Six Sigma - Green Belt
In 2006, we successfully concluded the specialist Six Sigma – Green Belt course. The lecturing instructor was Ing. Marián Kóňa, who is a Black Belt (American Society for Quality).
Six Sigma is a complex manager’s method to achieve the high effectiveness and efficiency of processes carried out in organisations.
The target of the course was to obtain a defined scope of knowledge focused on the purposeful use of statistical and other modern tools and methods which solve Six Sigma projects.
Six Sigma: Pande and co. (2000)
“The Six Sigma method is a complete and flexible system to achieve, maintain and maximise business success. Six Sigma is founded on an understanding of customer needs and expectations, a disciplined use of facts, data and statistical analysis, on a careful approach to management, improvement and creating new business, production and operating processes. Six Sigma is no temporary method associated with a single methodology or strategy; it is a flexible system which perfects business management and its performance. Six Sigma builds on many proven management concepts and the best methods of quality management from the last century.”
Course content:
- Six Sigma concept– Six Sigma concept and targets, organisational benefit of Six Sigma,
- tasks and responsibilities in the Six Sigma programme - tasks and responsibilities of Green Belts, Black Belts and champions/ management,
- historical foundations of Six Sigma – contributions of pioneers: Deming, Juran, Shewhart, Ishikawa, Taguchi,
- Six Sigma project - DMAIC – method of problem solving, Synopsis and project plan, Gantt’s diagram,
- indicators of process performance - DPU, RTY a DPMO, sigma levels,
- process input and output – identification of input and output variable processes, process map, diagram of causes and results, matrix of causes and results,
- selected chapters on statistics – basic concepts, types of data, scales of values, sampling, division of frequency and probability, their representation, normal and binomial division, graphic test of normality, parameters of popular and statistics of selection, estimation of parameters, descriptive statistics, correlation, sources of dispersal and their representation, timeline, tests of statistical hypotheses, t-test, F-test, ANOVA, error of 1st and 2nd type, strength of test, statistical and technical significance, regressive analysis,
- analysis of the measuring system – random and systematic measurement error, linearity, repeatability and reproducibility, assessment of qualities,
- analysis of process capability – short-term and long-term process capability, capability indices Cp, Cpk, Pp, Ppk, realisation of studies of process capability,
- design of experiments methods (DOE) – selection of experiment input and output, experiment plan, types of plans, randomisation, repetition of tests, bloc factor, analysis of experimental data,
- statistical process control (SPC) – principle and targets of SPC, types of regulation diagrams, calculation of regulation media, use of regulation diagram,
- analysis of possible errors and their consequences (FMEA) – aim of FMEA, risk factor (RPN), analysis approach.
Target and aim of the course
To acquire the defined extent of knowledge focused on the purposeful use of statistical and other modern tools and methods in the position of heads or team leaders solving Six Sigma projects.
Opinion of a course participant
”The course was prepared at a professional level; I was very satisfied. Very pleasant surroundings, excellent conditions as far as organisation and refreshments were concerned. The instructor was very well prepared, it was obvious that he had experience in practice, too, which is a good presumption that he can help start off the first projects in companies which decided to use 6 sigma in practice.”
Modern companies who want to keep their position on international markets consider it indispensable to use this information to improve production processes and to become competitive as far as quality, price and profit are concerned.