Lean Six Sigma is the combination of principles from Lean Manufacturing, Theory of Constraints, and Six Sigma into one program.
The three methodologies are summarized below.
All three of them have a collective goal to improve the process performance towards a target (improve the mean) and reduce variability, improve customer satisfaction, and profitability.
You may fall short of satisfying the customer if using anything short of all three principles. Any of the three are beneficial but may not be enough alone to get the best results.
A successful project will have controllable inputs that provide consistent and accurate output. This type of result requires the collective use of all three methodologies.
The primary difference between Six Sigma and Lean Manufacturing is:
*Remember the customer is not only the end-user but may also be your company and stakeholders within your company (such as the operators, nurses, drivers, etc.). These concepts are often combined within organizational structures and call "Lean Six Sigma".
Six Sigma is the most math intensive of the three methodologies and uses statistics to drive and validate ideas and processes. The others use more subjective input but all three require data and math to some extent.
Six Sigma has a higher emphasis on product quality than Lean Manufacturing, where-as Lean Manufacturing has a higher emphasis on speed and cycle time reduction than Six Sigma. Both cycle time and quality are important but each program focuses on them to a different extent.
It's hard to balance a line of processes if the output is highly variable and contains yield losses, waste, etc. All three programs play a role and there is some overlap in each of the methods which is the reason why Lean Six Sigma has become more popular.
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Six Sigma
Templates, Tables & Calculators
Six Sigma Slides
Green Belt Program (1,000+ Slides)
Basic Statistics
Cost of Quality
SPC
Process Mapping
Capability Studies
MSA
SIPOC
Cause & Effect Matrix
FMEA
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Central Limit Theorem
Confidence Intervals
Hypothesis Testing
T Tests
1-Way ANOVA
Chi-Square
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Kaizen
MTBF and MTTR
Project Pitfalls
Error Proofing
Z Scores
OEE
Takt Time
Line Balancing
Yield Metrics
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Data Classification
Practice Exam
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