Quality control management systems go in and out of popularity like the latest fashion trends. As one system loses favor, another pops up to take its place. One of the few that has outlasted other quality management systems is Six Sigma. Originally created and used by Motorola, Six Sigma improves production quality by removing variables that can cause defects.
Six Sigma includes many tools that can be used to implement the system’s basic principles. Everything from flow charts to process mapping can be utilized in order to create better customer satisfaction and to cut back on wastes and defects. Six Sigma has dozens of tools as well as software that is available but there are some basic tools that everyone needs to know.
Lean Six Sigma Resources and Tools
Despite the number of Six Sigma tools and Six Sigma software that is available, the basic tools are the most fundamental. Like learning to do anything, it is always best to start at the beginning. Here are some of the tools which are the foundation for the basic principles for Six Sigma.
Fishbone Diagrams: Also known as Ishikawa diagrams or cause-and-effect diagrams. One of the key theories of Six Sigma is that all outcomes are the result of specific inputs. When there is a problem in production, the fishbone diagram helps to identify the variable inputs that should be checked out. The diagram gets its name because it visually looks like the skeleton of a fish.
If there is a problem with production, to identify it you have to start with the problem of interest which is represented by the head of the fish. To list all the variables of the input, you draw them out like bones on a fish. Each of the six bones represent a category for the variables. A Six Sigma team analyzes the fishbone diagram to try to identify two or three variables that are likely causing the problem. Some areas where the fishbone diagram is often used is in product design and quality defect prevention
Cause-and-Effect (C&E) Matrix: The cause-and-effect matrix is an extension of the fishbone diagram. It is most often used during the measure stage in the DMAIC method. The cause-and-effect matrix assists in exploring and identifying the possible root cause of a problem in workflow.
Flowchart: Flowcharts are used to analyze, create, and manage various programs. They are used in numerous industries and used to describe computer algorithms. The diagram commonly shows step-by-step processes along with arrows to indicate the next step. While flowcharts are common everywhere, they vary due to factors such as type of users or industry.
Failure Modes and Effects Analysis (FMEA): This type of analysis is used to identify ways a process or service might fail. The analysis covers everything from Six Sigma principles, how they are used, and other factors outside of Six Sigma such as how a project is set up. It works by first listing possible failure scenarios. These individual scenarios are each ranked in importance. Second, a list of solutions to correct the failures is created and also ranked. These lists help Six Sigma teams to prioritize and to set up possible solutions beforehand.
Pareto Chart: Named after Vilfredo Pareto, is a chart that highlights the most important factors in production. These factors are displayed in descending order while the line graph shows the cumulative totals. When used for quality control, it represents common causes for defects.
Histogram: This is a graph that uses bars to show tabulated frequencies. They are used to plot the density of data as well as estimating the probability density function of the main variables.
Quality Function Deployment: Also known as the QFD, it is used to identify customer requirements. These requirements are rated from highest to lowest with the highest being the more important and the lowest being the least. Once the requirements are listed, it is up to a Six Sigma team to prioritize them. Each requirment is given a score, with the highest scores being the projects that the team will pursue. The ‘deployment’ part of the name comes from when companies use to delpoy customer service reps to physically go to a customer’s location to better access customer needs and requirements.
Control Charts: Control charts utilize statistical information to monitor and control variables. The control chart is the primary tool of statistical process control, or SPC. In Six Sigma, control charts can plot the performance of a process. A visual representation of the process is created that contains three key elements: a center line, an upper control limit and a lower control limit. Control charts can help determine if a variation is acceptbale or is a result from a problem.
Analysis of Variance: Also known as ANOVA, this is a group of statistical models that give a test of whether the means of several groups are all equal. ANOVA models can be classified in three different ways: fixed-effect, random-effect, and mixed-effect.
Check Sheet: This is a blank document that is used for collecting data in the location where the data is generated. The information that is documented can be either quantitative or qualitative. When the information is quantitative, the checksheet is also known as a tally sheet. One of the characteristsics of a check sheet is that the data is written down and given a check next to it, usually in a box.
Check sheets are classified in 5 basic types:
- Classification: Everything such as defects and failures must be classified into its own category.
- Location: Everything that is listed on the check sheet must have its physical location indicated. Physical items are easy to list their location. Things such as traits or factors must be listed on a picture of the process where the trait is located.
- Frequency: Whenever a trait appears, it is recorded on the check sheet along with how often is appears. The same goes for a trait that doesn’t appear when it is supposed to.
- Measurement Scale: Whenever something must be measured, it can be indicated on a measurement scale on the check sheet.
- Check List: A small box or area where a check can be added whenever items are completed.
Scatter Plot: This is a type of mathematical diagram that displays values for two variables for a set of data. This data is displayed as a collection of separate points and only specifies variables when they exist. One of the most important characteristics of a scatter plot is that it can show nonlinear relationships between variables. A scatter plot is also known as a scatter chart, scatter diagram and scatter graph.