Most of QA knows about the Ishikawa’s Seven Basic Tools of quality. These tools are basically used to analyze the reports and finding the root cause of the issues in the system. These seven tools are different ways to analyse the system.
In this post i will just explain the basic of each tool and in later post i will explain each of one in detail.
Ishikawa’s Seven Basic Tools of quality
- Check Sheet ( Checklist)
- Pareto Diagram
- Scatter Diagram
- Run Chart
- Cause Effect Diagram
- Control Chart
1. Check Sheet (Check list):
It is nothing but the checklist mostly printed one but now we can use excel for the same. his checklist consists of may be probable failure list, such as error types, functionality issues, UI issues, code failure (logical errors) , design issues etc where QA needs to put counts of how many time that particular error has been found at different places in the application. result of having this checklist is getting the overall feel/quality of the product.
2. Pareto Diagram:
A Pareto Chart is a series of bars whose heights reflect the frequency or impact of problems. The bars are arranged in descending order of height from left to right. This means the categories represented by the tall bars on the left are relatively more significant then those on the right. This bar chart is used to separate the “vital few” from the “trivial many”. These charts are based on the Pareto Principle which states that 80 percent of the problems come from 20 percent of the causes. Pareto charts are extremely useful because they can be used to identify those factors that have the greatest cumulative effect on the system, and thus screen out the less significant factors in an analysis. Ideally, this allows the user to focus attention on a few important factors in a process.
A Histogram is a variation of a bar chart in which data values are grouped together and put into different classes. This grouping allows you see how frequently data in each class occur in the data set. Higher bars represent more data values in a class. Lower bars represent fewer data values in a class.
4) Scatter Diagram
The scatter diagram is one of the tools of quality. A scatter diagram is a graphical
technique used to analyze the relationship between two variables. It shows whether or not there is correlation between two variables. Correlation refers to the measure of the relationship between two sets of numbers or variables. Two sets of data are plotted on a graph, with the y-axis being used for the variable to be predicted and the x-axis being used for the variable to make the prediction. The graph will show possible relationships (although two variables might appear to be related, they might not be: Those who know most about the variables must make that evaluation). However, correlation does not necessarily mean a direct cause and effect relationship. If it appears that values for one of the variables can be predicted based on the value of the other variable, then there is correlation.
5) Run Chart
Improvement takes place over time. Determining if improvement has really happened and if it is lasting requires observing patterns over time. Run charts are graphs of data over time and are one of the single most important tools in performance improvement. They help improvement teams formulate aims by depicting how well (or poorly) a process is performing. They help in determining when changes are truly improvements by displaying a pattern of data that you can observe as you make changes. They give direction as you work on improvement and information about the value of particular changes.
6) Cause Effect Diagram
The cause and effect diagram is used to explore all the potential or real causes (or inputs) that result in a single effect (or output). Causes are arranged according to their level of importance or detail, resulting in a depiction of relationships and hierarchy of events. This can help you search for root causes, identify areas where there may be problems, and compare the relative importance of different causes.
7) Control Charts:
Control charts are used to routinely monitor quality. Depending on the number of process characteristics to be monitored, there are two basic types of control charts. The first, referred to as a uni-variate control chart, is a graphical display (chart) of one quality characteristic. The second, referred to as a multivariate control chart, is a graphical display of a statistic that summarizes or represents more than one quality characteristic.