LOOKING FOR BETTER INDUSTRIAL PROCESS RESULTS

(Variability,Statistical Interpratation of results, Statistical Experimental Design, Statistical Process Control - SPC )

OBJECTIVE

Transmit to participants basic statistical concepts to enable them to cientifically interpret results variability and to look for improvements in their industrial processes. Use of statistical design of experiments and statistical process control. Useful for all people that works with  numerical results and aims to improve them.


DIRECTED TO :

Production engeneers, mangers ans supervisors, process engineers and managers, researchers, quality control supervisors  and for trainees training.

PROGRAM

A - PROCESS RESULTS VARIABILITY

1. WHAT IS A PROCESS - Inputs and Outputs of a process, factors that may affect process results. 

2. COLLECTING, PRESENTING AND INTERPRETING RESULTS -  Populations and samples, selecting groups and sub-groups, systematic and random errors. Results presentation.

3. RESULTS FREQUENCY DISTRIBUTION - Frequency distribution models, Normal distribution, Students, Binomial, Poisson and Exponential distributions.

4. BASIC STATISTICAL PARAMETERS - Central tendency and results dispersion ( average, range, variance, standard deviation, relative standard deviation and variation coefficients) 

5. SAMPLE RESULTS RELATED TO POPULATIONS RESULTS - Establishing statistical populations parameters  from sample statistical results. Central limit teereme.  Z, t, F parameters and tables. Testes for statistical significance of results differences.

6. ERRORS - Systematic and random process erros. Outlier identification and rejection tests

7. RESULTS VARIABILITY CAUSES - Factors that may cause results variability. 

8. ANOVA - Results comparison by variance analysis. Multiple comparisons by Student, Tukey and Dunnet methods. Using ANOVA to evaluate parameters variation in process results. Blocking factors and block projects ( Latin and Greco-Latin Projects )

B - LOOKING FOR RESULTS IMPROVEMENT

1. EXPERIMENTS FOR PROCESS KNOWLEDGE  - How to perform experiments to know how parameters affect process results. Statistical Design of Experiments. Statistical interpretation of results. 

2. TYPES OF EXPERIMENTS PROJECTS - Comparative, factorial projects, reduced factorials projects. Screening of factors. EVOP.

C - STATISTICAL PROCESS CONTROL - SPC 

Control charts, processes under statistical control, process capability indexes - Cp e Cpk . Process Validation



SALVI ENGENHARIA - TREINAMENTO E CONSULTORIA
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