Problems that are difficult to model in other mathematical ways, because of their complexity, have sometimes show difficulties when the results are compared to those obtained from neural networks.

Examining the history of using knowledge based engineering systems and other artificial intelligence related methods, a special conclusion can be drawn: neural networks have not been widely applied to the analysis of textile spinning processes.

In cotton spinning, problems can be divided into those that have an impact on the technology including machinery and control, affect the properties of materials, and determine the quality.

This paper discusses this field and develops proper approaches and by giving examples of applications of neural networks too real cotton spinning processes.