A Strategic Approach To Process Optimization
Like 5S, the Six Sigma process seeks to improve the output of a process, but unlike a 5S methodology, Six Sigma takes a more statistical approach by focusing on eliminating process defects. In statistical terms, the value Sigma represents a standard deviation. Without getting involved in presenting statistical computations, the term Six Sigma refers to the sixth standard deviation from the mean. In the case of manufacturing processes, it technically means seeking to achieve a defect level of 3.4 defects for every million process opportunities – in other words, almost perfection. In practice, the Six Sigma process is designed to formalize a process by which an organization statistically and methodically evaluates various interrelated factors in the production of a "product" with the objective of reducing or eliminates defects.
The DMAIC Model is typically incorporated in the analysis and improvement of existing business processes. It consists of the following 5 steps.
Define – This step includes developing a specific definition of both the opportunity and the objective(s) of the process
Measure – A thorough collection of all relevant process data and statistical assessment of the current state of performance
Analyze – Analyzing the statistical data generated in the Measure stage and applying mathematical and statistical tools to understanding the data reveals where process variations exist and how detrimental variations can be reduced or eliminated.
Improve – Once defects are identified and determined to be commonplace in the process as opposed to aberrant statistical data, improvements are proposed. Experiments are conducted to evaluate possible solutions against other process variables to identify the optimal solution.
Control – In order for this complex process to have lasting value, the Control process carries the work forward by requiring a periodic and systematic review of process data to verify that process data is still accurate and performance continues at peak.
The DMADV model is a corresponding process which applies a Six Sigma approach to the development of new products or technologies.
Define – Again, the scope and objective(s) of the development project are defined in this step.
Measure – A variety of parameters are measured in this step, including product expectations, process capabilities and limitations, and risks.
Analyze – Consider and evaluate a variety of alternatives to reach the defined objective.
Design – The selected alternative as revealed through the Analyze process.
Verify – Prove the process concept in preliminary production testing and once the concept is verified, begin full scale production.
Lean Six Sigma
As Six Sigma has evolved as a methodology, many organizations have combined its statistical principles with Lean principles and processes to produce a hybrid production floor management philosophy called Lean Six Sigma. In this hybrid, the Lean process, which is based on identifying and incorporating opportunities to eliminate waste and streamline production efficiencies combines with the Six Sigma empirical methodology which seeks to eliminate product defects.
In theory, combining these two methodologies makes sense, because at their root, each attacks the problem of waste from a different perspective. The Lean process seeks to optimize the production process by fostering efficiencies in time, motion and other temporal and physical parameters that are easily observed. As a statistical method, the Six Sigma process develops a knowledge base that requires more rigorous, specialized analysts to mine the information found in the data gathered.
On the surface, Lean Six Sigma seems like the "best of both worlds" by offering participants from two distinct perspectives the opportunity to apply their unique expertise and sensibilities to defining a comprehensive corporate initiative to increase value by reducing process inefficiencies and production defects. In a perfect world, out of the coupling these two strategies would evolve into a dramatic reduction in waste and increase in value - defined as features the customer is willing to pay for.