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Designing a tissue converting line is a complicated process of matching business objectives with equipment cost and capability and then creating a cost effective and efficient layout. Very often the design engineer must rely on experience and spreadsheet calculations to develop a process design and layout, which may not optimize total output of the operation. PLS lite is a revolutionary tool which models actual production scenarios so that the design engineer can make the best selection of equipment in an optimized layout.

PLS, powerful calculation engine based on sophisticated mathematical algorithm, aims at analyzing and checking the performance of converting lines. In fact, PLS enables to define the entire plant layout according to mathematical rules before purchasing the processing machines: it virtually checks the entire productive process before the investment, and helps to compare and find possible alternatives to improve it and helping to choose the processing machine based on one’s own specific productive needs.

Furthermore, it checks the line performances, simulating the real process, also in consideration of the interaction between products to obtain (from raw material, to final packs configurations) and specific machines in operation.
PLS is a useful tool for tissue producers, for material manufacturers and for machine manufacturers. PLS checks the accuracy of the input data to calculate plant's bottlenecks; the user can also use a preconfigured plant layout for his trials, or he can use his own layout.

Costs analysis and return of investment evaluation are included in the assessment.
PLS transforms the technical model of the layout into a flow diagram to express the logic of the network of machines, displaying the plant's nervous system.
After matching each machine with speed and products data, PLS checks the congruity of the input data, by making several product and machine trials.
The assessment allows the user to compare the speed and performances of different machines and calculate productivity, pinpointing bottlenecks.
The user can verify each machine's usage and the future availability of the plant, predicting both breakdowns and physiological stops.
All results are expressed through reports, exportable in pdf and usable for future analysis.