Other Popular Applications Of Neural Network In FMS Assignment Help

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Other Popular Applications Of Neural Network In FMS

Neural Network Based FMS Control

Artificial Neural Networks or ANN is mathematical models of theorized brain and mind. Different design methods for flexible manufacturing systems controllers are being practiced that comprise drum timer employed in automatic washing machines, semi-automatic cutting machines, textile machines, engine camshafts. Ring modular and counter sequencer methods or techniques for sequential controller design or implementation. The sequential control's majority applications currently employ a programmable controller that commonly employs a graphical language termed as ladder logic language, like sequential controller. Conversely, the most problems encountered along with their use are because of:

(a)    The method of implementing a sequential control protocol that has an inherently slow response time such increases linearly along with program size due to continuous scanning g of the whole program;

(b)   Ladder logic language is not well appropriated as a sequential control programming language, nevertheless is quite a combinational method and does not explains the operations of sequential progression; and

(c)    This depends upon a trial and error method to design a ladder language.

In order to circumvent such problems, Artificial Neural Network or ANN algorithms were utilized for the solution of not easy real-world problems, comprising control applications, visual pattern recognition, speech recognition, and English text pronunciation. Based upon a biological analogy, an Artificial Neural Network tries to emulate the human brain's ability to learn from illustrations, to learn from not completed data, and particularly to generalize concepts.

The validity of utilizing an Artificial Neural Network based sequential controller has these advantageous strengths along with regard to the conventional controller algorithms:

(a)    Neural networks are robust in the existence of noise and are robust in the existence of hardware failure.

(b)   Minute changes in an input signal will not drastically affect an output node; such is, the proposed RNN-based sequential controller that has a fault tolerant feature controller.

(c)    High-level ideas will be shown as a pattern of activity transversely many nodes quite than like the contents of a minute portion of computer memory.

Neural Network Based Setup Planning of FMS
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