Nonlinear modeling to increase speed in optical cable manufacturing lines

The efficiency of an optical cable manufacturing line can be improved significantly by increasing line speed. But to do so, the manufacturing process itself must be quite robust. It must withstand abnormalities and changes in the factory environment. Maillefer has taken several steps forward in bringing high speed capability to customers, thanks to nonlinear modeling.

Triple speeds
In the loose tube process, excess fiber length (EFL) and post-shrinkage must stay under control during production. The loose tube properties play important role in final cable quality. When EFL is outside tolerances it can cause attenuation increase in temperature cycling. All these properties can be adjusted with correct process parameters. Higher line speeds need tighter tolerances and precisely defined process conditions in order to guarantee good cable quality.

The secondary coating process is reaching totally new limits for line speeds. With traditional manufacturing speeds increased by 300%, obvious process items must be redefined. First, an accurate model that reflected how the process parameters affect the product quality was developed. Then, it was quite straightforward to optimize the most critical production line parameters and components to reach target line speeds.

Nonlinear most suitable
The product quality of the buffering process depends on excess fiber length and on shrinkage properties affected by several process variables. Interrelations are complex. Some variables, including line speed, have clearly nonlinear effects on excess length. Linear statistical techniques are not very efficient at describing these interrelations. Developing phenomenological models is often not feasible, and phenomenological models require a lot of assumptions and simplifications, and hence predict process consequences less accurately.

The most suitable approach is nonlinear modelling, which is empirical or semi-empirical and takes nonlinearities into account. It does not require any major assumptions or simplifications, but simply describes the reality as observed. Nonlinear models have been successfully used to improve the productivity of different extrusion processes. It gives deeper insight to production process and allows users to optimize their end product quality and productivity at the same time.

Read the complete article >>>