Fishbone Diagram Analysis

3.3.2 Cause and Effect or Fishbone Diagram
One analysis tool is the Cause-and-Effect or Fishbone diagram. These are also called Ishikawa diagrams because Kaoru Ishikawa developed them in 1943. They are called fishbone diagrams since they resemble one with the long spine and various connecting branches. Figure 3.3.2 Cause and Effect Diagram
The fishbone chart organizes and displays the relationships between different causes for the effect that is being examined. This chart helps organize the brainstorming process. The major categories of causes are put on major branches connecting to the backbone, and various sub-causes are attached to the branches. A tree-like structure results, showing the many facets of the problem.
The method for using

This procedure alone can uncover some of the reasons a process is not working correctly. Other problems and hidden traps are often uncovered when working through this

Analyzing each of these separately minimizes the number of factors that contribute to the variation in the process. After creating the flowchart, one may want to take another look at the fishbone diagram and see if any other factors have been uncovered. If so, one may need to do another Pareto diagram as well. Quality Control is a continual process, in which factors and causes are constantly reviewed and changes made as required. For example, a flowchart of routine checkup process by a patient in some hospital can be seen in figure 3.3.3 Figure 3.3.3 Flow Chart of patient activities in a hospital
3.3.4 Scatter Plots
The Scatter plot is another problem analysis tool. Scatter plots are also called correlation charts.
A Scatter plot is used to uncover possible cause-and-effect relationships. It is constructed by plotting two variables against one another on a pair of axes. A Scatter plot cannot prove that one variable causes another, but it does show how a pair of variables is related and the strength of that relationship. Statistical tests quantify the degree of correlation between the variables. Figure 3.3.4 Scatter Plot of Student’s height and weight
In this example, there appears to be a relationship between height and weight. As the student gets taller, generally speaking they get heavier.
3.3.5 Check