Lean Six Sigma

Many organizations are combining the principles of Lean Manufacturing, Theory of Constraints, and Six Sigma into one program and labeing it Lean Six Sigma

At a high level the three methodologies are summarized below.

  • Lean Manufacturing reduces waste through process map improvements
  • Theory of Constraints concentrates on relieving bottleneck operations
  • Six Sigma reduces and controls process variation with the help of statistics

All three of them have a collective goal to improve the process performance towards a target (improve the mean), improve customer satisfaction and more profitable.

You may fall short of satisifying the customer if using anything short of all three. 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.

Lean Six Sigma

The primary difference between Six Sigma and Lean Manufacturing is:

  • Six Sigma uses statistics to identify and reduce variation in processes to satisfy the customer*. The first priority is control (which lead to precision) and to have that precise output on a target (which is accuracy). 
  • Lean Manufacturing focuses on finding and eliminating waste in processes to satisfy the customer*. This increase the velocity of process flow and thus allows a reduction in inventory (as long as it is a stable process...hence the purpose of Six Sigma) and possibly get cash sooner.
  • Theory of Constraints is a method that is often combined in these two programs. This focuses on evaluating constraints operations and processes and using tools such as Takt Time and Line Balancing to optimize throughput.

*remember the customer is not only the end-user but may also be your company. 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.

It's hard to balance a line of processes if the output is highly variable and contains yield losses, waste, etc. All three 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.  


Learn more about Six Sigma

Learn more about Lean Manufacturing

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Basic Statistics

SPC

Process Mapping

Capability Studies

MSA

Cause & Effect Matrix

FMEA

Multivariate Analysis

Central Limit Theorem

Confidence Intervals

Hypothesis Testing

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1-Way Anova Test

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