Mastering Advanced Quality Control #253004

Upon successful completion of this course, participants will be able to:

• Apply advanced statistical process control (SPC) techniques, including capability analysis for non-normal data and multivariate control charts.

• Utilize powerful root cause analysis (RCA) methodologies, such as 8D and 5-Why, to solve complex quality problems permanently.

• Design and analyze experiments (DOE) to optimize processes and robustly design products against noise factors.

• Assess and improve measurement system analysis (MSA) for complex and automated systems, including Gage R&R for destructive testing.

• Integrate advanced quality planning (AQP) methodologies, including Failure Mode and Effects Analysis (FMEA), into the product development lifecycle.

• Lead the implementation of a data-driven quality culture and effectively communicate quality metrics to executive leadership.

This advanced course is designed for experienced quality professionals and engineers:

• Quality Managers, Directors, and Engineers

• Process Engineers and Manufacturing Engineers

• Continuous Improvement Managers and Lean Six Sigma Black Belts

• Production and Operations Managers with quality responsibilities

• Supplier Quality Engineers and Auditors

• R&D Engineers involved in product design and validation

Prerequisite: A foundational understanding of basic quality principles and statistics (e.g., mean, standard deviation, basic control charts) is highly recommended.

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a binder containing a copy of the presentation
• slides and handouts
• Post-assessment

Day 1: Foundations of Advanced Statistical Process Control (SPC)

• Morning Session: Beyond Basic Control Charts

  • Review of Fundamental SPC Concepts: Variation, stability, and capability.

  • Advanced Control Charts: CUSUM and EWMA charts for detecting small shifts.

  • Handling Autocorrelated Processes.

• Afternoon Session: Process Capability Deep Dive

  • Capability Analysis for Non-Normal Data: Transformations and non-normal distributions (Weibull, Gamma).

  • Introduction to Multivariate Process Control.

  • Hands-On Workshop: Use statistical software (Minitab/JMP) to perform a capability analysis on a non-normal data set and interpret the results.

Day 2: Root Cause Analysis & Problem-Solving Frameworks

• Morning Session: Structured Problem-Solving

  • Comparative Analysis of RCA Methods: 8D, A3, and DMAIC.

  • The 8D Process: A step-by-step application for containing and correcting major quality issues.

• Afternoon Session: Advanced Analytical Tools

  • Fault Tree Analysis (FTA) and Is/Is Not Analysis.

  • Practical Exercise: Work through a complex, real-world quality failure using the 8D methodology, culminating in a presentation of findings.

Day 3: Design of Experiments (DOE) for Process Optimization

• Morning Session: Introduction to DOE

  • Terminology: Factors, levels, responses, and interactions.

  • Full Factorial vs. Fractional Factorial Designs: Understanding aliasing and resolution.

• Afternoon Session: Analyzing and Interpreting Experiments

  • Using Statistical Software to create designs and analyze results.

  • Introduction to Response Surface Methodology (RSM) and Robust Design (Taguchi).

  • Workshop: Design, run (via provided data), and analyze a factorial experiment to optimize a key process parameter.

Day 4: Advanced Measurement Systems & Risk Mitigation

• Morning Session: Measurement System Analysis (MSA) Advanced

  • Gage R&R for Non-Destructive and Destructive Testing.

  • Attribute MSA: Agreement analysis for pass/fail data.

  • Calibration Systems and Metrology Fundamentals.

• Afternoon Session: Proactive Risk Management

  • Advanced Failure Mode and Effects Analysis (FMEA): Process and Design FMEA.

  • Calculating and Prioritizing Risk Priority Numbers (RPN).

  • Case Study: Conduct a Process FMEA for a new product introduction.

Day 5: Integration, Leadership, and Capstone

• Morning Session: Quality Leadership and Strategy

  • Creating a Data-Driven Quality Culture.
    *- Auditing Advanced Quality Systems: Ensuring compliance and effectiveness.

  • Communicating the Cost of Quality (COQ) to Senior Management.

• Afternoon Session: Capstone Project

  • Final Application: Participants are given a comprehensive case study with a messy data set and a quality problem. They must:

    1. Perform a capability analysis.

    2. Conduct a root cause analysis.

    3. Propose an experimental design to find a solution.

    4. Present their strategic quality improvement plan.

  • Course Recap: Key Takeaways and Implementation Roadmap.

  • Final Q&A and Certification.