” with those for which the solutions suggested proved successful.
Next: COMPONENTS OF AN INTELLIGENT MANUFACTURING SYSTEMS
(MODELLING AIR FUEL RATIO CONTROL)
Read the Summary of Manufacturing system
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