Analysis of the practices and proposals for improving the dissemination and use of statistical thinking and statistical techniques in industries of the State of São Paulo

Abstract

Approaches to management and production improvement (Lean Manufacturing, TQC - Total Quality Control, TPM - Total Productive Maintenance, Six Sigma Program, etc.) have as a scientific basis the decision-making, control and improvement of products and processes, based on "facts and data", supported by principles and statistical techniques. Despite being disseminated since the early twentieth century, the dissemination and application of these principles and techniques have limitations for routine use in business decisions. Some possible explanations for this situation are: prejudices about the difficulty of understanding and use of these principles and techniques; poor and late training, in statistics, mainly for engineers and administrators; the lack of understanding that direct teaching of statistical techniques is not enough if such training is not preceded by the valuation of Statistical Thinking. The Statistical Thinking means the understanding that the variability is present in all processes and needs to be controlled, the adoption of a vision that rejects the determinism and appreciates the random behavior and the natural variability. The Statistical Thinking would be a basic condition for the greater appreciation and use of Statistical Techniques. This project aims to identify the level of dissemination and the application of Statistical Thinking and Statistical Techniques in several industrial sectors, evaluating the perceived impact on the level of control and the improvement of processes, the level of satisfaction with this usage, and the main obstacles in their dissemination and implementation. The research will be conducted by means of survey, case studies and interviews with consultants and teachers. Based on the analysis of the data, a model for successful application of Statistical Thinking and Statistical Techniques will be proposed. It is expected to generate better understanding and increase success in the application of principles and statistical techniques. (AU)