Introduction

This course is intended for Engineers, quality control personnel, inspectors, testing personnel, or those interested in the quality engineering profession.

Objectives

• Understand basic quality management principles.
• The relationship of the quality engineer to the quality system.
• Assess the relationship of statistics to a process.
• Utilise process capability and statistical process control to monitor a process.
• Build acceptance sampling plans and identify and use technical quality tools.
• Incorporate quality technology in design, customer-supplier relationships, Reliability, Availability, and Maintainability (RAM), materials control, measurement, auditing, quality costs and document control within a quality system.
• Problem-solving methods and basic statistical concepts, process control and process capability plans, acceptance sampling, and attribute controls.

Course Outline

Day 1

Overview of Management and Leadership Principles

• Quality Philosophies and Foundations.
• The Quality Management System (QMS).
o Strategic Planning.
o Deployment Techniques.
o Quality Information System (QIS).
• Facilitation Principles and Techniques.
• Customer Relations.
• Supplier Management.

Day 2

The Quality System

• Elements of the Quality System.
• Documentation of the Quality System.
• Quality Standards and Other Guidelines.
• Quality Audits.
• Cost of Quality (COQ).
• Quality Training.

Product and Process Design

• Classification of Quality Characteristics.
• Design Inputs and Review.
• Reliability and Maintainability.

Day 3

Product and Process Control

• Tools.
• Material Control.
• Acceptance Sampling.
• Measurement System Analysis (MSA) and Metrology.

Day 4

Continuous Improvement

• Quality Control Tools.
• Quality Management and Planning Tools.
• Continuous Improvement Techniques.
• Corrective Action.
• Preventive Action.

Day 5

Quantitative Methods and Tools

• Collecting and Summarizing Data
o Descriptive Statistics.
o Graphical Methods for Depicting Relationships.
o Graphical Methods for Depicting Distributions.
o Continuous Distributions.
o Discrete Distributions.
• Statistical Decision-Making
o Point Estimates and Confidence Intervals.
o Hypothesis Testing and Paired-Comparison Tests.
• Relationships between Variables
o Linear Regression and Simple Linear Correlation.
• Statistical Process Control (SPC)
o Objectives and Benefits.
o Common and Special Causes.
o Selection of Variable and Rational Subgrouping.
o Control Charts.
• Process and Performance Capability
o Process Capability Studies and Indices.
• Design and Analysis of Experiments
o Terminology and ANOVA.
o Planning and Organizing Experiments.