Lean Sigma Process Improvement Tools and Techniques

A range of 1 day modules that can be mixed, matched and adapted to suit specific project and organisation requirements

Each programme delivered by industry experienced professionals.  Please call us to discuss your specific requirements

Six Sigma Introduction

This course will give an introduction to the six sigma process. The expected outcome is that the attendee will have a basic overview of the tools, elements and the usage of six sigma.

Course outline
Introduction to six sigma
What is six sigma
Basic terminology
Motorola / GE usage
Measures of quality
Cost of poor quality
Introduction to DMAIC problem solving methodology
Understanding variability
Data collection
Data analysis techniques
Process improvement
Control
SPC
Control charts
Control plans

Lean Introduction

This course will give an introduction to the lean principles and toolkit. The expected outcome is that the attendee will have a basic overview of the lean principles and usage.

Course outline

Introduction to lean
Why lean
Basic terminology
Toyota Production System overview
Lean Toolbox
8 wastes
5S
Kaizen
Work flow
Takt time
KANBAN
Just in time (JIT)
SMED
Total productive maintenance (TPM)
Error proofing
How a lean structure can be implemented
Work "families"
Training regimes

Lean Sigma Introduction

This course will give an introduction to the lean sigma process. The expected outcome is that the attendee will have a basic overview of the integrated usage of lean and six sigma tools.

Course outline

Introduction to Lean sigma
What is lean
What is six sigma
Basic terminology
Why lean and six sigma are complimentary
Measures of quality
Cost of poor quality
Lean techniques to prioritise improvements
8 wastes
5S
Kaizen
Introduction to DMAIC problem solving methodology
Understanding variability
Data collection and analysis techniques
Process improvement
Work flow
KANBAN
Just in time (JIT)
Control
SPC
Control charts
Control plans

Problem Solving

This course will describe structured problem solving tools and practice their usage. The expected outcome is that the attendee will have an understanding of the various problem solving methods and when to use them.

Course outline
Introduction to problem solving
Structured vs unstructured
Basic problem identification
Cost impact of poor problem solving
Different structured approaches
DMAIC
8D
Defining the problem
Critical to quality definitions
Data collection and measurement basics
Sampling
Capability
SPC
Basic data analysis tools
Histograms, Pareto etc.
Basic risk analysis
Developing new solutions
Error proofing
Implementation and control

Data Measurement Techniques

This course will describe data measurement techniques and practice their usage. The expected outcome is that the attendee will have an understanding of the types of data, how to measure, collect it and validate the result.

Course outline
Introduction to lean sigma and data
What is lean sigma
Why lean and six sigma are complimentary
Types of data
Understanding variability
Data collection plans
Different types of variability patterns
Equipment R&R / Measurement system analysis / Gauge R&R
Calculation a process sigma and DPMO
Yield calculations
Sampling techniques
Confidence intervals
Data collection
Identifying the process problem
Brainstorming

Data Analysis Techniques

This course will describe data analysis techniques and practice their usage. The expected outcome is that the attendee will have an understanding of the types of data, how to analyse and present it in the appropriate context.

Course outline
Introduction to lean sigma and data
What is lean sigma
Why lean and six sigma are complimentary
Types of data
Data collection plans
Different types of variability patterns
Data analysis toolbox
Histograms
Pareto
Run charts
Box plots
Regression
Multivariate analysis
Cause and effect diagrams / 5 why's
Confidence intervals
Process mapping
Cause verification

Process Improvement

This course will describe process improvement techniques and practice their usage. The expected outcome is that the attendee will have an understanding of what a process is, how to design a new process and improve an existing process.

Course outline
Introduction to lean sigma process improvement
What is lean sigma
Why lean and six sigma are complimentary
Process improvement methods
Generation of new solutions
Solution selection
Hypothesis testing - T test, ANOVA, Chi Squared
Solution selection matrix
Result analysis
Error proofing
Design of experiments overview
Methods of implementing process improvements
Sustaining improvement
Statistical control
Control plans
Process Scorecards
I, Xbar & R charts
Standardisation
Visual management

Design of Experiments

This course will describe experimental design techniques and practice their usage. The expected outcome is that the attendee will have an understanding of the concept of DOE, the various models available and be able to select the most appropriate for a given situation.

Course outline
Introduction to designed experiments
Basics of experimentation
Different options available for experimentation
Repeatability
Randomisation
Models for designed experiments
Factorial experiments Interactions and effects
Advantages of factorial matrices
Multiple factor experiments
Best design selection
Nested designs
Robustness evaluation
Interaction tables
Variation reduction and process optimisation
Real situation approaches

Statistical Process Control (SPC)

This course will describe statistical process control and practice its usage. The expected outcome is that the attendee will have an understanding of the concepts of process variation, how to measure, understand and control it.

Course outline
Introduction to six sigma and SPC
What is six sigma
Basic terminology
Motorola / GE usage
Measures of quality
Cost of poor quality
Understanding variability
Control Charts
Chart types - Xbar & R, Moving Range etc.
Baseline charts
Calculating control limits
Western Electric rules
Interpreting control charts
Process capability
Cp / Cpk
Individuals vs. subgroups
Ppk vs. Cpk
Single sided distributions
Skewed distributions
SPC programme implementation

Failure Mode and Effect Analysis (FMEA)

This course will describe failure mode and effect analysis and practice its usage. The expected outcome is that the attendee will have an understanding of the concepts of different failure modes, how to pro-actively analyse them, perform risk analysis and create risk mitigation action plans.

Course outline
Overview
What is FMEA
How does the process work
Purpose of FMEA
How is it used
Links to quality systems (ISO9000 etc.)
Design FMEA or Process FMEA
FMEA team selection
Steps to conduct a FMEA
Severity, occurrence and detection ranking
Creation of a control plan
FMEA and continuous improvement