Six Sigma Yellow & Green Belt with artificial intelligence (AI) in quality management

The course combines practical Six Sigma knowledge with modern quality management and the use of AI. You will learn the methods from Yellow to Green Belt to implement projects efficiently and manage improvement processes professionally. With additional knowledge of ISO 9001 and AI-supported automation tools, you will be able to optimize QM processes in a standard-compliant, responsible and sustainable manner.
  • Certificates: Certificate "Six Sigma Yellow & Green Belt"
    Certificate "Artificial intelligence (AI) in quality management"
  • Examination: Praxisbezogene Projektarbeiten mit Abschlusspräsentationen
    „Six Sigma Yellow & Green Belt”
  • Teaching Times: Full-time
    Monday 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.)
  • Language of Instruction: German
  • 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)

Artificial intelligence (AI) in quality management

Basics of artificial intelligence in quality management (approx. 2 days)

AI core definitions and technologies

Significance and possible applications for QM


AI in the ISO 9001 context (approx. 1 day)

Process and risk-based approach

Standard-relevant AI fields of application


Data management and analysis (approx. 2 days)

Data quality and preparation

Data availability and documentation

Predictive quality and data-based decisions

Predictive analytics and machine learning

Risk and requirements management with AI


Legal and ethical aspects (approx. 4 days)

AI regulation, GDPR and EU AI Act

ISO/IEC 42001 (management systems for AI)

Corporate compliance

Bias, discrimination, traceability

Responsibility for AI-supported decisions

Current developments regarding ISO 9001:2025


Prompting and automation (approx. 1 day)

Effective prompting for QM applications

Introduction to assisting AI agents in QM (agent-based workflows)

Short workflows with a low-code platform


CIP and process improvement with AI (approx. 2 days)

Process management according to ISO 9001

CIP cycle and automation options

Use of assisting AI agents to support the CIP cycle

Suggestions for improvement with ChatGPT


AI in internal communication (approx. 3 days)

Analyze customer requirements with AI support

Creating texts with AI (audit reports, action plans)

Creating simple learning modules and content as well as

employee training with AI


Auditing and certification (approx. 2 days)

Planning and preparation with AI

AI agents for audit preparation (assistance systems)

Generating audit checklists

Audit programs


Project work (approx. 3 days)

To consolidate the content learned

Presentation of the project results



Changes are possible. The course content is updated regularly.

Professional experience in the production or service sector and basic knowledge of quality management are required.

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 can also use tools such as ChatGPT Team and low-code platforms specifically for process optimization, data analysis and audit preparation. The focus here is on integrating AI into ISO 9001-compliant QM processes, taking legal and ethical requirements into account (AI Act, GDPR) and developing automated solutions for CIP, audit and communication. You will also be able to use and further develop AI applications independently, responsibly and in compliance with standards in quality management.

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.

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.

In addition, your expertise in standard-compliant AI integration makes you a sought-after specialist for companies that want to future-proof their quality management.

Your meaningful certificate provides a detailed insight into the qualifications you have acquired and improves your career prospects.

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).

We will gladly advise you free of charge.

0800 3456-500 Mon. - Fri. from 8 am to 5 pm
free of charge from all German networks.

Contact

We will gladly advise you free of charge. 0800 3456-500 Mon. - Fri. from 8 am to 5 pm free of charge from all German networks.