Six Sigma is a frequent term that we all have heard about in our day to day corporate activity. Though a very powerful tool for process improvement, it is vital that it is understood and implemented in the right manner for maximum gain. To help you understand the process better, we have consolidated information pertaining to Six Sigma and how it can help in process improvement in this article.
What is Six Sigma?
To explain in a simple layman term, a near perfection quality is Six Sigma. It is a methodical and data-driven strategy that aims at eliminating defects almost completely in all processes of an organization. The name, Six Sigma, implies that the approach leads to six standard deviations between the mean and the nearest specification limit. To define statistically, a Six Sigma process aims at producing no more than 3.4 defects per million opportunities.
Terms associated with Six Sigma
As Six Sigma is a data-driven approach, the statistical representation of data provides an idea on how the process is performing. In Six Sigma, a defect is anything that is produced outside the specifications provided by the customer. An Opportunity in Six Sigma language is the total quantity of chances for a defect. The Sigma for a process can be easily calculated using the Sigma Calculator by taking into consideration the Sigma defects, opportunity and the associated data.
Objective of Six Sigma Methodology
The main objective of the Six Sigma method is to create an improvement in the process and to provide end products that are almost defect-free by implementing process improvement strategies. Variation reduction is a key concept of Six Sigma where the customer specification is met accurately for greater than 99.9% on an overall basis.
Six Sigma Process
The Six Sigma Process is accomplished through two different methods namely DMAIC and DMADV.
1. DMAIC – It is an acronym for Define, Measure, Analyze, Improve and Control. This system is an improvement process which analyzes the existing system in place and looks for places of improvement to reduce defects.
2. DMADV – It is an acronym for Define, Measure, Analyze, Design and Verify. Unlike the DMAIC process that is used for improvement of existing systems, this method is used basically for developing new processes or products. It is also at times used in case of existing systems when the goal is not just process improvement.
The below is a brief discussion on the various phases of the Six Sigma processes.
1. Define – This is the first stage of both the DMAIC and DMADV methods. This stage is centred on identifying the main goal of the problem. All questions like what is the problem, who is the responsible person for resolving it, why is resolving the problem important, how can it help in process improvement, etc. are answered in this phase.
2. Measure – This phase is all about collecting data and statistics about the current system performance. It is important to know how the system is working now before we improve on it. Charts, maps and tools are used to statistically represent data.
3. Analyze – The data that is collected in the previous phase is analyzed so as to understand what needs to be done for improving the system. The main aspect that is the cause for the system let down is identified in this phase.
The DMAIC and the DMADV methods both are similar for the first 3 steps and differ in the last 2 steps. The DMAIC includes Improve and Control as it is used for an existing system to improve the performance while the DMADV uses Design and Verify phases.
4. Improve – Once the main aspect of error is found out, the root cause is eliminated or improvised so as to find a solution for increasing the performance. This is the step where the system is improved.
5. Control – The statistics are once again measured so as to understand if the change that has been done is good enough to provide the desired performance levels.
6. Design – This phase is a part of the DMADV method and is related to the Improve step of the DMAIC. On contrary to the “Improve” method, the “Design” phase does not include root cause elimination, but involves designing the system as per the desired values from the measurement and analysis phases.
7. Verify – This is again similar to the control phase, where the values obtained after the “Design” phase are compared with those from the “Measure” phase.