The Program for Experimental Data Processing in Cotton Spinning Mill
The Program for Experimental Data Processing in Cotton Spinning Mill

Summary/Abstract: The quality improvement is essential for every textile enterprise. The optimization of quality could be possible only by using the best materials. The quality of products for customer reflects the materials used in factory, the cycle of production, the processing of each technological line and also the maintenance of machines on the entire technological line. If one of these criterions is neglected, the quality expected by the customer won't be the optimal one. The notion of optimization is adopted relative because the company will be able to secure better materials, to hire a larger staff, to replace the parts of the machines more often. Only these measures will improve the quality, but the real rise of costs could catapult the company out from the market. The lab and the technical service have to be capable of supervising the whole cycle of production in different ways. The success of improving will be assured only by learning the causes of different imperfections of semi-finished products and goods. The main objective is the control of the causes and not of the effects. It is also necessary to out run the primary data a little over the general informing level. The statistics methods permit the value of every individual characteristic on each fabrication cycle. When the fabrication cycle is improved the statistic limits are also more precise. The STATTEX program is very useful for physical and mechanical labs for determination of the fibers physical-mechanical characteristics while the reception on new materials is done, for determination of the semi-finished products characteristics and also for processing of the data from analysis report elaborated for each 3000 kg lot of fibers or any time when it's necessary. The STATTEX program solved the following problems: - Reading of experimental data; - Arrangements of the pool data; - Elimination of the aberrant values using the Dixon or Grubbs tests depending on the sample volume and after then their visualization; - Presents a report for the remaining values; - Lists this report on printer; - Calculates the valid values and their classification; - Testing the concordance between experimental and normal distribution by using the concordance c2 or the Kolmogorov-Smirnov tests depending on sample volume; - Allows the option for listing a report on printer which contains the helping table for the concordance tests; - Graphic representations: - The histogram - The polygon of the relative frequencies - The polygon of the absolute frequencies - The diagram of the cumulate frequencies - Allows the option to list the graphic representations on the printer - Calculates the typical poll values (arithmetical average, median line, mood value, amplitude, dispersion, the average square deviation, the coefficient of variation, the absolute average deviation, the coefficient of linear irregularity, the coefficient of asymmetry, the coefficient of vaulting and the excess); - Allows the option for listing the VTS report that contains the typical poll values calculated previously for interpreting the results.

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