Statistical Methods for Quality Control: A Tool for Data Analysis in the Statistica Package

Abstract

The article substantiates the applicability of statistical methods for product quality assessment, analysis of production processes, business processes, etc. The notion “quality” is characterized and its properties are defined: suitability, operational efficiency, appropriate content, etc. It is highlighted that the State Standard of Ukraine is a national body for standardization, metrology and certification, which defines and approves the quality standardization system in accordance with the international standards Guidance on statistical techniques for ISO 9001:2000.
 The focus is made on the main methods for quality control, which are considered the most relevant and most widely used. The application of seven quality control methods is described in detail: Control Sheets, Pareto Diagram, Stratification, Histogram, Scatter Diagram, Cause and Effect Diagram, Control Chart.
 It is substantiated that in a digitalized economy with large scopes of accumulated information, the use of statistical data processing packages is an indisputable tool for analysts. Using statistical quality control methods implemented in the Statistica package, the authors conducted research on simulated data and constructed appropriate graphs and charts. Pareto diagram is designed for ranking the factors with impact on a production process or product quality. The stratification method allows for performing a variance analysis, to determine each factor’s effect on the result.
 The main advantage of the histogram method is its visibility and simplicity for analyzing the homogeneity of a distribution and checking for normality. Scatter diagrams allow one to evaluate the correlation strength and make graphical descriptions of the dependence between production factors, reveal the impact of a factor characteristic on the resulting one, etc. The Ishikawa’s cause-and-effect diagram provides a tool for arranging the factors with effect on the production process. The use of control charts makes enables for analyzing the production process in dynamics.
 It is emphasized that the described quality control methods can be applied in any sequence, production cycle or combination: altogether or as separate analytical tools. Based on the results of the study, the main challenges faced now by business analysts are summed up: the mastery of statistical tools and computer data processing for making effective management decisions.