Anıl Uzal, 030070012, 1st week

Fuzzy Logic:

An element of AI having important applications in control systems and pattern recognition is fuzzy logic (also called fuzzy models). Introduced in 1965 and based on the observation that people can make good decisions on the basis of imprecise and nonnumeric information, fuzzy models are mathematical means of representing vagueness and imprecise information (hence the term “fuzzy”).

These models have the ability to recognize, represent, manipulate, interpret, and utilize data and information that are vague or lack precision. These methods deal with reasoning and decision making at the level higher than neural networks. Typical linguistic examples are the following: few, very, more or less, small, medium, extremely, and almost all.

Fuzzy technologies and devices have been developed (and successfully applied) in areas such as robotics and motion control, image processing and machine vision, machine learning, and the design of intelligent systems. (Kalpakjian S., Schmid S.R., Manufacturing engineering and technology, p 1233)

Expert Systems:

An expert system (ES, also called a knowledge-based system) generally is defined as an intelligent computer program that has the capability to solve difficult real-life problems by the use of knowledge-based and inference procedures (Fig 39.6). The goal of an expert system is the capability to conduct an intellectually demanding task in the way that a human expert would. (Kalpakjian S., Schmid S.R., Manufacturing engineering and technology, p 1231)

Enterprise Resource Planning (ERP):

Beginning in 1990s, enterprise resource planning (ERP) became an important trend. It is basically an extension of MRP-II, and although there are variations, it also is a method for effective planning and control of all the resources needed in a business enterprise (i.e., companies) to take orders for products, produce them, ship them to the customer, and service them. ERP thus attempts to coordinate, optimize, and dynamically integrate all information sources and the widely diverse technical and financial activities in a manufacturing organization. (Kalpakjian S., Schmid S.R., Manufacturing engineering and technology, p 1206)

Laminated-Object Manufacturing (LOM):

Laminated-object manufacturing produces a solid physical model by stacking layers of sheet stock that are each cut to an outline corresponding to the cross-sectional shape of a CAD model that has been sliced into layers. The layers are bonded one on top of the previous one prior to cutting. After cutting, the excess material in the layer remains in place to support the part during building. Starting material in LOM can be virtually any material in sheet stock form, such as paper, plastic, cellulose, metals, or fiber-reinforced materials. (Groover M.P., Fundamentals of Modern Manufacturing: Materials, Processes, and Systems, p 791)