Last week we looked at an overview of six sigma, the statistically driven quality control procedure used to improve business consistency and improve efficiencies. The six sigma process is largely an umbrella term for two strategies; six sigma DMAIC and six sigma DMADV. This week we will be looking at the six sigma DMAIC process, defining each term and advising on how you can use them.
Overview of DMAIC
The DMAIC six sigma process is a statistically driven strategy to improve processes or solve problems. The five steps are to define, measure, analyse, improve and control the process on hand. This is an iterative process which can consequently take a number of months to successfully implement.
The first step of the six sigma DMAIC process is define. This involves fully defining and comprehending the goals of process improvement. Here the leaders of the project have to take charge and set the tone for what needs to be improved upon. This process may involve defining customer requirements, developing the problem statement or goals of six sigma, gathering and allocating resources, developing a plan and a project charter. In this stage the team development needs to take place. A clear plan on budget, time plan etc. should be decided upon. It is crucial here that the problem to be addressed aligns with both the customers and the organisation objectives.
The next step in the DMAIC process is to measure. This involves gathering the relative data of interest to the project. Data collected might address how the process currently performs, how often deviations occur and giving numerical basis as to why they are occurring. From data collected, relationships between variables can therefore be built up, giving an indication of how variables effect the process.
The analysation phase of DMAIC involves critically analysing the data which has been collected and using it. Reviewing the data can give you lots of information about why the problem is occurring, how it can be fixed, and even how the process cab be further improved. This step is often coupled with the measurement phase. It helps gain an insight into the crucial variables which affect the process, how these variables can be used to fix the problem, or even improve it above desired operating efficiency.
The next step of the process is to improve it. This part of the process seeks to directly tackle the objective at hand and hence solve the problem. Here the analysis of the data is taken and methods subsequently are devised in which to address the problem and improve upon the process. This is quite an iterative method which make take several tries before the right solution is found. Potential solutions need to be found, critical evaluations of each solution performed, tolerances of the systems numerated and potential failures of each solution found. Selected solutions should then be tested to see if they work as expected and they give the level of process improvement that the process required. The process is iterated until the best solution is implemented.
The whole point of applying the six sigma DMAIC process is to establish consistency in the process. Therefore the last step of the process is control. The improvements made as a result of the six sigma process will be meaningless unless they are sustained. In this step, metrics are developed which can help with monitoring and therefore control of the newly modified process. This requires further analysis of adequate control methods, determining the process capability and implementing a statistically driven control method.