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Lean Sigma Manufacturing Black Belt Upgrade
Categories:
Process Improvement & Six Sigma
Course Overview
Course Dates
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LEAN SIGMA MANUFACTURING BLACK BELT UPGRADE
Inclusive of:
Comprehensive training manual
Lunches and refreshments
Lean Sigma Toolkit
Access to Lean Sigma Website
INTRODUCTION
For accredited Green Belts, this programme provides the upgrade path to achieve Black Belt status, focusing on the advanced DMAIC tools that are required for more complex projects. The 2-block course format combines training inputs and practical exercises and case study simulations. Delegates are recommended to enter the programme with a suitable Lean Sigma project assigned, which should be progressed in parallel with training.
ACCREDITATION
The Smallpeice accreditation process for Lean Sigma Black Belts incorporates completing a project for formal assessment and passing a multi-choice examination.
BQF Accreditation Option: Smallpeice courses are also licensed for BQF (British Quality Foundation) accreditation, enabling candidates to achieve this external accreditation benchmark. The accreditation steps are as described above, with an additional £175 fee to cover the licensed accreditation route (Note: more details on accreditation options will be provided in Block 1).
BLOCK 1
Define Phase Revisited
Advanced Data Collection Planning
Advanced Statistics
Hypothesis Testing
Regression Analysis
Course Introduction
Expectations & objectives
The role of a Black Belt
Black Belt project selection
Define Phase Revisited
Scoping complex cross-functional projects
Use of quality function deployment to understand the voice of the customer
Benefits calculation & tracking
Planning for change
Managing your Black Belt Project
Advanced Data Collection Planning
Planning data collection for Black Belt projects
Sampling techniques re-visited
Gauge R&R for variable and attribute data (bias & linearity)
Statistical process control for attribute and variable data
Process capability revisited
Advanced Statistics
Basic statistics and probability revisited
Probability distributions
The central limit theorem
Dealing with non-normal data
Planning and communicating data analysis
Hypothesis Testing
Use of inferential statistics
Significance testing route map
Analysis of variable and attribute data
Power & sample size
Non-parametric techniques
Multi-Variable Regression
Introduction to multiple regression
Analysis of multi-variable data
Further diagnostic techniques
Signpost to advanced regression techniques
BLOCK 2
Design of Experiments
Control Phase
Design of Experiments
Introduction to designed experiments (DOE)
Applications of DOE techniques
Basic system optimisation
Screening techniques using DOE
Optimising a worked example
Advanced Design of Experiments
Review of Full Factorial Designs
Benefits & limitations of basic DOE techniques
Introduction to Fractional Factorial
Screening Designs
Overview of advanced techniques
Advanced Design of Experiments (Contd)
Taguchi techniques
Mixed & multi-level experiments
Response surface designs
(CCD, CCF & Box-Behnken designs)
Introduction to evolutionary experimentation
(EVOP techniques)
Note: All DOE modules Include SimWare Simulations & Minitab Analysis, as well as practical experimentation examples
Control
Control phase techniques
Embedding the change within the business
Application of long term MSA
Long-term control
Intro to DFSS
Introduction to design for six sigma and the DMADV methodology
Links to DMAIC
Review & Next Steps Planning
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Key Details
Provided by:
Training Course Provider A054MS
Duration
10 days
£2,500
per delegate
Bookings Helpline: 01933 233884
(Monday to Thursday - 8:00am to 5:30pm and Friday 8:00am to 5:00pm).
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