Basic Roll Variability Analysis Software

This is a simple Windows Excel-based spreadsheet that has been designed to provide both cross direction and machine direction graphics and machine direction statistical analyses for those companies using end-of-roll or other types of manual samples.

The graphics and statistical analysis combinations will assist the user in determining significant inherent and assignable patterns and levels of variability, cross directional profiles, process capability indexes and out-of-specification occurrences.

You may have the option of a two day on-site software training seminar. Seminar fee will include a free software system. Additional software systems and/or a site license may be obtained at a reduced rates.

Please Note: This software is available for clients only.

Continuous Process SPC Software

"SPC On A Roll" may be used to analyze data from any continuous manufacturing process. It provides unique capabilities in terms of handling data from both fixed and scanning sensors. It is a general purpose interactive statistical graphics system that features an extensive collection of functions for analyzing, visualizing and controlling continuous processes.

The Roll SPC module includes capabilities for adjusting X-Bar control limits and limits to correct for autocorrelation effects. It can also produce multivariate control charts.

The system can accept data files produced by leading spreadsheet programs. A two day on-site software training seminar is also offered.

Book - "Application Of SPC To Roll Products" 3rd Edition

This edition contains new case histories along with expanded sections dealing with roll variability studies, machine capability studies, process capability indexes (Cpk & Ppk) and roll SPC charting options. Additional information on scanning sensors has been added.

Please Note: This book is now sold out.

Video - "Basic Roll Product SPC"

Introduces the process stream concept and discusses the mis-use of end-of-roll cross directional test values for Shewhart charts. Time: 18:24.