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We all know that quality is everyone's responsibility; however, getting everyone to participate is difficult. People need tools to help them identify quality problems and plan corrective action. Let's review seven tools that are helpful in the quality management process.

The first tool is the check sheet. A check sheet is any blank form used to tally quality data and includes time of observation, problems discovered, and number of occurrences of each problem.

The second tool is the histogram. A histogram is a vertical bar chart representing a tabulation of data arranged according to size. This tabulation of data is commonly known as a frequency distribution. The frequency distribution can take a number of shapes. A "normal," or bell-shaped curve indicates that most of the data collected are centered around an average value. A skewed, or off-center, shape indicates that most data are not centered around an average value, but toward either the high or low limit of the range. Skewed data can result when a machined diameter is running consistently toward the high end of the tolerance. A normal distribution would result when most of the diameter readings are near the center of the tolerance.

The third tool is the Pareto chart. A Pareto chart shows how frequently various types of problems occur. A Pareto chart lists the problems discovered along the horizontal axis and the number of occurrences along the vertical axis. In a machining operation, a Pareto chart may indicate: Undersize hole (two occurrences), sharp edge (two occurrences), and oversize diameter (18 occurrences). In this case, the oversize diameter problem should receive the highest priority.

The fourth tool is the cause and effect diagram. The cause and effect diagram consists of a long horizontal arrow with a description of the problem. Causes of the problem are depicted as radial lines from this arrow. Causes for the "causes" are then depicted as horizontal lines from the radial lines. Additional "causes for the causes" are depicted as additional radial lines, and so forth. The completed diagram looks like a skeleton and so is also referred to as a "fishbone diagram." A problem that could benefit from a cause and effect diagram is a poorly machined finish. Causes could be: 1) worn tool, 2) insufficient coolant, or 3) wrong cutting feed. Causes of the worn tool could be: a) no other tool available, b) insufficient inspection of the part, or c) wrong tool for the application.

The fifth tool is the scatter diagram. A scatter diagram is another graphic representation of the interrelation between variables. The horizontal axis contains values of one variable (independent variable), while the vertical axis shows values of the other variable (dependent variable). The relationship between the two variables is indicated by the slope of the diagram, as follows:

• Positive correlation: as one value increases, so does the other.
• Possible positive correlation: as one value increases, the other value increases somewhat.
• No correlation: the results are completely random.
• Possible negative correlation: as one value increases, the other value decreases somewhat.
• Negative correlation: as one value increases, the other decreases.

Note: Correlation does not necessarily mean causality! The correlation results could be caused by an outside factor.

The sixth tool is the control chart. A control chart shows the variability of a process by plotting sample measurements over time. A control chart includes a central line representing the average value and lines representing upper and lower control limits. There are two main types of control charts: X-Bar (x), showing averages of the measurements (center of the process); and R-Bar (r), showing ranges of the measurements in a sample (variability about the center of the process). A manufacturing process is considered under control if recorded readings are within the upper and lower control limits on the chart.

The seventh and last tool is the graph. Typical graphs used in quality measurement include bar graphs, pie charts, line charts, and time series graphs.

These seven tools can assist your quality management effort. Next month, I will discuss seven "new" tools for problem solving and quality management.