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Certificates: Certificate "Six Sigma Yellow & Green Belt"
Statistics" certificate -
Examination: Praxisbezogene Projektarbeiten mit Abschlusspräsentationen
„Six Sigma Yellow & Green Belt” -
Teaching Times: Full-timeMonday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
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Language of Instruction: German
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Duration: 8 Weeks
Quality management - Six Sigma Yellow & Green Belt
Six Sigma Yellow Belt (approx. 1 week)
Introduction to the Six Sigma strategy - Yellow Belt (approx. 1.5 days)
What is Six Sigma? History and philosophy
DMAIC project phases at a glance and their individual objectives
Roles and responsibilities
Six Sigma in the context of lean and QM (OpEx)
AI as an assistant for structuring the project objective, scope and stakeholders
AI in the improvement project (approx. 0.5 days)
Types of AI (ML,DL,LLM,GenAI)
Data and prompt basics
Governance and security
Define phase (approx. 0.5 days)
Problem and project definition (Project Charter)
Understanding customer requirements (VOC-CTQ)
Process mapping (SIPOC)
Operational definition and data quality
AI-supported clustering of simple VOC examples
Measure phase (approx. 0.5 days)
Process mapping (flow chart and swimlane)
Insight into measurement system analysis (MSA)
Basic key figures (DPMO, Sigma Level)
Data types and collection (graphical analyses)
AI for measurement plan checklists, plausibility checks
Analysis phase (approx. 1 day)
Cause-effect analysis (5-Why, Ishikawa)
Basics of statistical methods
Insight into machines and process capability
Improve phase (approx. 0.5 days)
Generate solution ideas (Poka Yoke)
Risk assessment and introduction of FMEA
Control phase (approx. 0.5 days)
Definition of process monitoring (control plan)
Insight into statistical process control (SPC)
Process documentation and standardization (SOP)
Six Sigma Green Belt (approx. 3 weeks)
Project management with Six Sigma - Green Belt (approx. 1 day)
Green Belts as project managers
Work breakdown structure (WBS), project communication and documentation
Teamwork and leadership
Going through DMAIC project phases using advanced statistics application tools and methods
AI-supported project management: risks/dependencies, schedule risk analysis
Define phase (approx. 1.5 days)
Project profile, business case
Project scoping, stakeholder and risk analysis
VOC in CTQ transformation (CTQ tree)
Team composition, project planning (Gantt chart, milestone planning)
Cost calculation and target formulation (benefit)
Measure phase (approx. 2.5 days)
Advanced statistical basics
Visualization and interpretation (histogram, run chart, box plot)
Short-term vs. long-term capability (MFU, PFU)
Calculation and interpretation of the sigma level
Process indicators (Pp, Ppk, Cp, Cpk)
Measurement system analysis (MSA), bias, gage R&R
AI-supported data checks (missing values, outlier indications)
Analysis phase (approx. 4 days)
Hypothesis development, correlation analysis
Correlation (Pearson) and analysis of variance (ANOVA)
Lean time and value flow (yield, OEE, VSM)
Text/error code clustering for Pareto according to failure modes with AI
Improve phase (approx. 1 day)
Design of Experiments (DoE)
Solution generation and creativity methods (mind mapping, brainstorm/writing, 6-3-5 method)
Testing (Poka Yoke, piloting, cost-benefit analysis)
Risk minimization (FMEA, RPN evaluation)
Implementation
Control phase (approx. 1 day)
Sustainable implementation (control plan)
SPC, quality control charts (X̄-R chart, X̄-s chart)
Process monitoring (KPI, dashboard, BSC)
Project completion and handover
AI-supported KPI story/management summary
Project work, certification preparation and certification examination (approx. 4 days)
Statistics
Statistical basics (approx. 6 days)
Measurement theory basics (population and sample, sample types, measurement and scale levels)
Univariate descriptive statistics (frequency distributions, central measures, measures of dispersion, standard value, histograms, bar charts, pie charts, line charts and box plots)
Bivariate descriptive statistics (measures of correlation, correlation coefficients, crosstabs, scatter plots and grouped bar charts)
Basics of inductive inferential statistics (probability distribution, normal distribution, mean value distribution, significance test, Fisher's null hypothesis test, effect size, parameter estimation, confidence intervals, error bar charts, power analyses and determining the optimum sample size)
Artificial intelligence (AI) in the work process
Presentation of specific AI technologies
and possible applications in the professional environment
Methods for comparing two groups (approx. 5 days)
z- and t-test for a sample (deviation from a specified value)
t-test for the mean difference between two independent/connected samples
Testing the effectiveness of actions, measures, interventions and other changes with t-tests (pretest-posttest designs with two groups)
Supporting significance tests (Anderson-Darling test, Ryan-Joiner test, Levene test, Bonnet test, significance test for correlations)
Nonparametric methods (Wilcoxon test, sign test, Mann-Whitney test)
Contingency analyses (binomial test, Fisher's exact test, chi-square test, cross-tabulations with measures of association)
Methods for comparing the means of several groups (approx. 5 days)
One- and two-factorial analysis of variance (simple and balanced ANOVA)
Multi-factorial analysis of variance (general linear model)
Fixed, random, crossed and nested factors
Multiple comparison methods (Tukey-HSD, Dunnett, Hsu-MCB, Games-Howell)
Interaction analysis (analysis of interaction effects)
Selectivity and power analysis for variance analyses
Introduction to Design of Experiments (DoE) (approx. 1 day)
Full and partial factorial experimental designs
Project work (approx. 3 days)
To consolidate the content learned
Presentation of the project results
Changes are possible. The course content is updated regularly.
The course enables you to implement Six Sigma projects independently and successfully in accordance with ISO 13053-1 (DMAIC). You will be able to use the specific tools and methods with confidence and thus implement complex improvement projects responsibly.
You will also understand the basics of statistics, be able to process and evaluate data and present, explain and interpret statistical data analyses and results using graphics.
People with a degree in engineering, technicians, foremen and specialists from the production and service sectors and people from the areas of quality management, administration and sales who want to carry out and manage improvement projects using the Six Sigma method.
Users and specialists from social and market research, business administration (marketing, business intelligence), technical areas, production, quality assurance and research in the healthcare sector.
Six Sigma is an internationally standardized and recognized method of quality management and a management tool for process improvement. By obtaining the Green Belt, you demonstrate your mastery of the methodology in your profession. As a Six Sigma project manager, you will be in demand across all industries in medium-sized and large companies, thus enhancing your career profile in the long term.
A sound knowledge of statistics is a valuable additional qualification that is in great demand in industrial research and development, in drug development, in the supervision of medical studies, in finance and insurance, in information technology or in public administration.Didactic concept
Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).
You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.
Virtual classroom alfaview®
Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face lessons via video technology.
The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).