Web breaks are considered as one of the most significant runnability problems
in a pressroom. This work concerns the analysis of relation between various
parameters (variables) characterizing the paper, printing press, the printing
process and the web break occurrence. A large number of variables, 61 in
total, obtained off-line as well as measured online during the printing process
are used in the investigation. Each paper reel is characterized by a vector x
of 61 components.
Two main approaches are explored. The first one treats the problem as a
data classification task into "break" and "non break" classes. The procedures
of classifier training, the selection of relevant input variables and the selection
of hyper-parameters of the classifier are aggregated into one process based on
genetic search. The second approach combines procedures of genetic search
based variable selection and data mapping into a low dimensional space. The
genetic search process results into a variable set providing the best mapping
according to some quality function.
The empirical study was performed using data collected at a pressroom
in Sweden. The total number of data points available for the experiments
was equal to 309. Amongst those, only 37 data points represent the web
break cases. The results of the investigations have shown that the linear
relations between the independent variables and the web break frequency
are not strong.
Three important groups of variables were identified, namely Lab data
(variables characterizing paper properties and measured off-line in a paper
mill lab), Ink registry (variables characterizing operator actions aimed to
adjust ink registry) and Web tension. We found that the most important
variables are: Ink registry Y LS MD (adjustments of yellow ink registry
in machine direction on the lower paper side), Air permeability (character-
izes paper porosity), Paper grammage, Elongation MD, and four variables
characterizing web tension: Moment mean, Min sliding Mean, Web tension
variance, and Web tension mean.
The proposed methods were helpful in finding the variables influencing
the occurrence of web breaks and can also be used for solving other industrial